Anthropic提交S-1，拟首次公开发行Class A普通股并申请以“ANT”在纳斯达克上市

As filed with the Securities and Exchange Commission on October 26, 2026.

Registration No. 333-          

UNITED STATES

SECURITIES AND EXCHANGE COMMISSION

WASHINGTON, D.C. 20549

FORM S-1

REGISTRATION STATEMENT

UNDER

THE SECURITIES ACT OF 1933

Anthropic, PBC

(Exact name of registrant as specified in its charter)

548 Market Street

PMB 90375

San Francisco, California 94104

(415) 326-6303

(Address, including zip code, and telephone number, including area code, of registrant’s principal executive offices)

Dario Amodei, Chief Executive Officer and Co-Founder

Daniela Amodei, President and Co-Founder

Anthropic, PBC

548 Market Street

PMB 90375

San Francisco, California 94104

(415) 326-6303

(Name, address, including zip code, and telephone number, including area code, of agent for service)

Copies to:  

Approximate date of commencement of proposed sale to the public: As soon as practicable after this registration statement becomes effective.

If any of the securities being registered on this Form are to be offered on a delayed or continuous basis pursuant to Rule 415 under the Securities Act of 1933 check the

following box.  £

If this Form is filed to register additional securities for an offering pursuant to Rule 462(b) under the Securities Act, please check the following box and list the Securities

Act registration statement number of the earlier effective registration statement for the same offering.  £

If this Form is a post-effective amendment filed pursuant to Rule 462(c) under the Securities Act, check the following box and list the Securities Act registration

statement number of the earlier effective registration statement for the same offering.  £

If this Form is a post-effective amendment filed pursuant to Rule 462(d) under the Securities Act, check the following box and list the Securities Act registration

statement number of the earlier effective registration statement for the same offering.  £

Indicate by check mark whether the registrant is a large accelerated filer, an accelerated filer, a non-accelerated filer, smaller reporting company, or an emerging growth

company. See the definitions of “large accelerated filer,” “accelerated filer,” “smaller reporting company,” and “emerging growth company” in Rule 12b-2 of the

Exchange Act. 

If an emerging growth company, indicate by check mark if the registrant has elected not to use the extended transition period for complying with any new or revised

financial accounting standards provided pursuant to Section 7(a)(2)(B) of the Securities Act.  £

The registrant hereby amends this registration statement on such date or dates as may be necessary to delay its effective date until the registrant

shall file a further amendment which specifically states that this registration statement shall thereafter become effective in accordance with

Section 8(a) of the Securities Act of 1933, as amended, or until the registration statement shall become effective on such date as the Securities

and Exchange Commission, acting pursuant to said Section 8(a), may determine.

The information in this preliminary prospectus is not complete and may be changed. These securities may not be sold until

the registration statement filed with the Securities and Exchange Commission is effective. This preliminary prospectus is not

an offer to sell nor does it seek an offer to buy these securities in any jurisdiction where the offer or sale is not permitted.

Subject To Completion. Dated           .

This is an initial public offering of shares of Class A common stock of Anthropic, PBC. We are selling            shares of Class A common stock and

the selling stockholders identified in this prospectus are selling an additional            shares of Class A common stock. We will not receive any

proceeds from the sale of shares of our Class A common stock by any of the selling stockholders.

Prior to this offering, there has been no public market for our Class A common stock. It is currently estimated that the initial public offering price

per share will be between $           and $          . We have applied to list our Class A common stock on the Nasdaq Global Select Market under the

symbol “ANT.”

We have a novel capital and corporate governance structure. We are incorporated as a public benefit corporation under Delaware law, a structure

consistent with our commitment to artificial intelligence (“AI”) safety and responsibility. As a public benefit corporation, we are required to

balance the pecuniary interests of our stockholders, the best interests of those materially affected by our conduct, and the specific public benefit

purpose identified in our amended and restated certificate of incorporation: the responsible development and maintenance of advanced AI for

the long-term benefit of humanity. We created our Long-Term Benefit Trust (the “LTBT”) to help ensure that Anthropic, PBC is managed in a

manner that responsibly balances its goals as a public benefit corporation. The LTBT is intended to operate as an independent body of financially

disinterested trustees with expertise in AI safety, national security, public policy, and social enterprise. Through a special class of common stock,

Class T common stock, the LTBT generally has the authority to elect and remove the Class T directors, who together will constitute a majority of

the authorized members of our board of directors. Our Class T common stock does not otherwise have voting rights with respect to matters

submitted to stockholders generally and has no economic rights. Immediately prior to the completion of this offering, we will also issue a single

share of Class F common stock, a special class of our common stock, to a limited liability company organized by our co-founders (the “Founder

LLC”). Dario Amodei, our Chief Executive Officer and a member of our board of directors, and Daniela Amodei, our President and Chairperson of

our board of directors, together with our five other co-founders, will initially be the sole members of the Founder LLC. Our Class F common

stock, which will be held by the Founder LLC, will be entitled to an aggregate number of votes that equals 50.1% of the total voting power of our

outstanding shares of capital stock with respect to matters submitted to stockholders generally, including the election of our directors other than

the Class T directors. Our Class F common stock will not have any economic rights. Upon the completion of this offering, we will also authorize a

special class of our common stock, Class E common stock, which will be issued to our employees, excluding our co-founders. Our Class E

common stock will be entitled to vote only on certain limited matters and will not have any economic rights. In addition, we have authorized

Class A common stock and Class N common stock. The rights of the holders of Class A common stock and Class N common stock are identical,

except with respect to voting and conversion. Each share of Class A common stock is entitled to one vote per share and shares of Class N common

stock have no voting rights, except as otherwise required by law. The holders of our Class N common stock are primarily strategic business

partners, and shares of Class N common stock will generally convert to Class A common stock upon a sale or transfer to an unaffiliated third

party. Our Class A common stock is not convertible. See the sections titled “Risk Factors—Risks Related to our Governance Structure,” “Our

Governance Structure and Its Goals,” and “Description of Capital Stock” for more information.

We are considered a “controlled company” within the meaning of the Nasdaq Global Select Market corporate governance requirements. See the

sections titled “Our Governance Structure and Its Goals,” “Management,” and “Description of Capital Stock” for additional information.

See the section titled “Risk Factors” beginning on page 26 to read about factors you should consider before buying shares of

our Class A common stock.

Neither the Securities and Exchange Commission nor any other regulatory body has approved or disapproved of these securities or

passed upon the accuracy or adequacy of this prospectus. Any representation to the contrary is a criminal offense.

______________

(1)See the section titled “Underwriting” for a description of the compensation payable to the underwriters.

To the extent that the underwriters sell more than            shares of Class A common stock, the underwriters have the option to purchase up to an

additional            shares of Class A common stock from Anthropic, PBC at the initial public offering price less the underwriting discount.

The underwriters expect to deliver the shares against payment in New York, New York, on or about           .

Prospectus dated            

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Through and including            (the 25th day after the date of this prospectus), all dealers effecting

transactions in these securities, whether or not participating in this offering, may be required

to deliver a prospectus. This is in addition to a dealer’s obligation to deliver a prospectus when

acting as an underwriter and with respect to an unsold allotment or subscription.

Neither we nor the selling stockholders, nor any of the underwriters, have authorized anyone to provide any

information or to make any representations other than those contained in this prospectus or in any free writing

prospectuses prepared by or on behalf of us to which we may have referred you in connection with this offering.

Neither we nor the selling stockholders, nor any of the underwriters, take responsibility for, or can provide any

assurance as to the reliability of, any other information that others may give you. This prospectus is an offer to

sell only the shares offered hereby, but only under circumstances and in jurisdictions where it is lawful to do so.

The information contained in this prospectus is current only as of its date, regardless of the time of delivery of

this prospectus or of any sale of our Class A common stock. Our business, financial condition, results of

operations, and prospects may have changed since such date.

For investors outside the United States: This offering includes public offerings in Australia, Canada, certain

member states of the European Economic Area, Japan, Switzerland, and the United Kingdom. We do not

currently intend to list our Class A common stock on any exchange in such jurisdictions. Neither we nor the

selling stockholders, nor any of the underwriters, have done anything that would permit this offering or

possession or distribution of this prospectus in any jurisdiction where action for that purpose is required, other

than in the United States and the jurisdictions listed above. Persons outside the United States who come into

possession of this prospectus must inform themselves about, and observe any restrictions relating to, the

offering of the shares of our Class A common stock and the distribution of this prospectus outside the United

States.

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Select Defined Terms

The following are abbreviations, acronyms, and definitions of certain terms used in this prospectus:

“agent loop” refers to the iterative cycle in which an AI agent receives a task, takes an action, such as planning

a project, running code, or calling a tool, observes the result, and decides its next step, with this cycle repeating

until the task is complete. The agent loop is the core execution pattern underlying agentic AI behavior.

“agentic AI” refers to AI systems that, with varying degrees of autonomy, can plan, determine, and sequence

actions and execute them to accomplish defined objectives, including through interaction with external tools,

services, datasets, and environments on behalf of a user.

“AI” refers to artificial intelligence, a machine-based system that learns or is trained from data and, for explicit

or implicit objectives and with varying levels of autonomy, processes that data to infer patterns, generate

outputs—such as predictions, content, recommendations, and decisions—and act upon physical or virtual

environments.

“AI accelerators” refer to processors purpose-built or adapted for the large-scale computations required to

pre-train, post-train, refine, and run AI models. These processors are significantly more efficient and faster

than general-purpose processors for AI workloads.

“API” refers to application programming interface, a standardized interface that allows external software to

access a system’s capabilities programmatically. AI model providers may offer APIs that allow software

developers to send inputs to an AI model and receive outputs, enabling integration into the software developers’

products and workflows.

“Applied AI” refers to a discipline and organizational function focused on embedding AI capabilities directly

into production business environments to address specific customer requirements. Applied AI teams, which

include forward-deployed engineers, work with enterprises to design and deploy custom solutions, specialized

workflows, and domain-specific implementations tailored to a customer’s own systems and processes.

“closing the loop” refers to a development cycle in which successive versions of an AI model assist in building

the next, with the goal of compounding capability gains over time.

“compute” refers to the computational processing resources used to train and run AI models, including,

without limitation, specialized AI accelerators, memory, networking, storage, and power systems that are

deployed in data centers or other physical computing environments.

“compute multipliers” refer to algorithmic and methodological improvements in training and inference that

increase the effective output of a given amount of compute.

“computer use” refers to an AI capability that allows a model to observe and interact with a graphical user

interface, such as clicking, typing, and navigating applications, similar to how a human operator would.

“Constitutional AI” refers to an approach to training AI models using a set of written principles, which we

refer to as Claude’s constitution, currently organized around four priorities: being broadly safe, broadly ethical,

compliant with our guidelines, and genuinely helpful. Under Constitutional AI, our models evaluate, critique,

and revise their own responses against these principles, enabling us to define and control model behavior

through auditable principles, rather than relying solely on fixed rule-based instructions or human reviewers.

“context window” refers to the maximum amount of text, code, or other content, measured in tokens, that an

AI model can process in a given request, encompassing instructions, prior conversation history, user input, and

the model’s output.

“CSP” refers to a cloud services provider, a technology company that owns and operates large-scale cloud

computing infrastructure and provides on-demand compute, storage, and networking. CSPs may also serve as

distribution channels through which AI products and services are made available to customers. The largest

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CSPs, sometimes referred to as hyperscalers, operate at global scale with significant infrastructure and market

concentration.

“customer” refers to a prosumer or an organization that uses our models, platform, or applications.

“customers with $100,000 or more of revenue on a TTM basis,” “customers with $1 million or

more of revenue on a TTM basis,” and “customers with $10 million or more of revenue on a TTM

basis” each refer to customers contributing revenue equal to or greater than the applicable dollar amount

during the trailing twelve-month (“TTM”) period ending on the measurement date. For purposes of this metric,

we define a customer as a distinct organization, identified by aggregating the accounts that we determine

belong to the same organization based on internal records and available data. We do not separately define or

internally track a category of “enterprise” customers, and our customers are not segmented or measured

internally by reference to whether a given customer is an “enterprise.” Because spending $100,000 or more on

our products is generally characteristic of organizational rather than individual usage, we use the number of

and revenue from customers with $100,000 or more of revenue on a TTM basis as our measure of enterprise

adoption and engagement with Claude throughout this prospectus, including in references to “enterprise

customers” and “enterprise adoption.”

“frontier AI” refers to AI systems at the current leading edge of capability and safety, performing at or near

the highest levels of any existing system across a broad range of tasks.

“hallucinations” refer to outputs in which an AI model generates factually incorrect or fabricated information

with apparent confidence.

“inference” refers to the process by which a trained AI model processes an input and generates an output.

Inference occurs each time a user or agent interacts with an AI system.

“interleaved thinking” refers to a capability whereby an AI model interposes discrete reasoning steps

between successive tool calls within a single response, rather than confining its reasoning to a single planning

phase at the outset.

“interpretability” refers to research into how and why AI models produce specific outputs, with the goal of

making model behavior more transparent and verifiable, especially in high-stakes applications.

“knowledge work” refers to complex cognitive work and related professional activities, including obtaining,

producing, analyzing, and communicating information through tasks such as coding, drafting analyses,

synthesizing research, building financial models, and managing and automating documents and workflows.

“LLMs” refer to large language models, or AI models trained primarily on large datasets to understand and

generate natural language and computer code.

“mechanistic interpretability” refers to a subfield of interpretability research focused on reverse-

engineering the internal computations of neural networks. Rather than inferring model behavior from inputs

and outputs alone, mechanistic interpretability seeks to identify the specific features and circuits within a model

that give rise to its behavior with the goal of making model reasoning auditable at the mechanism level and

detecting failure modes, including deceptive or unsafe behavior, that may not surface in standard testing.

“model weights” refer to the numerical parameters encoding a trained AI model’s behavior, which are the

primary intellectual asset of a frontier AI developer, representing the accumulated investment in compute, data,

and research.

“multi-agent orchestration” refers to an architecture in which multiple AI agents collaborate on a shared

task, with one coordinating while others execute subtasks in parallel, enabling more complex, long-horizon

work than a single agent can complete alone.

“Net Revenue Retention” reflects customer expansion, contraction, and churn as of a measurement date.

We calculate Net Revenue Retention by dividing the Qualified Customers’ Current Period revenue by their Base

Period revenue. A Qualified Customer is a customer with at least $1 of revenue during the Base Period,

excluding subscribers to our Claude Pro and Max plans, whose fixed-price subscriptions do not reflect the

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expansion and contraction behavior this metric is intended to capture. The Base Period is the three months

ending a year prior to the measurement date. The Current Period is the three months ending as of the

measurement date.

“open-weight” refers to an AI model whose trained model weights, or the numerical parameters encoding the

model’s learned behavior, are publicly released, allowing third parties to download, run, and modify the model,

subject to the terms of the model’s license, without necessarily providing access to the underlying training data

or code.

“pay-for-intelligence” or “consumption” refers to our revenue model under which customers pay for their

usage of our intelligence service, which is metered in tokens and priced according to the model selected.

“persistent,” in the context of AI applications, refers to denoting data, state, or context that is continuously

retained beyond the boundary of a single operation, session, or interaction, remaining accessible for reuse

across subsequent steps, sessions, or workflows without requiring reinitialization.

“post-training” refers to the collection of techniques applied to a pre-trained model to refine its behavior,

including reinforcement learning, supervised refinement methods, and other alignment methods. Post-training

is the stage in which much of the work to make a frontier model helpful, accurate, and safe is performed,

including the application of safety and alignment techniques.

“pre-training” refers to the initial stage of training an AI model, in which the model learns general patterns

and representations from large-scale datasets of text, code, and other data, typically by predicting the next

token in a sequence. The output of pre-training is a base model with broad capabilities that has not yet been

adapted for any specific deployment context.

“primitives” refer to the foundational, modular building blocks of a software system from which more

complex applications and workflows are constructed.

“prompt injection” refers to an adversarial technique in which malicious instructions are embedded in

content an AI model is asked to process, such as websites, documents, or tool outputs, with the aim of

overriding or manipulating the model’s intended behavior, typically without the user’s knowledge.

“prosumers” refer to individual users who subscribe to AI tools to perform knowledge work.

“reinforcement learning” refers to a machine learning approach in which a model learns to perform a task

by taking actions, receiving feedback signals called rewards, and adjusting its behavior to maximize the rewards

it accrues over time. In contemporary AI development, reinforcement learning is widely used to refine model

behavior after pre-training, including to improve helpfulness, accuracy, and adherence to safety guidelines.

“RLHF” refers to reinforcement learning from human feedback, a specific form of reinforcement learning in

which human evaluators rate the model’s responses, and those ratings are used as the reward signal to guide

training.

“Run-Rate Revenue” is an operating metric that refers to the estimated annualized value of our revenue-

generating activity as of a measurement date, calculated as the sum of (i) our consumption-based fees during

the trailing 28-day period ended on the measurement date, multiplied by 13, and (ii) our aggregate monthly

subscription fees as of the measurement date, multiplied by 12. For purposes of calculating Run-Rate Revenue,

consumption-based fees and subscription-based fees are derived from customer usage and active subscriptions.

“SIs” refer to systems integrators, or third-party technology and professional services firms that design, build,

and deploy integrated solutions for customers by combining products and services from multiple technology

vendors into unified systems tailored to customer needs.

“tokens” refer to numeric units into which an AI model converts the data it processes, including text, images,

audio, and video, the number of which varies by the model and tokenizer applied. Tokens are the smallest

individual units of a language model and can correspond to words, subwords, characters, or bytes. A tokenizer

is the component of a model that converts customer inputs into the sequence of tokens the model processes and

then converts the processed tokens into the outputs provided to customers.

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Prospectus Summary

This summary highlights selected information that is presented in greater detail elsewhere in this prospectus.

This summary does not contain all of the information you should consider before investing in our Class A

common stock. You should read this entire prospectus carefully, including the sections titled “Risk Factors,”

“Special Note Regarding Forward-looking Statements,” “Management’s Discussion and Analysis of Financial

Condition and Results of Operations,” “Business,” and “Our Governance Structure and Its Goals,” as well as

our consolidated financial statements and the related notes included elsewhere in this prospectus, before

making an investment decision. Unless the context otherwise requires, the terms “Anthropic,” “the company,”

“we,” “us,” and “our” in this prospectus refer to Anthropic, PBC and its consolidated subsidiaries, and

references to our “common stock” refer to our Class A common stock, Class N common stock, and Class F

common stock (and, where the context requires, our Class T common stock and our Class E common stock).

Overview

For the first time in history, intelligence is something humans can build. The cognitive capability to reason,

analyze, synthesize, decide, and create is producible at scale and accessible on demand. We believe this

abundance of AI will rapidly transform every sector of the global economy in ways greater than the impact of

industrialization, electricity, semiconductors, and the internet. AI that truly delivers on its potential—with the

risks well managed—could significantly accelerate global growth and dramatically improve quality of life for

people around the world.

Anthropic was founded in 2021 by a team of researchers responsible for many of the breakthroughs that define

AI. We are first and foremost a research lab—our mission is the responsible development and maintenance of

advanced AI for the long-term benefit of humanity. This mission directs our focus—along with our talent and

culture, our frontier and safety research, our approach to compute, and our enterprise strategy, it is one of the

core advantages that set us apart. These advantages enable us to continuously advance frontier AI and shape

the standards for its safe and responsible development. Our frontier AI, Claude, is delivered to customers

through our models, platform, and applications. Claude has experienced the fastest enterprise adoption of any

technology in history, as demonstrated by revenue growing from $0 at commercial launch in the first quarter of

2023 to $           for the three months ended September 30, 2026. This rapid and growing adoption generates

two self-reinforcing dynamics—an improvement loop that advances Claude and an investment loop that helps

fund our continued research in frontier AI.

Our Core Advantages

Mission & Focus. All of our efforts are guided by a singular focus on our mission. This focus enables us to

concentrate talent, research, and compute investment on the highest-value work for humanity and to avoid

conflicting priorities. Achieving our mission means the world gains the enormous benefits of frontier AI while

mitigating the most significant risks, and we believe this requires safety and capability to advance together.

Talent & Culture. Our mission and focus enable us to attract and retain world-class talent, including

researchers and engineers who want their work to shape a better future. We also have a culture that promotes a

low-ego, truth-seeking environment, where frontier AI capability and safety are mutually reinforcing. We

believe our culture has driven our talent density as we have scaled.

Frontier & Safety Research. We believe that sustained, focused research at the frontier of intelligence is

required to build the most capable and safest AI systems. Our frontier capabilities and safety research are

deeply integrated and directly shape model design, training, and deployment, helping us produce systems that

are more reliable, steerable, and well-suited for real-world deployment, particularly in demanding enterprise

environments. We translate our research leadership into innovation velocity, and have consistently released

better models, platform capabilities, and applications. Each version of a Claude model assists in building the

next, helping to compress development timelines and produce compounding improvements in the speed at

which we innovate. We refer to this recursive dynamic as “closing the loop,” and we believe it is one of the most

significant structural advantages in frontier AI.

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Our Approach to Compute. We manage compute as a single, fungible pool from multiple strategic partners, and

we dynamically direct available compute between workloads based on where the marginal unit is expected to be

most productive at any given time. We believe that this approach to compute enables us to deliver superior

models, serve more customers, and achieve greater productivity from our compute investment. This compute

efficiency creates the foundation for us to advance the frontier of AI capabilities through research and model

development, meet growing demand from customers, and provide for internal usage of Claude. We have

achieved this through our research breakthroughs and our multi-chip compute architecture across AWS

Trainium, Google TPUs, NVIDIA GPUs, and AMD GPUs, enabling us to orchestrate workloads to optimize for

price and performance. To support our research, model development, customer demand, and internal usage of

Claude, we continue to invest at scale. As of and subsequent to September 30, 2026, we have entered into

purchase commitments and lease agreements, including short-term commitments, as well as leases not yet

commenced, with an aggregate committed spend of more than $          , substantially all of which is related to

compute and infrastructure. These commitments include approximately $           expected to be incurred before

December 31, 2030, and substantially all of the remainder is expected to be incurred between 2031 and 2045.

Approximately $           of these commitments are due in the next 12 months. See the section titled

“Management’s Discussion and Analysis of Financial Condition and Results of Operations—Liquidity and

Capital Resources—Contractual Obligations” for more information.

Enterprise Strategy. Our enterprise strategy is built on the belief that frontier AI is most valuable in real-world

settings, as deployment across enterprises is where economic impact is greatest and where the improvement

loops from customer feedback are richest. Accordingly, we have organized our research priorities, our product

roadmap, and our go-to-market and Applied AI teams around enterprise use cases, which range from routine

knowledge work to the most complex problems. The customer feedback we gather directs our research focus

and makes Claude more capable over time. This broadens where Claude can be deployed and further expands

enterprise adoption, which helps ensure that the benefits of our AI reach people and organizations at scale.

AI is Transforming Intelligence

We believe that Powerful AI, a highly capable and impactful form of frontier AI characterized by the following

key attributes, will become widely available within a few years:

•cognitive capabilities matching or exceeding those of top human experts across most professional and

scientific disciplines;

•the ability to navigate all interfaces available to a human working virtually, including text, audio, video,

and direct computer control;

•the ability to reason through complex tasks autonomously over extended periods—lasting hours, days,

or weeks—and seek clarification and feedback when needed;

•the ability to coordinate across multiple instances and collaborate with both humans and other AI

systems; and

•the ability to interface with the physical world by digitally controlling laboratory equipment, robotic

systems, and other machines through digital connections.

If Powerful AI is directed at solving humanity’s hardest problems and the risks are managed responsibly, the

potential is extraordinary. The possibilities include compressing decades of scientific progress into years;

accelerating drug discovery, disease detection, and the delivery of personalized therapy; providing individually

tailored education and expert financial and legal advice; advancing power grids and battery design for greater

efficiency and reliability; and extending to the developing world capabilities that took wealthy nations

generations to build.

A Near-Term Opportunity to Transform Cognitive Work

Frontier AI is transforming cognitive work—the application of knowledge, reasoning, and judgment to produce

economic value. We believe it will make humans far more capable and expand the world’s overall capacity for

that work, including accelerating scientific discovery and helping businesses grow. Knowledge workers are the

leading edge of this opportunity. As frontier AI advances, more capable models can unlock entirely new use

1 See the section titled “Industry, Market, and Other Data” for a description of how we calculate annual economic value attributable

to knowledge workers globally.

2 IDC, The Economic Impact of AI: 2026 Edition, doc # US54452226, April 2026. Reflects the annual value created across AI

solutions and services, investments in the AI infrastructure supply chain, and enhancements in enterprise productivity and

efficiency unlocked by AI.

3 IQVIA Institute for Human Data Science, Global Medicine Use Trends 2026, February 2026.

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cases while also efficiently serving a wide range of cognitive work at scale across the capability-cost-speed

curve. We believe the work that knowledge workers perform represented more than $40 trillion in economic

value globally in 2025,1 and with frontier AI’s potential to make them meaningfully more productive, our near-

term opportunity is to expand this value and accelerate economic growth. While it is still early to forecast

frontier AI’s full impact across the economy, International Data Corporation (“IDC”) estimates that investment

in AI solutions and services will yield a cumulative global economic impact of $22.5 trillion by 2031.2 We

believe the impact could be even greater.

Frontier AI May Reshape Entire Sectors and Accelerate Novel Discoveries

We believe frontier AI represents a larger opportunity than any prior technology cycle, and Claude is already

demonstrating this potential. Claude can now execute complex projects autonomously and turn open-ended

tasks into finished, high-quality deliverables. These capabilities enable it to transform the largest sectors of the

economy, driving meaningful gains in productivity and output. Frontier AI’s capabilities may extend beyond

current markets to open entirely new ones, reaching domains such as robotics, advanced manufacturing, and

logistics, and accelerating progress in scientific research, including drug discovery and materials science. For

example, in the life sciences sector, where annual global pharmaceutical spend is expected to exceed $2 trillion

in 2026,3 Claude is used in drug discovery and development by our customers, our biotechnology partners, and

our own researchers. We are also extending Claude into robotics, where our Model Hardware Standard enables

AI agents to operate lab and manufacturing equipment such as microscopes, liquid handlers, and off-the-shelf

robotic arms. Ultimately, we believe frontier AI will help drive global economic growth. As frontier AI makes

workers and organizations more productive, becomes embedded in the products and services they deliver, and

unlocks new business models, it creates economic output that did not previously exist. We believe our

opportunity is to capture a share not only of today’s economic activity but also of that newly created output as

the global economy expands.

The Importance of Safety and Ethical Behavior

While the potential benefits of AI are extraordinary, its rapid advancement will impact the economy and society

in ways that could create significant disruption, particularly if the technology is not developed and deployed

responsibly. For example, bad actors have already conducted high-profile cyberattacks using AI’s capabilities to

discover vulnerabilities, generate malware, and evade detection tools; other risks associated with misuse,

including in the domain of biology, could result in even greater harm. AI deployed at scale also has the potential

to concentrate power and wealth both within and between countries in ways that could erode trust, harm

society, and destabilize the geopolitical order. Misaligned AI systems could corrupt institutional decision-

making or cause large-scale harm through autonomous actions that are not visible or understandable to their

users and operators. We believe that frontier AI companies must invest in safety and alignment to help ensure

the responsible diffusion of this technology. We also believe that safety, alignment, and ethical behavior

resonate particularly strongly with enterprises, where rigorous safeguards, predictable model behavior, and

demonstrable accountability have become decisive criteria in selecting an AI partner for mission-critical

workloads.

Claude as a Virtual Collaborator

We believe we have reached an inflection point where AI systems can function as genuine collaborators in

professional work. They quickly complete substantive tasks that might otherwise occupy a skilled professional

for several hours, a full day, or longer. AI systems are also becoming increasingly capable of performing tasks

that were previously too difficult or costly to complete or surfacing original insights and analyses. We refer to

these AI systems that work alongside humans to perform complex, multi-step work at professional levels as

Virtual Collaborators. Virtual Collaborators carry the access rights, system connections, and context that their

organizations grant them, which allows them to function more accurately and reliably. They can navigate and

use internal tools and execute workflows that span multiple steps that require sustained reasoning. Virtual

4 IDC, Worldwide Developer Population Growth Forecast, 2025–2029, doc # US53789825, September 2025.

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Collaborators are AI designed to be embedded where work gets done, and our aim is to continue extending

them to knowledge workers globally, a population that is estimated to exceed one billion in 2028.4

Claude Code. The clearest manifestation of Virtual Collaborators today is Claude Code, our coding agent and

the product we believe has most concretely defined what autonomous AI work looks like. Claude Code shifted

the market’s understanding of what an AI system could do in collaboration with software developers: the model

suggests the next line of code and goes further by planning, writing, testing, and debugging—a process that

results in production-grade code. Within months of its release, autonomous coding became the reference point

for measuring the progress of frontier AI. For enterprise AI use cases, we believe the launch of Claude Code was

comparable in its impact to the introduction of the first widely adopted conversational AI assistants. What

makes Claude Code a Virtual Collaborator is its sustained reasoning, a harness that translates intent into

actions, an execution environment that maintains a persistent state whether on a developer’s machine or in a

sandboxed cloud environment, integration with existing tools and systems, and a user-friendly interface. Its

uses are highly varied and often surprising: for example, NASA engineers used Claude Code to plan and write

navigation commands for the Mars Perseverance rover, resulting in the first AI-planned drive on Mars.

Software developers are powerful advocates for Claude—they understand how systems work, have credibility

evaluating technical tools, and often serve as internal champions for adopting new technologies. Winning their

trust creates a foundation for broader diffusion of Virtual Collaborators across enterprise workforces. We are

already seeing this pattern play out with non-technical teams increasingly adopting Claude Code and Claude

Cowork to manage their own workflows.

Claude Cowork. All digital work is ultimately an expression of code, and Claude’s mastery of it powers Virtual

Collaborators capable of handling complex work far beyond software development. Claude Cowork extends the

same agentic architecture of Claude Code to knowledge workers broadly by translating a user’s intent into

completed work, autonomously reading files, navigating applications, and executing multi-step workflows on a

user’s desktop while the underlying code is abstracted away. By extending beyond Claude Code with

applications purpose-built for specific professions and industry verticals, we accelerate Claude’s diffusion into

new categories of knowledge work and deepen our presence across the enterprise. As of September 30, 2026,

adoption of Claude Cowork, which we made available as a research preview in January 2026, outpaced the

adoption Claude Code achieved at the equivalent point following its research preview release in February 2025.

In September 2026, we began merging Claude Cowork and Claude.ai, bringing agentic and conversational work

into a unified application. Users can now move from a simple question to complex, multi-step tasks in the same

conversation.

Extending Virtual Collaborators. We believe the trajectory for Virtual Collaborators is clear and accelerating.

Each generation of Claude models has expanded along multiple dimensions: the depth and rigor of their

reasoning, the duration and autonomy of the work they can sustain, the complexity of tasks they can complete,

and the volume of useful output they can produce. Capability evaluations and benchmarking have shown

substantial improvements across Claude model versions in the duration and complexity of tasks that can be

completed reliably, with more recent model versions demonstrating particularly significant advances.

We are building towards a world where Claude can be given open-ended tasks lasting hours, days, or weeks,

and then execute them autonomously with the judgment and initiative of a brilliant colleague. Ultimately,

millions of Virtual Collaborators can run in parallel, each working independently on unrelated problems or

collaborating seamlessly to achieve a shared objective. The result is something without historical precedent:

what we refer to as a country of geniuses in a data center, available to every organization and sector of the

economy.

Enterprise Adoption of Claude

The speed and depth of our enterprise customer adoption are powerful evidence of Claude’s position at the

frontier of AI. Our customer base as of September 30, 2026 includes:

•More than 11,900 customers with $100,000 or more of revenue on a TTM basis;

•More than 1,900 customers with $1 million or more of revenue on a TTM basis; and

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•Approximately 250 customers with $10 million or more of revenue on a TTM basis.

We believe customers choose Claude for a wide variety of use cases, from routine knowledge work to their most

important problems. They come to us for access to frontier AI across our platform and applications that deliver

real-world outcomes. We see this conviction in customer behavior: enterprises consistently utilize our latest

and most capable models as soon as they are released, gravitating to the most advanced option for their highest-

value work. Our customers see us as a long-term partner for the frontier capabilities we offer today, for the

innovation they expect from us in the future, and for our ability to meet their needs across the capability-cost-

speed curve.

Beyond our models, the Claude Platform provides primitives that enable customers to accelerate time-to-value

and leverage Claude’s intelligence in a variety of use cases. These primitives are the same ones we use to build

our own applications. Our applications, such as Claude Code and Claude Cowork, multiply the impact of

employees. Over time, our applications have become more capable and are now frequently being used to

conduct long-running autonomous work alongside employees. Improvements to our models, platform, and

applications accrue to the benefit of our customers and drive continued adoption.

Our commitment to our mission instills confidence in our customers to choose Claude as a trusted partner. Our

investments in research on AI alignment, interpretability, cybersecurity, and enterprise-grade controls aim to

deliver the predictability and dependability that organizations need in customer-facing and regulated contexts.

This trust means that enterprises can expand the scope of the work that they delegate to Claude, as well as the

systems into which Claude is integrated. Enterprises are aligning their strategies around Claude with the

confidence that we are building frontier AI that serves their needs in the long term.

Today, enterprises rely on Claude to reason, plan, and execute across complex workflows with a level of

trustworthiness and judgment that we believe was not previously available from earlier generations of AI.

Customers realize value from Claude in three primary ways: more productive employees, faster processes, and

embedded intelligence in their products. As Claude’s capabilities grow, our customers benefit and often

broaden their adoption of Claude in new workflows. This expanding role reflects a broader shift in how Claude

is used inside the enterprise, from a tool that responds to discrete prompts to a Virtual Collaborator.

We drive the diffusion of Claude primarily by making it accessible across multiple product surfaces. For

example:

•Claude Platform, our comprehensive agentic development environment, provides customers with

direct access to the primitives to build, deploy, and scale their own applications that leverage Claude’s

capabilities within their own products and workflows.

•Claude Code, our coding agent, works alongside human software developers on end-to-end software

development: writing, planning, editing, testing, debugging, and committing code across production-

scale codebases.

•Claude Cowork, our knowledge work agent, has computer use capability that enables it to work with

professionals on end-to-end business tasks: autonomously researching, drafting, analyzing,

synthesizing, and executing other knowledge work.

Much of the diffusion of Claude has been organic. We amplify this with our go-to-market and Applied AI teams,

which extend our reach by meeting customers where they are through distribution partnerships that place

Claude inside customers’ existing technology stacks. For example, Claude is accessible on all three major cloud

platforms—Amazon Web Services (“AWS”), Google Cloud Platform (“GCP”), and Microsoft Azure (“Azure”). We

have a joint go-to-market approach with these CSPs through which we establish direct contractual relationships

with our customers while paying a fee to each CSP. This structure allows us to foster stronger commercial

alignment with these CSPs, avoid channel conflict, set pricing, and realize the financial benefits of ongoing

compute efficiency improvements. Ecosystem partnerships also expand our reach, allowing customers to adopt

Claude through SIs, such as Accenture, Deloitte, KPMG, and PwC, consultants, and data platforms, such as

Salesforce and Snowflake. We recently launched an AI services company, Ode with Anthropic, in partnership

with leading private equity firms to bring Claude’s capabilities to mid-sized companies across sectors, building

solutions on the Claude Platform and supporting customers over the long term.

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Strengths of Our Financial Model

Building and scaling frontier AI is one of the most important and capital-intensive endeavors in history. Our

financial model provides us with the following strengths that allow us to build and scale efficiently:

•Rapid Revenue Growth. Our enterprise strategy is designed to drive durable customer adoption by

embedding Claude directly into business-critical workflows and enabling the development of products

built on Claude. We believe that enterprise customers achieve a compelling return on investment from

Claude, as agentic workflows can drive both top-line growth and efficiency. This enables us to expand

quickly with customers, as demonstrated by our Net Revenue Retention of approximately 900% as of

September 30, 2026. Diffusion also accelerates as our models become more capable and efficient,

allowing us to lower the cost per task for customers. For example, Claude Opus 5.5 reduced customer

costs per task by approximately 40% compared to Claude Opus 5. Lower costs per task drive greater

usage, which in turn drives broader diffusion of Claude. Our compute efficiency allows us to deliver

these reductions while preserving our margins.

•Compute Efficiency. Our compute efficiency drives more intelligence from research and model

development, and we believe this approach can support more customer and internal usage of Claude

for the same amount of compute compared to other approaches. Our compute efficiency is

demonstrated by revenue that grew 1,368% year over year for the three months ended June 30, 2026

compared to compute and infrastructure expenses that grew 300% during the same period.

•Operating Efficiency. Our operating efficiency, derived from our high talent density, our efficient go-

to-market, and how extensively our teams leverage Claude in their work, enables us to scale with a

smaller team relative to other large enterprise technology companies. Our operating efficiency is

demonstrated by TTM revenue per employee of over $6.6 million as of September 30, 2026, compared

to $1.4 million as of September 30, 2025.

The demonstrated growth, scale, and efficiency of our financial model help us to continue making significant

long-term investments to build frontier AI responsibly. Our business trajectory and financial profile have

enabled us to access capital and secure compute from investors and partners. As of June 30, 2026, we had

raised an aggregate of $141.1 billion of capital and had cash and cash equivalents of $112.4 billion and short-

term investments of $19.3 billion.

Our Self-Reinforcing Loops

Our scale and growth create self-reinforcing loops that make Claude better over time and that we believe create

durable competitive advantages.

•Improvement Loop. Enterprise deployments of Claude deepen our understanding of the hard

problems, edge cases, and domain-specific challenges that matter most to our customers. We improve

our models, platform, and applications based on feedback from customers using our offerings in

production across their businesses. These improvements result in wider deployments and adoption

that fuel the next cycle of improvement.

•Investment Loop. Revenue from expanding enterprise adoption helps us to fund the compute,

research, and talent needed to improve Claude. Claude’s advancing capabilities expand the range of

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tasks and workflows customers use Claude for, broadening our addressable market and driving deeper

deployment, additional revenue, and continued reinvestment in Claude.

Claude is Accelerating Our Ability to Close the Loop

Claude itself has become one of the most powerful drivers of our progress—each new version of a Claude model

directly accelerates development of the next. Many aspects of the research, training, and testing of subsequent

model generations now involve Claude, including running experiments, generating and processing training

data, automating evaluations and safety audits, and writing and reviewing code. We refer to this recursive

dynamic as “closing the loop.” A direct expression of this dynamic is our accelerating pace of producing

compute multipliers. More capable models help our researchers discover these improvements faster; in turn,

more powerful compute multipliers enable us to train even more capable models and deploy them more

efficiently.

Our Growth Strategy

We believe the diffusion of AI through the global economy represents one of the largest opportunities in history

to improve how humans live and work, and it is just beginning. In our view, the world has only begun to use the

capabilities of today’s frontier models, and the gap between what Claude can do and how broadly it is used

represents one of our largest growth opportunities, alongside continued advances at the frontier. Claude’s

capabilities have evolved significantly in recent years, and we expect they will continue advancing rapidly. This

will lead not only to an expanding addressable market, but also to an expanding scope of impact on the world.

We aim to ensure that impact is as positive as possible. Our core advantages, the speed and scale of enterprise

adoption of Claude, and our unprecedented financial model enable us to continue investing aggressively to

build an AI-enabled future that benefits humanity broadly. Elements of our growth strategy include:

•Talent and Culture. To recruit world-class researchers and engineers and retain exceptional people, we

intend to continue investing in our low-ego, high-impact, and mission-aligned culture that has driven

our talent density as we have scaled.

•Compute. We intend to secure further compute beyond our existing commitments, expand our own

data center footprint to secure additional long-term compute, improve compute efficiency across our

multi-chip compute architecture, and produce further algorithmic advances in model efficiency.

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•Claude’s Intelligence, Capability, and Safety. We plan to continue advancing Claude’s core intelligence

and safety in tandem, expand the frontier of what AI systems can reliably do, and pioneer new ways AI

can be applied across professional domains.

•Claude’s Accessibility. We plan to continue making Claude’s intelligence accessible across every surface

where work happens, including through our own platform and applications, through AWS, GCP, and

Azure, and through embedding in enterprise applications.

•Claude’s Adoption. We intend to grow our direct go-to-market and Applied AI teams, deepen cloud

distribution partnerships, invest in brand and marketing, and expand our international presence to

drive adoption of Claude as the trusted AI partner for organizations worldwide.

•Enter New Markets. We intend to extend frontier AI to accelerate novel discoveries, reaching domains

from healthcare and life sciences to robotics and physical work, where we believe compounding model

capabilities can unlock transformative opportunities.

•Strategic Transactions and Partnerships. We intend to selectively pursue acquisitions, investments,

and strategic partnerships, including ecosystem partnerships with SIs, consultants, and data platforms,

that accelerate our mission, expand our reach, and strengthen our competitive position.

Our Commitment to Public Benefit

We founded Anthropic on the belief that the most transformative technology in human history demands an

extraordinary level of responsibility, and that responsibility extends far beyond building safe systems. We

intend to direct a meaningful portion of our resources toward ensuring that frontier AI is safe and its benefits

are broadly distributed, which we refer to as our public benefit initiatives.

As part of these initiatives, we contributed 846,840,960 shares of our Class N common stock, representing 5%

of our fully diluted shares as of June 30, 2026 (assuming full conversion of the Amazon Notes, as defined

below), to Anthropic Public Benefit Fund, LLC (the “Anthropic Public Benefit Fund”), our wholly owned

subsidiary dedicated to the Company Purpose (as defined below) (such issuance, the “Initial Public Benefit

Issuance”). Our board of directors has also approved a framework under which it may, in its discretion, issue

shares of our Class N common stock to the Anthropic Public Benefit Fund (or other designee) representing up

to an additional 2% of our then-outstanding shares (plus any shares subject to options, restricted stock units,

and other convertible securities and any shares held by the Anthropic Public Benefit Fund) each time our share

price appreciates 50% above the prior share price milestone, beginning with our initial public offering price (the

“Public Benefit Issuances”). In addition, our co-founders have each pledged to dedicate 80% of their personal

equity in Anthropic to philanthropic causes. For additional information regarding these pledges, including

related risks, see the section titled “Risk Factors—Risks Related to Ownership of our Class A Common Stock.”

Separate from the co-founders’ pledges, we also maintain a donation matching program through which

employees can pledge a meaningful portion of their equity awards toward charitable giving, which we match

with shares of our Class N common stock.

Our Governance Structure and Its Goals

Our novel capital and corporate governance structure has been carefully designed and differs significantly from

that of other public companies. We strive to help bring humanity safely into an era where transformative AI

exerts tremendous and potentially decisive influence over a broad range of human undertakings. Operating as a

public benefit corporation (“PBC”) gives our board of directors the necessary latitude to balance the pecuniary

interests of our stockholders, the best interests of those materially affected by our conduct, and the specific

public benefit purpose that we promote. Our specific public benefit purpose is the responsible development and

maintenance of advanced AI for the long-term benefit of humanity (the “Company Purpose”). In addition, a

financially disinterested trust, which we refer to as the Long-Term Benefit Trust (the “LTBT”) and which

generally has the power to elect and remove a majority of the authorized members of our board of directors, is

designed to supply both the incentives and insights for striking this balance appropriately. We also believe that

our seven co-founders are distinctly equipped to be stewards of our mission.

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Public Benefit Corporation Status

Consistent with our long-term commitment to AI safety and responsibility, we are incorporated as a PBC under

Delaware law. PBCs are a class of corporations that are intended to produce a public benefit and operate in a

responsible and sustainable manner. Under Delaware law, a PBC is required to identify in its certificate of

incorporation the public benefit or benefits it will promote, and its directors have a duty to manage the affairs of

the corporation in a manner that balances the pecuniary interests of the corporation’s stockholders, the best

interests of those materially affected by the corporation’s conduct, and the specific public benefit purpose

identified in the corporation’s certificate of incorporation. As provided in our amended and restated certificate

of incorporation, the public benefit that we promote, which we must always consider in the management of our

company, is the Company Purpose.

Long-Term Benefit Trust

In 2023, we implemented an innovative governance structure featuring the LTBT, which is designed to ensure

that we are managed in a manner that responsibly balances our tripartite goals as a PBC: the pecuniary

interests of our stockholders, the best interests of those materially affected by our conduct, and the Company

Purpose. The LTBT is intended to operate as an independent body of five financially disinterested voting

trustees (“Trustees”) with expertise in AI safety, national security, public policy, and social enterprise. Through

a special class of common stock, Class T common stock, the LTBT generally has the authority to elect and

remove the Class T directors, who together will constitute a majority of the authorized members of our board of

directors. Our Class T common stock does not otherwise have voting rights on matters submitted to

stockholders generally.

Founder Voting Structure

We believe that our seven co-founders, Dario Amodei, Daniela Amodei, Tom Brown, Jack Clark, Jared Kaplan,

Sam McCandlish, and Christopher Olah, as a group, are distinctly equipped to be stewards of our mission.

Immediately prior to the completion of this offering, we will issue a single share of Class F common stock, a

special class of our common stock, to a limited liability company of which our seven co-founders will initially be

the sole members (the “Founder LLC”).

Our Class F common stock will be entitled to an aggregate number of votes that equals 50.1% of the total voting

power of our outstanding shares of capital stock with respect to matters submitted to stockholders generally,

including the election of our directors other than the Class T directors.

Board Governance

Decisions regarding our business and affairs are made by our board of directors. Immediately prior to the

completion of this offering, we will enter into a stockholders’ agreement (the “Stockholders’ Agreement”) with

the LTBT and the Founder LLC, under which they will agree to vote their shares and take other actions to give

effect to the board composition, director nomination, and director removal provisions described in our

governing documents. Collectively, the LTBT and the Founder LLC will have the ability to elect all members of

our board of directors. Regardless of the class or classes of stock by which a director is elected, there is no limit

to the number of terms a director may serve.

While the LTBT has significant influence over our board of directors through its ability to generally elect and

remove a majority of the authorized members of our board of directors, neither the LTBT nor the Trustees have

decision-making authority in the day-to-day management or strategy setting of the company. The LTBT’s role is

to select directors who are well-equipped to make decisions in furtherance of the responsible balancing of the

pecuniary interests of our stockholders, the best interests of those materially affected by our conduct, and the

Company Purpose, and to support our management’s decision-making through advice and guidance.

The Founder LLC will also have significant influence over our business and affairs through its ability to vote our

Class F common stock, which is entitled to an aggregate number of votes that equals 50.1% of the total voting

power of our outstanding shares of capital stock with respect to matters submitted to stockholders generally,

including the election of our directors other than the Class T directors.

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See the sections titled “Risk Factors—Risks Related to our Governance Structure,” “Our Governance Structure

and Its Goals,” “Management,” “Certain Relationships and Related Person Transactions,” and “Description of

Capital Stock” for more information.

Controlled Company Status

We are considered a “controlled company” within the meaning of the Nasdaq Global Select Market corporate

governance requirements because the LTBT, as the sole holder of our Class T common stock, generally has the

power to elect a majority of the authorized members of our board of directors. As such, we are permitted to opt

out of compliance with certain Nasdaq Global Select Market corporate governance requirements. Accordingly, if

we elect not to comply with certain requirements, you will not have the same protections afforded to

stockholders of companies that are subject to all of the Nasdaq Global Select Market corporate governance

requirements. Although we qualify as a “controlled company,” we do not expect to rely on this exemption except

with respect to our nominating and corporate governance committee (“NGC”), which will not consist entirely of

independent directors. Our board of directors currently consists of a majority of independent directors and our

audit and compensation committees currently consist entirely of independent directors. See the sections titled

“Risk Factors—Risks Related to our Governance Structure—We are considered a “controlled company” within

the meaning of the Nasdaq Global Select Market corporate governance requirements, and, as a result, we

qualify for, and currently rely on, exemptions from certain corporate governance requirements,” “Our

Governance Structure and Its Goals,” “Management,” and “Description of Capital Stock” for additional

information.

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Our Capital Structure

The following table summarizes certain key terms of each class or series of our common stock that will be

authorized following the completion of this offering:

For more information about our capital structure, see the section titled “Description of Capital Stock.”

Risk Factors Summary

Our business is subject to numerous risks and uncertainties, including those highlighted in the section titled

“Risk Factors” immediately following this prospectus summary. These risks could adversely affect our business,

financial condition, and results of operations, which could cause the market price of our Class A common stock

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to decline and could result in a loss of all or part of your investment. Additional risks, beyond those summarized

below or discussed elsewhere in this prospectus, may apply to our business, activities, or operations as currently

conducted or as we may conduct them in the future and in the markets in which we operate or may in the future

operate. These risks include the following:

•Our success depends in large part on our ability to continue to develop the most advanced and capable

AI models, and any failure to do so could adversely affect our business.

•If we are unable to secure adequate compute or if we fail to direct our compute effectively across our

workloads, we may be unable to train models that remain competitive with those of our competitors or

adequately serve our customers.

•Constraints on the critical inputs supporting compute could limit our ability to secure adequate

compute.

•We are highly dependent on the continued service of our co-founders, senior management team, and

key technical employees, and the loss of any of these individuals may adversely affect our business,

financial condition, and results of operations.

•Our company culture has contributed to our success and, if we cannot maintain this culture as we

grow, our business could be adversely affected.

•We face intense competition, and if we are unable to compete effectively, our business, financial

condition, and results of operations could be adversely affected.

•If the market for our models, platform, and applications develops more slowly than we expect or

declines, our growth may slow or stall, and our business, financial condition, and results of operations

could be adversely affected.

•If the use of our AI models results in harm, whether through use by malicious actors or misuse by other

third parties, or if our model guardrails or safeguards fail to prevent such misuse, our reputation and

brand, business, financial condition, and results of operations could be adversely affected.

•Our AI models may behave in unintended, misaligned, or autonomous ways, including by taking

harmful actions that no user or third party directed, which could adversely affect our reputation and

brand, business, financial condition, and results of operations.

•We may be exposed to liability, litigation, and regulatory action arising from harms associated with our

AI models, and our contractual protections and insurance may be insufficient, any of which could

adversely affect our business, financial condition, and results of operations.

•A substantial portion of our revenue and accounts receivable is driven by a limited number of

customers and distribution channels, and the loss of, or a significant reduction in, spend from one or

more of our top customers or disruption through those channels could adversely affect our prospects,

business, and financial condition.

•We have a limited operating history in an evolving and nascent industry, which makes it difficult to

evaluate our future prospects and may increase the risk that we will not be successful.

•We are at an early stage of our revenue growth, we have experienced rapid growth in recent periods,

and our historical growth rates are not indicative of future performance or our ability to sustain or

forecast future revenue growth.

•Our business is subject to an evolving and uncertain regulatory and political environment, which could

increase our costs, restrict our operations, or adversely affect demand for our models, platform, and

applications.

•Our reliance on a limited number of CSPs and suppliers, some of which have strategic and investment

relationships with us and are our customers, creates complex dynamics that could give rise to conflicts

of interest and adversely affect our access to compute.

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•Our capital stock structure features certain provisions that are novel or otherwise not common among

other corporations with multiple-class structures, and may effectively eliminate the ability of holders of

our Class A common stock to influence important decisions, including a change in control.

•Our capital structure will concentrate voting power with the LTBT and the Founder LLC for the

foreseeable future and will result in the LTBT and the Founder LLC having voting power that is not

derived from or proportionate to economic interests in our company.

•Our focus on the long-term best interests of our company as a PBC, and the duty of our directors to

balance the pecuniary interests of our stockholders, the best interests of those stakeholders materially

affected by our conduct, and our Company Purpose, may conflict with short-, medium-, or long-term

financial interests and business performance, which may negatively impact the value of our Class A

common stock.

Channels for Disclosure of Information

Investors, the media, and others should note that, following the completion of this offering, we intend to

announce material information to the public through filings with the Securities and Exchange Commission

(“SEC”), the investor relations page on our website (www.anthropic.com), blog posts on our website, press

releases, public conference calls, public webcasts, our X accounts (@AnthropicAI and @ClaudeAI), our

Instagram page (@claudeai), our Threads account (@claudeai), and our LinkedIn page (https://

www.linkedin.com/company/anthropicresearch/).

The information disclosed by the foregoing channels could be deemed to be material information. As such,

following the completion of this offering, we encourage investors, the media, and others to follow the channels

listed above and to review the information disclosed through such channels. We are not incorporating any of

the information in such channels into this prospectus.

Any updates to the list of disclosure channels through which we will announce information will be posted on the

investor relations page on our website.

Corporate Information

We were incorporated as a Delaware PBC in January 2021. Our principal executive offices are located at 548

Market Street, PMB 90375, San Francisco, California 94104, and our telephone number is (415) 326-6303. Our

website address is www.anthropic.com. Information contained on, or that can be accessed through, our website

does not constitute part of this prospectus and references to our website address in this prospectus are inactive

textual references only. You should not consider information contained on our website to be part of this

prospectus or in deciding whether to purchase shares of our Class A common stock.

“Anthropic,” our logo, and our other registered or common law trademarks, service marks, or trade names

appearing in this prospectus are the property of Anthropic, PBC. Other trademarks and trade names referred to

in this prospectus are the property of their respective owners. Solely for convenience, trademarks and trade

names referred to in this prospectus may appear without the ® or ™ symbols, but such references are not

intended to indicate, in any way, that we will not assert, to the fullest extent under applicable law, our rights, or

the rights of any applicable licensor, to these trademarks and trade names. 

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The Offering

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The number of shares of our Class A common stock, Class N common stock, Class T common stock, and Class F

common stock that will be outstanding after this offering is based on            shares of our Class A common stock,

           shares of our Class N common stock, one share of our Class T common stock, and one share of our Class F

common stock outstanding as of September 30, 2026, which reflects:

•the automatic conversion of (i) all            outstanding shares of our Series A, C-1, D-1, D-2, E-1, F-1, G-1,

and H-1 redeemable convertible preferred stock into            shares of Class A common stock and (ii) all

           outstanding shares of our Series B, C-2, D-3, E-2, E-3, E-4, E-5, F-2, G-2, G-3, G-4, H-2, H-3,

and H-4 redeemable convertible preferred stock into            shares of Class N common stock,

immediately prior to the completion of this offering pursuant to the terms of our amended and restated

certificate of incorporation (collectively, the “Preferred Stock Conversion”);

•one share of our Class F common stock that will be issued immediately prior to the completion of this

offering to the Founder LLC (the “Class F Stock Issuance”);

•the conversion of $           in aggregate principal amount of our

outstanding convertible promissory notes into            shares of Class N common stock immediately

prior to the completion of this offering, representing shares issuable to Amazon Web Services, Inc.

upon the completion of this offering without causing it to exceed the applicable ownership cap (the

“Convertible Notes Conversion”);

•the Initial Public Benefit Issuance, the shares of which (i) are considered legally outstanding, (ii) are

not considered outstanding for accounting purposes while held by our wholly owned subsidiary, and

(iii) accordingly will not be reflected as outstanding in our consolidated financial statements; and

•the net issuance of            shares of Class A common stock subject to RSUs for which the service-based

vesting condition was satisfied as of the date of this prospectus and the performance-based vesting

condition will be satisfied upon the effectiveness of the registration statement of which this prospectus

forms a part, after giving effect to the withholding of            shares of Class A common stock subject to

such RSUs to satisfy the associated estimated tax withholding and remittance obligations (based upon

the assumed initial public offering price of $           per share, which is the midpoint of the estimated

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offering price range set forth on the cover page of this prospectus, and an assumed           % tax

withholding rate) (the “RSU Settlement”).

The shares of our Class A common stock, Class N common stock, Class T common stock, and Class F common

stock outstanding as of September 30, 2026 exclude the following:

•           shares of our Class A common stock issuable upon the exercise of options to purchase shares of

our Class A common stock outstanding as of September 30, 2026, with a weighted-average exercise

price of $           per share;

•           shares of our Class A common stock issuable upon the vesting and settlement of RSUs

outstanding as of the date of this prospectus, but for which (i) the service-based vesting condition was

not satisfied as of such date and (ii) the performance-based vesting condition, if applicable, will be

satisfied upon the effectiveness of the registration statement of which this prospectus forms a part;

•           shares of our Class A common stock issued after September 30, 2026 in connection with our

acquisitions of privately-held companies; and

•           shares of our Class A common stock reserved for future issuance under our equity compensation

plans, consisting of:

◦           shares of our Class A common stock reserved for future issuance upon conversion of Class N

common stock issuable under our Donation Matching Plan (as amended and restated, the

“Donation Matching Plan”);

◦           shares of our Class A common stock to be reserved for future issuance under our 2026

Equity Incentive Plan (our “2026 Plan”), which will become effective prior to the completion of

this offering;

◦           shares of our Class A common stock reserved for future issuance under our Amended and

Restated 2021 Stock Plan (our “2021 Plan”) as of September 30, 2026, which number of shares will

be added to the shares of our Class A common stock to be reserved for future issuance under our

2026 Plan upon its effectiveness, at which time we will cease granting awards under our 2021 Plan;

and

◦           shares of our Class A common stock to be reserved for future issuance under our 2026

Employee Stock Purchase Plan (our “ESPP”), which will become effective prior to the completion

of this offering.

Our 2026 Plan and ESPP each provide for an annual automatic increase in the number of shares of our Class A

common stock reserved thereunder, and our 2026 Plan provides for increases to the number of shares that may

be granted thereunder based on awards under our 2021 Plan that expire or are cancelled or forfeited, and

shares under our 2021 Plan that are tendered to or withheld by us for payment of an exercise price or for

satisfying tax withholding obligations or are forfeited or otherwise repurchased by us, as more fully described in

the section titled “Executive Compensation—Equity Plans.”

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Except as otherwise indicated, all information in this prospectus assumes:

•the Preferred Stock Conversion will occur immediately prior to the completion of this offering;

•the Convertible Notes Conversion will occur immediately prior to the completion of this offering;

•the filing and effectiveness of our amended and restated certificate of incorporation in Delaware and

the effectiveness of our amended and restated bylaws will each occur immediately prior to the

completion of this offering;

•the Class F Stock Issuance will occur immediately prior to the completion of this offering;

•no issuance of shares of Class E common stock prior to the completion of this offering;

•a 10-for-one forward split of our Class A common stock and Class N common stock effected on

September 17, 2026, including a proportional increase in the authorized shares of our capital stock,

with all share, option, RSU, and per share information for all periods presented in this prospectus

adjusted to reflect such forward split on a retroactive basis;

•a one-for-1,000 reverse split of our Class T common stock effected on September 17, 2026;

•no exercise of outstanding stock options or settlement of outstanding RSUs subsequent to September

30, 2026, other than the RSU Settlement; and

•no exercise by the underwriters of their option to purchase up to an additional            shares of our

Class A common stock from us in this offering.

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Summary Consolidated Financial and Other Data

The following tables summarize our consolidated financial and other data. We have derived the summary

consolidated statements of operations data for the years ended December 31, 2023, 2024, and 2025 from our

audited consolidated financial statements included elsewhere in this prospectus. We have derived the summary

consolidated statements of operations data for the six months ended June 30, 2025 and 2026, and the

summary consolidated balance sheet data as of June 30, 2026, from our unaudited interim consolidated

financial statements included elsewhere in this prospectus. The summary consolidated financial data in this

section are not intended to replace our consolidated financial statements and related notes and are qualified in

their entirety by our consolidated financial statements and related notes included elsewhere in this prospectus.

Our historical results are not necessarily indicative of the results that may be expected in the future and our

results for the six months ended June 30, 2026 are not necessarily indicative of the results that may be

expected for the full year ending December 31, 2026 or any other period. The following summary consolidated

financial and other data should be read in conjunction with the section titled “Management’s Discussion and

Analysis of Financial Condition and Results of Operations” and our consolidated financial statements and

related notes thereto included elsewhere in this prospectus.

Consolidated Statements of Operations Data

(1)Includes stock-based compensation expense of $29 million, $192 million, and $1.2 billion for the years ended December 31,

2023, 2024, and 2025, respectively, and $286 million and $2.2 billion for the six months ended June 30, 2025 and 2026,

respectively.

(2)Includes change in fair value of convertible notes, derivative liabilities, and simple agreements for future equity (“SAFEs”),

which were $1.0 billion, $5.4 billion, and $34.3 billion for the years ended December 31, 2023, 2024, and 2025, respectively,

and $10.9 billion and $72.4 billion for the six months ended June 30, 2025 and 2026, respectively. These changes were

primarily driven by an increase in the fair value of our outstanding convertible promissory notes resulting from an increase in

our enterprise valuation during each of the respective periods.

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The following table sets forth the computation of unaudited pro forma net loss per share, basic and diluted, of

common stock attributable to common stockholders for the periods presented:

______________

(1)The unaudited pro forma net loss per share and pro forma weighted-average number of shares used in computing pro forma net

loss per share give effect to (i) the Preferred Stock Conversion, as if such conversion had occurred on January 1, 2025, (ii) the

Convertible Notes Conversion, as if such conversion had occurred on January 1, 2025, (iii) stock-based compensation expense

related to RSUs for which the service-based vesting condition was satisfied or partially satisfied, and as if the performance

condition had been satisfied on January 1, 2025, of $           and $           for the year ended December 31, 2025 and the six

months ended June 30, 2026, respectively, (iv) the net issuance of            and            shares of our Class A common stock upon

the vesting and settlement of RSUs, for which the service-based vesting condition was satisfied, and as if the performance

condition had been satisfied on January 1, 2025, for the year ended December 31, 2025 and the six months ended June 30,

2026, respectively, and (v) the filing and effectiveness of our amended and restated certificate of incorporation in Delaware that

will become effective immediately prior to the completion of this offering. The pro forma weighted-average number of shares

does not give effect to the Initial Public Benefit Issuance, as shares of our Class N common stock held by our wholly owned

subsidiary are not considered outstanding for accounting purposes.

(2)As of           , 2026, unrecognized stock-based compensation expense not reflected in pro forma net loss per share was

$          related to RSUs for which the service-based vesting condition was not satisfied, and which is expected to be recognized

over a weighted-average period of approximately            years, and $           related to our other outstanding equity awards, which

is expected to be recognized over a weighted-average period of approximately            years.

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Consolidated Balance Sheet Data

______________

(1)The pro forma column in the consolidated balance sheet gives effect to (i) the Preferred Stock Conversion, as if such conversion

had occurred on June 30, 2026, (ii) the Convertible Notes Conversion, as if such conversion had occurred on June 30, 2026,

(iii) the Class F Stock Issuance, as if it had occurred on June 30, 2026, (iv) an increase to additional paid-in capital and

accumulated deficit related to stock-based compensation of $           related to RSUs subject to the RSU Settlement, and (v) the

filing and effectiveness of our amended and restated certificate of incorporation in Delaware that will become effective

immediately prior to the completion of this offering.

(2)The pro forma as adjusted column gives effect to (i) the pro forma adjustments set forth above, (ii) the sale and issuance by us

of             shares of our Class A common stock in this offering, based upon the assumed initial public offering price of $           per

share, which is the midpoint of the estimated price range set forth on the cover page of this prospectus, and after deducting

estimated underwriting discounts and commissions and estimated offering expenses payable by us, and (iii) the use of net

proceeds from this offering, together with existing cash and cash equivalents, if necessary, to satisfy the estimated tax

withholding and remittance obligations related to the RSU Settlement. We will not receive any proceeds from the sale of shares

of our Class A common stock by any of the selling stockholders.

(3)Each $1.00 increase (decrease) in the assumed initial public offering price would increase (decrease) each of cash, cash

equivalents, and short-term investments; working capital; total assets; additional paid-in capital; and total stockholders’ deficit

by $          , assuming the number of shares offered by us as stated on the cover page of this prospectus remains unchanged and

after deducting the estimated underwriting discounts and commissions and estimated offering expenses payable by us.

Similarly, an increase (decrease) of 1.0 million shares in the number of shares offered by us, as set forth on the cover page of

this prospectus, would increase (decrease) each of cash, cash equivalents, and short-term investments; working capital; total

assets; additional paid-in capital; and total stockholders’ deficit by $          , assuming the assumed initial public offering price of

$           per share (the midpoint of the price range set forth on the cover page of this prospectus) remains the same, and after

deducting the estimated underwriting discounts and commissions and estimated offering expenses payable by us. We will not

receive any proceeds from the sale of shares of our Class A common stock by any of the selling stockholders.

(4)Working capital is defined as current assets less current liabilities.

Non-GAAP Financial Measures

In addition to the measures presented in our consolidated financial statements that were prepared in

accordance with accounting principles generally accepted in the United States (“GAAP”), we use Adjusted

Operating Income (Loss), Adjusted Operating Margin, and Adjusted Net Income (Loss) as non-GAAP financial

measures to evaluate our business, measure our performance, identify trends affecting our business, formulate

business plans, and make strategic decisions.

See the section titled “Management’s Discussion and Analysis of Financial Condition and Results of Operations

—Non-GAAP Financial Measures” for a definition of each non-GAAP financial measure, a discussion of the

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limitations of each non-GAAP financial measure, and a reconciliation of each non-GAAP financial measure to

its most comparable GAAP financial measure for the periods presented and additional information. 

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Risk Factors

Investing in our Class A common stock involves a high degree of risk. You should carefully consider the risks

and uncertainties described below, together with all of the other information in this prospectus, including the

section titled “Management’s Discussion and Analysis of Financial Condition and Results of Operations” and

our consolidated financial statements and related notes, before making a decision to invest in our Class A

common stock. The disclosures in this section reflect our beliefs and opinions as to matters that could

materially and adversely affect us in the future, and are not representations as to whether such matters have

or have not occurred previously, except as otherwise disclosed. References to past events are provided by way

of example only and are not intended to be a complete listing or a representation as to their likelihood of

occurring in the future. Our business, financial condition, results of operations, or prospects could also be

adversely affected by risks and uncertainties not currently known to us or that we currently do not believe

are material. If any of the risks actually occur, our business, financial condition, results of operations, and

prospects could be adversely affected. In that event, the market price of our Class A common stock could

decline, and you could lose part or all of your investment.

Risks Related to our Business and Industry

Our success depends in large part on our ability to continue to develop the most advanced and

capable AI models, and any failure to do so could adversely affect our business.

Our success depends in large part on our ability to continuously develop, improve, and deploy the most

advanced, capable, and useful AI models. Achieving and maintaining this position depends on our ability to:

•advance the frontier of AI capabilities through breakthrough research, innovative architectures, and

efficient training methodologies;

•ensure our models are safe, reliable, and trustworthy while maintaining competitive performance;

•secure the compute and infrastructure necessary to power and support our increasing needs;

•advance compute efficiency through algorithmic and architectural innovations, including compute

multiplier advancements;

•retain the continued service of our co-founders, senior management team, and key technical

employees, and attract, retain, and motivate leading researchers, engineers, and technical talent in an

intensely competitive and evolving market;

•continue revenue growth and maintain access to sufficient capital, including through potential equity

and debt financing, to make the investments we believe are necessary to support our growth trajectory;

•secure and maintain relationships with data providers, licensors, and partners to obtain the diverse,

high-quality datasets necessary for world-class model performance;

•secure and maintain relationships with cloud, ecosystem, and other partners to facilitate the diffusion

of Claude;

•build, operate, and maintain the infrastructure required to deploy frontier models cost-effectively and

at scale;

•translate model capabilities into products that meet evolving customer needs and achieve meaningful

adoption;

•allocate substantial financial resources efficiently across research, infrastructure, and operations; and

•navigate an evolving, uncertain, and at times divergent global regulatory landscape and engage with

legislators, regulators, and other stakeholders to promote the development of regulatory frameworks

that we believe are good for society, our customers, and the long-term health of the global economy.

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Our failure to achieve any of the foregoing could prevent us from maintaining our competitive position, cause

us to fall behind competitors, reduce customer adoption of, or demand for, our models, platform, and

applications, and impair our revenue growth. Limitations to our revenue growth could, in turn, constrain our

ability to fund the substantial and increasing expenditures required for frontier AI development, including

investments in compute, model training, data acquisition, and safety and security systems, as well as our ability

to attract, retain, and appropriately compensate highly skilled technical and operational personnel in a highly

competitive market. Any such constraints could slow our rate of development and innovation, degrade model

performance or reliability relative to competitors, limit our participation in industry standards-setting and

regulatory processes, and reduce our attractiveness to enterprises and prosumers. These effects could create a

self-reinforcing or compounding cycle in which diminished growth limits our capacity to invest in the resources

necessary to remain competitive, which in turn could further weaken our ability to sustain or increase our

revenue growth, making it increasingly difficult and costly to regain technological leadership and operate at the

frontier of AI. Any of the foregoing could adversely affect our business, financial condition, and results of

operations.

Our ability to maintain our position at the frontier of AI depends in part on our use of AI systems to accelerate

our research processes, a recursive dynamic we refer to as “closing the loop,” in which successive versions of our

models assist in building the next, with the goal of compounding capability gains over time. Our models have

been and are increasingly becoming critical tools in designing, training, testing, and optimizing next-generation

AI systems. If we fail to direct sufficient compute and research efforts to AI-assisted development, or if our

competitors more effectively leverage AI to enhance their own innovation cycles, we risk falling progressively

further behind as competitors continuously use AI to further enhance their own development capabilities,

enabling the creation of increasingly advanced systems at an accelerating pace. As our reliance on our own AI

systems to write production code, conduct research, and build subsequent model versions deepens, any

systemic flaw, bias, or error in our current models could propagate into the next versions of models and

products built using those systems, compounding across successive versions of Claude models in ways that may

be difficult to detect or remediate. If we are unable to manage the foregoing risks, our ability to deploy the most

advanced, capable, and useful AI models could be adversely affected.

In addition, our increasing use of AI systems to accelerate our own research and development may cause the

capabilities of our models to advance more rapidly than our ability to develop, validate, and implement

corresponding safety, alignment, and security measures. Much of our evidence regarding the pace of such AI-

driven acceleration is derived from lagging indicators, and our ability to forecast or measure the rate at which

our capabilities are advancing, including any acceleration attributable to our most recent or unreleased models,

is limited. As a result, we may not identify a significant acceleration in our rate of development until after it has

occurred. If our capabilities were to outpace our safety, alignment, and security measures, or if we were unable

to anticipate the pace of such advancement, we may be unable to adequately assess or mitigate the resulting

risks, which could increase the likelihood of safety incidents, regulatory intervention, or reputational harm, and

could adversely affect our business, financial condition, and results of operations. In light of these uncertainties,

including limits on our ability to observe the pace at which our capabilities are advancing, we have adopted, and

may continue to adopt, precautionary safety, alignment, and security measures to allow our safety efforts to

advance together with model capabilities. In the past these measures have included delaying the release of

models and limiting their initial availability, such as with Mythos through Project Glasswing, and in the future,

as we learn more about model capabilities and behavior, they could include additional measures that affect

whether, how, and when we develop or deploy new models or capabilities. We cannot predict with precision

when we will determine that such measures are necessary, what measures will be required, or how long they

will remain in place, and as the capabilities of our models advance, such measures may become more frequent

and more costly. These measures could slow our capability gains relative to competitors that do not adopt

similar constraints, and could adversely affect our competitive position, revenue growth, and results of

operations.

The development of frontier AI models requires substantial investments of compute resources, capital, and

human capital to conduct large-scale training runs that may span weeks or months and cost many millions of

dollars. There is no guarantee that any given training run will succeed—a run may fail for a number of reasons,

such as failing to achieve the targeted capability or safety thresholds, producing unexpected or undesirable

behaviors that cannot be adequately remediated, or yielding a model that is ultimately not competitive with

alternatives available in the market. We would also face the additional cost and delay of initiating a new training

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run to attempt to achieve the intended model improvements. We have in the past experienced, and may in the

future experience, such failed or underperforming training runs, resulting in a loss of invested resources with

limited or no corresponding benefit to our business. Given the scale of compute and other resources required

for frontier model training and the extended timelines involved, a failed or underperforming training run could

also delay our product roadmap, affect our competitive position, and adversely affect our business, financial

condition, and results of operations.

In addition, new models, features, or capabilities may not be introduced on schedule, may not perform as

intended, may require significant iteration after release, may fail to gain meaningful adoption, or may take

longer than expected to gain meaningful adoption, any of which could reduce customer demand or place us at a

competitive disadvantage. In addition, considerations relating to model safety, interpretability, alignment, and

welfare may lead us to limit or delay the deprecation of older models or to continue supporting legacy versions

alongside newer releases, creating trade-offs in product development and compute distribution that could

adversely affect innovation velocity, infrastructure utilization, and revenue. In addition, customers who have

integrated older models into their workflows may resist migration to newer versions, and any accelerated or

forced deprecation could result in customer attrition, contractual disputes, or reputational harm. We have also

changed, and may in the future change, usage limits, rate limits, or model and product capabilities, which could

adversely affect our reputation and the perceived value of our offerings. Some of these changes have resulted,

and could in the future result, in claims that our disclosures regarding model access or capabilities were

inadequate or misleading.

Further, the industry benchmarks commonly used to test AI models may not accurately reflect real-world

performance or utility, and even models that perform well on such benchmarks may not meet customer

expectations when deployed in production environments, which could lead to customer dissatisfaction, reduced

usage, or reputational harm. If we are unable to effectively innovate and improve our models, platform, and

applications while addressing these challenges, or if competitors are able to deliver AI solutions that are

perceived as more capable, safer, or more reliable, or that offer adequate performance at a lower cost, our

business, financial condition, and results of operations could be adversely affected.

In addition, innovation in AI involves addressing complex and evolving challenges related to data quality, data

integrity, training methodologies, bias, safety, accuracy, and the behavior of model outputs. AI algorithms may

be flawed, and AI systems may contain bugs, errors, or defects or fail to follow instructions or produce

inaccurate, misleading, offensive, inappropriate, or otherwise harmful outputs; reflect or amplify unwanted or

unknown biases present in training data; or raise concerns relating to intellectual property, privacy, or other

legal and ethical considerations. We must continually invest resources to identify, mitigate, remediate, and

reduce the occurrence of such issues, including through managing and improving datasets, training techniques,

evaluation methods, safeguards, and human oversight. However, we may not be able to obtain the datasets that

we need, including through licenses or strategic data partnerships. In addition, we or our data providers may

use synthetic or AI-generated data in the training process, which could introduce quality issues, amplify biases

or errors, contribute to model degradation, or raise novel legal questions regarding ownership, licensing, or

intellectual property rights that may not be timely or clearly resolved by courts or regulators. Such unintended

consequences, failures, or misuse of our models could impair customer trust, slow adoption, expose us to legal

or regulatory scrutiny, or adversely affect our brand and reputation.

If we are unable to secure adequate compute or if we fail to direct our compute effectively

across our workloads, we may be unable to train models that remain competitive with those

of our competitors or adequately serve our customers.

Our ability to develop, train, improve, and deploy frontier models depends on our access to enormous and

increasing quantities of specialized compute. The training of Claude models has required, and we expect will

continue to require, substantial compute. Industry participants, academic researchers, and our own experience

suggest that, in certain contexts, applying greater amounts of compute during model training has been

associated with improvements in model capabilities. These observations are consistent with aspects of broader

empirical relationships among model performance, model size, training data, and compute scale that are

commonly referred to as “Scaling Laws,” although the extent, efficiency, and durability of such improvements

are uncertain, and these relationships may plateau, diminish, or fail to materialize at larger scales or under

different conditions. Accordingly, our ability to remain at the frontier of AI capabilities is substantially

dependent on our ability to secure compute at the scale required to sustain all our workloads, including to train

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next-generation models, and we cannot provide assurance that increased investment in compute will result in

commensurate improvements in model performance.

The market for compute is intensely competitive. We compete for access to compute with some of the world’s

largest and most well-capitalized technology companies, many of which develop their own competitive AI

models and have significantly greater financial resources than us. Many own and operate cloud computing data

center infrastructure, maintain captive chip manufacturing or design capabilities, have long-standing strategic

relationships with key hardware suppliers, or have significant equity investments from, or other financial

arrangements with, such suppliers. These competitors can outbid us for scarce compute, secure priority

allocations from chip manufacturers and CSPs, and make long-term capital commitments that we cannot

match. We expect demand for advanced compute to continue to grow, and the cost of compute could rise

significantly, particularly if AI-driven demand accelerates or if the ability to build highly capable models

becomes more broadly available and shifts competition toward access to advanced compute. Additionally,

numerous well-funded AI companies are pursuing large-scale AI model development, further increasing

demand for limited compute. Certain CSPs from which we obtain substantial compute also develop and offer

their own AI models and related services. As a result, our commercial relationships with these providers may

not always be fully aligned with our long-term interests, and if the compute we have access to from third parties

is curtailed, repriced, or terminated, whether for competitive reasons or otherwise, our business, financial

condition, and results of operations could be adversely affected.

In addition to competition from third parties, our ability to secure compute is subject to allocation decisions by

our CSPs. Although our CSPs are generally subject to contractual commitments with us regarding the provision

of compute, our ability to obtain such capacity remains dependent on those providers’ operational execution,

adherence to the terms of such contractual provisions, and broader business considerations, such as capacity

constraints, internal demand for compute to support their own AI and computing operations, relationships with

or contractual obligations to third parties (which may include other AI companies), and risk management

considerations. As a result, we may not receive the full amount of compute we seek, or such compute may not

be delivered on the timelines we require, even where contractual arrangements are in place. Additionally, we

have in the past sought quantities of compute from CSPs in excess of what those partners were willing to

provide. If our CSPs reduce, limit, or fail to increase our allocations to keep pace with our growing requirements

for any reason, we may need to seek alternative compute sources on less favorable terms or timelines, and we

may be unable to secure adequate alternative compute, or any at all. Any such shortfall could constrain our

ability to train models, serve customers, or maintain our competitive position.

Even if we are able to secure compute, we must still direct it efficiently across the full range of workloads that

are a part of our business, including research, model development, serving customers, and internal usage of

Claude. While we manage our compute as a single, fungible pool and direct available compute between

workloads based on where the marginal unit is expected to be most productive at any given time, there can be

no assurance that this approach to compute will be the most efficient or that it will support the needs of each of

our workloads. Because demand for compute has historically exceeded available capacity, any constraint on our

ability to procure, maintain, or expand that capacity could adversely affect multiple aspects of our business

simultaneously, including our ability to serve customers at the quality and scale they expect, to train and

improve our models, and to develop new products and capabilities. While we actively manage and balance such

compute capacity across these workloads via our capacity management system, if this system fails to perform as

intended, or if our ability to dynamically rebalance capacity across workloads is disrupted, customer-facing

service quality or model and product development timelines could be adversely affected. There can be no

assurance that we will make optimal resourcing decisions, and any significant inefficiencies, including those

related to deployment and rebalancing, could adversely affect both our near-term results of operations and our

long-term strategic position. These compute resourcing challenges are heightened by the growth of our agentic

offerings, which involve multi-step reasoning chains, iterative tool invocations, extended context windows, and

sustained inference sessions that consume significantly more compute per user interaction than single-turn API

calls or chat-based interactions. As agentic workloads grow as a proportion of our total compute demand, the

aggregate compute required to serve our customers could increase disproportionately relative to the associated

revenue, placing additional strain on our compute workload management decisions.

The majority of our compute is procured under multi-year commitments that are typically entered into well in

advance of the periods in which that compute is deployed. Because different AI accelerators have varying

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performance characteristics across workload types, the composition of our committed compute portfolio,

including the mix of accelerator architectures procured from our partners, reflects our demand forecasts and

development roadmap assumptions at the time those commitments are made. If the magnitude or mix of

workloads we need to support differs materially from those forecasts, whether due to changes in model

architecture, customer demand, internal operations, or research priorities, the composition of our available

compute may not optimally match our needs in a given period. This could affect our ability to serve customers,

develop models, and support internal operations.

If we fail to secure sufficient compute, or if we fail to effectively direct the limited compute we have across our

workloads to develop and deploy models with capabilities at least comparable to those of our competitors, we

risk falling behind the technological frontier. The pace of AI development is extremely rapid, with successive

versions of models emerging in compressed timeframes, often measured in months rather than years. As a

result, even a brief period without access to sufficient compute could cause us to fall behind quickly. With AI

development, the gap between frontier models and those one or two versions behind can be significant in terms

of capability, performance, and commercial applicability. Customers, partners, and software developers may

shift to competitors whose models offer superior capabilities, and we may be unable to attract or retain the

technical talent necessary for frontier research if our researchers lack access to adequate compute or if we are

not perceived as operating at the forefront of model development. Any inability to maintain our position at the

frontier could result in loss of customers and revenue, diminished brand and reputation, and a decline in our

competitive position, each of which may be difficult to regain. If we are unable to manage the foregoing risks,

our business, financial condition, and results of operations could be adversely affected.

If our actual compute requirements differ materially from our projections, we may fail to

secure sufficient compute to meet our needs or we may be committed to excess compute that

remains underutilized.

The competitive and structural dynamics of the compute market require us to make binding financial

commitments for compute months or years in advance of our day-to-day delivery and use. Chip manufacturers,

CSPs, and data center developers require advance commitments in order to allocate production capacity, plan

infrastructure investments, and manage their own supply chains. As a result, we must forecast our compute

requirements well in advance of their deployment and commit capital accordingly, often with limited ability to

adjust commitments if our needs change.

These forecasts for future compute usage are inherently uncertain. Our actual compute requirements depend on

numerous factors that are difficult to predict, including the pace of our research progress, the compute intensity

of training techniques we develop or adopt, changes in the competitive landscape that may require us to

accelerate or modify our development plans, customer demand for inference compute, and the evolution of

hardware or other technological efficiencies and changes. If we underestimate our compute requirements, we

may be unable to secure sufficient compute to support our forecasted customer demand and model

development roadmap. In the past, we have significantly underestimated our compute requirements, which left

us capacity constrained and impacted both product development and deployment. Further, the timing of

compute coming online may not align with the timing of demand growth, which could result in periods of

excess or underutilized compute and committed cash outflows that do not produce immediate revenue.

Our ability to forecast and secure the compute we need is further challenged by our ongoing transition from a

cloud-only, fixed-time arrangement compute model to a hybrid model that includes directly leased chips that

are hosted in dedicated data center facilities leased and operated on our behalf, to our specification. This

transition introduces additional variables into our procurement planning, including the timing of facility

completion, the pace at which newly commissioned facilities achieve full operational capacity, our ability to

operate, maintain, and integrate on-premise capacity with cloud-based infrastructure, the operational

execution of our suppliers, and the performance of hardware in new facility environments. Delays in securing

energy, water, and other critical services for these facilities could further slow the pace at which newly

commissioned compute becomes available for use. Errors in forecasting any of these transition-related

variables could compound our risks related to securing sufficient compute and result in either capacity

shortfalls or underutilized capacity during the transition period.

We have entered into, and expect to continue to enter into, long-term agreements for compute and other

compute resources that involve minimum purchase commitments, take-or-pay provisions, and other terms that

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obligate us to pay for resources regardless of actual utilization. These commitments represent substantial fixed

obligations. As of and subsequent to September 30, 2026, we have entered into purchase commitments and

lease agreements, including short-term commitments, as well as leases not yet commenced, with an aggregate

committed spend of more than $          , substantially all of which is related to compute and infrastructure. These

commitments include approximately $           expected to be incurred before December 31, 2030, and

substantially all of the remainder is expected to be incurred between 2031 and 2045. Approximately $           of

these commitments are due in the next 12 months. See the section titled “Management’s Discussion and

Analysis of Financial Condition and Results of Operations—Liquidity and Capital Resources—Contractual

Obligations” for more information.

Our ability to meet the substantial and growing financial obligations of these requirements to secure compute

depends on our ability to generate significant revenue growth. We must grow our customer base and expand

revenue rapidly in order to generate the cash flows necessary to satisfy these commitments. However, our

revenue is primarily consumption-based, and much of it is not subject to long-term contractual commitments,

while our compute and infrastructure commitments generally extend over multiple years. As a result, we may

enter into these obligations based on revenue expectations that may not be realized. If our revenue growth does

not keep pace with our compute-related payment obligations, if we are unable to successfully convert our

compute investment into revenue-generating customer workloads, if we fail to raise additional capital on

acceptable terms, or if we experience other adverse developments affecting our liquidity, we may be unable to

satisfy these obligations. Any such failure could also result in defaults under our agreements, loss of access to

critical resources, and reputational harm. In particular, a default under certain commercial agreements could

trigger cross-default provisions under the A&R Credit Agreement (as defined below), and certain of our

outstanding convertible promissory notes, potentially resulting in the acceleration of substantially all of our

outstanding, and any future, indebtedness. Such cross-defaults could set off a cascading series of adverse

consequences, including the exercise of remedies by multiple creditors, the termination of key commercial

arrangements, enforcement actions against our assets, and severe liquidity constraints. An acceleration of our

indebtedness, combined with the loss of access to critical data center infrastructure, among other things, could

impair our ability to train and deploy models, serve customers, and fund ongoing operations, which could have

an adverse effect on our business, financial condition, and results of operations. For more information, see the

sections titled “—We have incurred significant indebtedness in order to operate and grow our business,

including to fund our substantial compute commitments, and our ability to service this indebtedness may be

constrained by our cash flows and liquidity” and “—We may not have the ability to raise the funds necessary to

repay the principal and accrued interest of our outstanding convertible promissory notes or the A&R Credit

Agreement in cash when required by the terms of the notes or the A&R Credit Agreement, as applicable, or at

their maturity.”

Additionally, the rapid pace of technological change across AI infrastructure, hardware, software, system

architectures, and model development techniques means that compute secured today may become less efficient

or economically attractive relative to future alternatives. We may find ourselves committed to using older-

generation hardware and infrastructure while competitors gain access to more advanced systems, or we may be

paying premium prices for resources that have declined in market value. These dynamics could adversely affect

our cost structure and competitive position. Certain of our financing arrangements require us to enter into

exclusive or preferential supply commitments with particular chip suppliers with respect to the compute

financed pursuant to such arrangements. These commitments may limit our ability to shift procurement to

alternative suppliers or newer chip architectures if our needs or the technology landscape evolve, potentially

leaving us committed to platforms that are suboptimal for our actual workload requirements and reducing our

ability to adjust our compute portfolio in response to changed circumstances. If we are unable to manage the

foregoing risks, our business, financial condition, and results of operations could be adversely affected.

Constraints on the critical inputs supporting compute could limit our ability to secure

adequate compute.

The compute necessary for training and deploying frontier models depends on a supply chain with multiple

potential points of constraint or failure. The availability, pricing, and lead times for compute are affected by the

supply of advanced chips and other IT equipment, the availability of sufficient electrical power and the

infrastructure required to generate and deliver it, and the capacity of data center infrastructure. Each of these

inputs faces significant constraints that may limit our ability to secure the compute we need. In addition,

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increasing demand for compute has contributed to, and may continue to contribute to, increases in the cost of

such resources, which could limit our ability to invest in, develop, or deploy our models, platform, and

applications at the pace we anticipate.

Supply and Concentration of Chips, Memory, and Data Center Equipment

The specialized chips required for AI workloads, particularly high-performance AI accelerators and memory,

are produced by a limited number of manufacturers. The production of advanced chips is extraordinarily

complex, requiring manufacturing processes at the leading edge of technological capability.

The majority of the world’s most advanced chip manufacturing capacity is concentrated in Taiwan, primarily at

Taiwan Semiconductor Manufacturing Company (“TSMC”). This geographic concentration creates significant

risks, including exposure to natural disasters such as earthquakes and typhoons, potential disruption from

geopolitical tensions between Taiwan and China, vulnerability to any interruption in Taiwan’s power grid, water

supply, or other critical infrastructure, and susceptibility to developing trade regulations and restrictions. Any

military conflict, tariffs and trade restrictions, economic coercion, blockade, natural disaster, or other incident

affecting Taiwan could severely disrupt the global supply of advanced chips, with effects that could persist for

years given the time required to construct and qualify alternative fabrication facilities. Efforts to establish

sufficient advanced chip manufacturing capacity outside of Taiwan, including in the United States, remain in

early stages and may not produce adequate compute to materially reduce these concentration risks within the

foreseeable future. In addition, due to the demand for advanced chip manufacturing, TSMC has, at times, been

unable to fully satisfy market demand for chip manufacturing capacity, and as a result, we have not always been

able to obtain sufficient quantities of chips on a timely basis. Accordingly, any restrictions or delays on the

supply of advanced chips out of Taiwan or TSMC would adversely affect our business, financial condition, and

results of operations.

In addition, both high bandwidth memory, which is a key component in high performance AI accelerators, and

other high performance memory products used in compute infrastructure, are largely manufactured by SK

hynix Inc., Samsung Electronics Co., and Micron Technology, Inc. Each of these manufacturers is working to

expand its production capacity to meet demand. However, there is no guarantee that these efforts will result in

adequate supply fast enough to meet demand, particularly if large customers or competitors secure exclusive

supply commitments or otherwise reserve substantially all of a manufacturer’s available production capacity.

The concentration and constraints in manufacturing supply expose us to the risk that manufacturers may make

allocation decisions or strategic shifts that adversely affect our access to the advanced chips needed for our

business. We also face risks that specialized chips may contain defects, or that their production or delivery may

be delayed or disrupted, which, given long replacement lead times, could constrain available compute and

adversely affect our operations and ability to scale. A meaningful portion of the components we and our

partners rely on is sourced from or manufactured outside of the United States, and new or increased tariffs,

import restrictions, or trade disputes could delay deliveries, force supply-chain changes, or raise our costs,

some of which we bear directly under pass-through arrangements. For more information, see the section titled

“—Governmental trade controls, including export and import controls, sanctions, customs requirements, and

related regimes, could subject us to liability or loss of contracting privileges or limit our ability to compete in

certain markets.”

We also depend on third-party chip design and services companies for the design, manufacture, and support of

certain custom accelerator platforms, as well as for related infrastructure financing arrangements. Disruption to

these relationships, or any failure by these parties to deliver hardware or services on expected timelines and

specifications, could adversely affect the availability, performance, or cost of accelerator platforms on which we

rely.

Data centers also require electrical, generation, and transmission equipment, cooling systems, backup

generators, and networking hardware, some of which are made by only a few manufacturers, must be ordered

years in advance, and require substantial pre-delivery payments that we may not recover if our plans change. In

addition, certain equipment, such as high-voltage transformers, switchgear, turbines, generators, substations,

and transmission components, has been subject to extended delivery timelines, price increases, tariffs and

national security requirements, and allocation constraints as demand from data center operators and other

large electricity consumers has grown. If such equipment is delayed or unavailable, we may be able to replace it

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only at higher prices or under less favorable long-term commitments. In order to secure near-term access to

compute, we may also elect, or be required, to procure long-lead-time generation and electrical equipment at

prices above prevailing market rates on the expectation that it can be deployed on an accelerated timeline to

unlock capacity in the near term. Realizing the benefit of paying such prices depends on the timely and

successful engineering, procurement, and construction of the associated facilities, which requires specialized

expertise that is currently in short supply and involves significant execution risk. Delays, cost overruns, or

failure to secure energy on the anticipated schedule could mean that we do not obtain the energy and capacity

for which we paid such prices. In some cases, these arrangements also depend on a developer or other

counterparty agreeing to purchase the equipment at such prices, finance such purchase, and recover those costs

and associated financing costs from us over time, and we may bear these costs even if the underlying capacity is

delayed or never realized. Our equipment supply framework agreements and similar arrangements may expose

us to further risks, including minimum purchase or take-or-pay commitments, price escalation, and obligations

that we are unable to align with our actual deployment needs.

Additionally, the U.S. government has imposed and may continue to impose export controls restricting the sale

of advanced chips and chip manufacturing equipment to certain countries, including China. These restrictions

have affected global chip and related equipment supply allocation, and future changes in export control policy

could affect the availability or pricing of the compute resources on which we rely. Future export controls could

be more restrictive, for example, by placing restrictions on the countries in which advanced chips may be

installed or in which model weights may be stored, which could limit where we or our partners are able to build

data centers, constrain our international expansion, or increase our costs.

Electrical Power and Fuel Constraints

The operation of data centers at the scale required for frontier AI development and deployment consumes

substantial quantities of electrical power. The availability of sufficient electrical power has emerged as a

significant constraint on data center development and expansion in many geographies, including the United

States. Electrical grid infrastructure in the United States and other countries was not designed to accommodate

the rapid increase in demand associated with AI development, and the lead times required to build new

generation capacity, transmission infrastructure, and grid interconnections can extend for years. Demand on

electric grid infrastructure is also increasing as a result of the increased electrification of homes, vehicles, and

industry, and this growing demand is occurring at a time when power generation capacity additions,

transmission expansion, and grid modernization efforts have not kept pace and certain existing generation

resources are being retired, all of which has contributed to higher electricity prices and longer interconnection

timelines in certain regions. We have publicly committed to covering the cost of electricity price increases to

consumers caused by our data centers, including both the cost of electricity itself and the infrastructure

necessary to deliver it.

Our access to electrical power also depends on our ability, and the ability of the third parties on which we rely

for the construction, management, and operation of our data center facilities, to negotiate and maintain

contracts with utility providers and grid operators and to obtain approvals from public utility commissions and

other regulators. These parties may be unable or unwilling to approve, or may condition or delay, the

connections, capacity expansions, special or negotiated rate arrangements, and infrastructure investments

necessary to support data center growth, or may grant them only at costs that limit the economic efficiency and

viability of certain facilities, such as by requiring us to bear grid upgrade or interconnection costs beyond those

attributable to serving our facilities—representing a larger share of costs than is required under existing or prior

regulatory constructs. Interconnection queues for large new electricity loads have also lengthened substantially

in many regions, which could delay or limit our access to grid power. Utility providers and regulators may also

reallocate previously committed capacity that our data center facilities may require. In many jurisdictions, a

single utility provider has substantial control over the terms, timing, and cost of the service and infrastructure

necessary to power our data center facilities. The commercial and regulatory priorities of utility providers may

differ from ours, including with respect to which infrastructure investments are made, how their costs are

allocated, and whether alternative or self-supplied generation arrangements are permitted and on what

conditions. Utility providers and other stakeholders may also seek regulatory or legislative measures affecting

large electricity loads, self-supply, or alternative power generation arrangements. The outcomes of our

negotiations and regulatory proceedings involving utilities are uncertain, and unfavorable results could increase

our costs, delay our projects, or limit the alternatives available to us. More broadly, regulatory proceedings

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relating to cost allocation, rate design, and the treatment of large electricity loads are ongoing in numerous

jurisdictions, and adverse outcomes, changes in policy, or the imposition of new tariffs, surcharges, or

curtailment obligations applicable to data centers could increase our costs or limit our access to electrical

power.

In addition, the construction of the generation and transmission infrastructure on which we depend is itself

capital-intensive and exposed to labor shortages, supply chain disruptions, permitting delays, changes in

interest rates, tariffs, other cost overruns, and financing constraints. The significant and increasing capital

required to fund these generation, transmission, and related infrastructure investments, whether incurred by

us, our utility and energy supply providers, or our data center development partners, is sensitive to prevailing

interest rates and the availability of debt or equity financing on acceptable terms. Any inability of our partners

to access capital when needed, and the limitations, cost, and competition for such capital, could increase the

cost of the power on which we depend, delay or halt projects, or render certain facilities commercially unviable,

and under certain of our arrangements, we bear these financing and capital costs directly or on a pass-through

basis. Furthermore, newer sources of generation, such as solar, wind, battery storage, nuclear, and geothermal

power, may not be available in the quantities or on the timelines we require, or may be available only at higher

cost. Our facilities separately depend on access to reliable water for cooling, which in some regions is scarce,

subject to use restrictions, or increasingly costly. Any of the foregoing could adversely affect the availability of

the power or water we require, increase our costs, or limit our ability to develop, expand, or operate our data

center facilities, which could adversely affect our business, financial condition, and results of operations.

Competition for access to electrical supply and data center locations with adequate power availability is intense,

and we compete for such access with well-capitalized CSPs, some of which produce and develop competing AI

models, cryptocurrency mining operations, and other large-scale electricity consumers. In addition to, or

sometimes in lieu of, grid-based electricity, an increasing share of data centers are being developed with

dedicated on-site power generation capacity that supplies electricity directly to the facility independent of any

utility-operated electric grid. The reliability of such off-grid power generation solutions varies by the underlying

technology, the equipment used, and the operator and will reflect site-by-site operational and environmental

profiles. Development of this new capacity in turn requires power generation and electrical infrastructure that

are themselves subject to supply challenges and operational complexity. For example, certain of our planned

data center facilities rely on dedicated on-site natural gas-fired generation, which exposes us to fuel price

volatility and supply disruptions that are outside of our control and for which we bear the cost on a pass-

through basis. These facilities are also subject to constraints on pipeline capacity and firm fuel transportation

necessary to deliver natural gas. As data center operators increasingly rely on natural gas-fired generation, and

because behind-the-meter and on-site arrangements are feasible only in some jurisdictions given the applicable

regulatory frameworks, we expect increased competition among users for the same natural gas supply and

pipeline capacity in those areas. This competition could drive up the price of natural gas in such areas and may

adversely affect our ability to contract for firm fuel supply and transportation and to secure the pipeline

connections and laterals our facilities require.

These dynamics present several related risks. We may be unable to secure firm gas supply and transportation

during the development of a facility, causing a planned site to be delayed or abandoned; we may face fuel supply

or delivery disruptions once a facility is operating; and because our arrangements generally provide for fuel and

related costs to be borne by us on a pass-through basis without cost caps, we remain exposed to increases in the

cost of natural gas and its transportation. More broadly, the cost of electricity is subject to significant variability

that is largely outside of our control, as wholesale electricity prices fluctuate with changing supply and demand,

weather, fuel prices, tariffs or surcharges, and grid stress, and can rise sharply during periods of peak demand

or constrained supply, and such increases in energy costs could adversely affect our results of operations.

In some regions, including certain regions where we have contracted compute commitments, data center

development has prompted public controversy and regulatory scrutiny regarding environmental impact, land

and water use, and the allocation of limited power resources. For example, if our efforts to secure electrical

power are perceived to affect other utility customers and the broader grid, regulators may impose conditions,

standby charges, or other requirements intended to address such impacts. More broadly, our access to electrical

power is subject to an evolving regulatory framework characterized by complexity, jurisdictional overlap, and

rules that were largely designed around service by incumbent utility providers and existing generation

arrangements and that may not readily accommodate new entrants or alternative approaches, which can result

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in significant delay or prevent the development of the generation we require. Grid-tied electrical supply, for

instance, is subject to the jurisdiction of federal and state energy regulators, regional grid operators, and public

utility commissions, while behind-the-meter and on-site generation is subject to a distinct set of exclusive

service franchise protections, permitting, environmental, air quality, interconnection, and siting requirements.

In addition, environmental standards applicable to power generation continue to evolve, including as a result of

changing governmental priorities and shifting public and political views regarding climate change and the

appropriate treatment of various power generation sources. Any failure to secure access to adequate electrical

power, any legal, regulatory, or other administrative action or change limiting the availability of electricity, or

any significant increase in energy or compliance costs, could adversely affect our cost structure and limit our

ability to scale our compute infrastructure, develop and deploy our models, and service our customers. We have

also made, and may in the future make, voluntary commitments to offset the impact of our data center energy

consumption on local communities and electricity ratepayers, including commitments to cover grid

infrastructure upgrade costs, procure new power generation to match our energy needs, invest in curtailment

systems to reduce strain on the grid during peak demand periods, and address environmental impacts. These

commitments have increased, and we expect will continue to increase, our operating costs. Moreover, we

believe this is part of a broader emerging trend in the AI industry, and such commitments, or similar

obligations, may become increasingly standard or required, which could further increase our costs. In addition,

the physical effects of climate change may increase our operating costs over time, as higher average

temperatures can increase the power consumption and water usage required to cool equipment at the facilities

on which we depend.

Data Center Infrastructure

Even where chips and electrical power are available, the development of data center facilities requires

substantial time, capital, and specialized expertise. Data center construction involves lengthy permitting

processes, complex supply chains for specialized equipment, and significant lead times for the installation and

commissioning of cooling systems, electrical infrastructure, and networking equipment. Labor shortages,

including shortages of, and competition for, electricians, facility technicians, and other skilled tradespeople,

supply chain disruptions, permitting delays, and other factors can extend construction timelines and increase

costs. Further, given data center development projects require advanced and significant capital commitments

with dedicated end users, we have in some cases relied, and expect to continue to rely, on arrangements for

financing or with partners who guarantee the lease obligations to support the development of data center

capacity that is expected to host such partner’s chips or computing infrastructure. In addition, there are a

limited number of qualified third-party vendors with the expertise we require and that support the particular

infrastructure we wish to implement. Accordingly, we rely on this limited number of third parties for the

construction, management, and operation of certain of our data center facilities, some of which have limited

operating history or may have less experience operating data center infrastructure at the scale and complexity

our operations require. In certain cases, these third-party operators are trained or supervised by our chip

partners to manage facilities on our behalf but are not affiliates of those partners and may not have the same

depth of expertise, operational resilience, or resources. Any failure by these third-party operators to perform as

expected could disrupt our access to compute. In addition, safety or environmental incidents at facilities built or

operated for us, whatever their cause, could expose us to claims, fines, or suspensions of construction or

operations, the costs of which we may bear. We also depend on an extended network of suppliers, builders, and

facility operators. If any of them engage in practices that are unsafe, unlawful, or contrary to the labor, human

rights, environmental, or other standards we or our partners require, we could face legal liability, lose the

ability to use affected suppliers or facilities, and suffer harm to our reputation, even where we did not direct or

know of the conduct.

Our collective data center infrastructure is currently concentrated primarily in the United States, which exposes

us to risks associated with regional regulatory changes, power grid constraints or failures, disruptions to

network connectivity between facilities, natural disasters, physical attacks—including those motivated by

geopolitical events, opposition to AI, and opposition to data center development—and other disruptions that

could affect multiple facilities. Certain state, local, and municipal jurisdictions in the United States are also

considering or have approved moratoriums on new data center construction, citing public health, safety, and

environmental concerns. Such jurisdictions and other regulators, grid operators, or utilities may also adopt

other measures that subject users of large electricity loads, including data centers, to curtailment, interruptions,

forced reductions, disconnection, or other restrictions during periods of grid stress, whether through changes in

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law or policy, market or reliability constraints, limits on transmission and distribution infrastructure, or a

preference for protecting other utility customers and the broader grid. New large loads on the electrical grid

may be increasingly subject to mandatory curtailment in regions where there is insufficient grid-connected

power generation to reliably supply existing and new electricity loads. For example, states such as New York

and Texas have recently moved to regulate large-scale data centers, whether by pausing state permitting for

new large facilities, as New York has, or by subjecting large electricity loads to curtailment or disconnection

during grid emergencies, as Texas has. Such moratoriums, or similar actions, could delay or prevent the

construction or expansion of facilities on which we depend for compute. Opposition to data center development

has also become more organized and coordinated across jurisdictions and our public profile may draw

particular attention to projects associated with us. The loss of, or a significant disruption at, any major facility

may not be readily absorbed by our remaining or future infrastructure. We are expanding our data center

capacity internationally as part of our efforts to diversify our infrastructure footprint and reduce concentration

risks associated with operating a significant portion of our compute infrastructure in the United States and to

support our international growth strategy, including by entering into letters of intent and negotiating lease and

related agreements for data center facilities in multiple non-U.S. jurisdictions, which exposes us to additional

risks related to foreign regulatory requirements and approvals, data sovereignty and localization laws,

governmental access or assistance requirements, cross-border data transfer restrictions, foreign tax regimes,

and increased operational complexity. Our ability to enter into definitive agreements for data center capacity

and operations in non-U.S. jurisdictions depends on the timely formation, registration, and receipt of

governmental approval of local subsidiaries, as well as the establishment of local banking arrangements, and

any delay or failure in completing these steps could delay or prevent us from mitigating our infrastructure

concentration risks, executing our international growth strategy, securing planned compute capacity, or could

result in substantial additional taxes, penalties, or other liabilities. In addition, regulatory, legal, and other

constraints in many jurisdictions may limit the locations in which we can practically site or contract for data

center capacity, which could constrain our ability to diversify our infrastructure footprint as quickly or as

broadly as we currently intend.

We and our principal competitors rely on substantially similar inputs to develop and deploy frontier models,

including advanced chips sourced from a small number of suppliers and data center capacity and compute

obtained from CSPs and other third parties. As we and our competitors increasingly pursue vertical integration,

the basis of competition could shift over time to encompass not only which company can develop the most

capable models, but also which company can develop the best underlying components. Our future

competitiveness may depend in part on our ability to successfully develop vertically integrated compute

infrastructure on competitive terms and timelines, and there can be no assurance that we will be able to do so.

Our competitors may be better positioned, or may invest greater efforts, to vertically integrate across the

compute supply chain, including through proprietary chip design, fabrication, ownership or long-term control

of data center infrastructure, access to dedicated power generation assets, exclusive supply arrangements with

hardware manufacturers, or by securing the limited sites suitable for large-scale data center development ahead

of us. Competitors that succeed in controlling a greater share of these supply chain layers may be able to secure

compute at greater scale, lower cost, or with greater reliability than we can, particularly during periods of high

demand or supply constraint, when captive supply relationships may confer certain advantages over

participants that depend on third-party providers. Such competitors may also develop proprietary hardware-

software co-designs that optimize compute efficiency for their specific model architectures, which could

compound any capability gap across successive model versions. While we are pursuing initiatives to develop

dedicated data center infrastructure, there can be no assurance that these efforts will be completed on the

timelines or at the costs we anticipate, or that they will be sufficient to offset any structural advantages that

vertically integrated competitors may achieve. Competitors that succeed in these efforts may be better

positioned to remain at the frontier of AI regardless of broader market constraints.

Natural hazards, extreme weather, or other disruptions affecting the regions where these inputs are produced

or where our facilities are located could further constrain the availability of chips, power, water, or data center

capacity on which we depend. If we are unable to manage the foregoing risks, our business, financial condition,

and results of operations could be adversely affected.

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We are highly dependent on the continued service of our co-founders, senior management

team, and key technical employees, and the loss of any of these individuals may adversely

affect our business, financial condition, and results of operations.

We are highly dependent on the continued service of our Chief Executive Officer, President, co-founders, senior

management team, and key technical team. In particular, our Chief Executive Officer and President are critical

to setting our strategic direction, advancing our research agenda, shaping our safety and governance

frameworks, and generally advancing our mission, and we believe that their leadership would be difficult to

replace. If either were to become unavailable for any reason, or if either of their reputations were significantly

harmed, regardless of merit, there could be an adverse impact on our operations and competitive position,

employee morale, employee retention, pace of innovation, customer and partner confidence in our company,

our brand and reputation, and our long-term strategic objectives. Further, the loss of key personnel, including

members of our founding team and senior management team, and key engineering, research, product

development, marketing, and sales personnel, could also disrupt our operations and have an adverse effect on

our business. Many of our key personnel, particularly within our technical and research teams, are strongly

motivated by our mission and the opportunity to work on addressing specific problems within the AI landscape.

To the extent that their interests evolve, they seek to pursue different technical challenges or areas of focus, or

they are drawn to other organizations or initiatives that they perceive as better aligned with their personal

beliefs or professional objectives, we may face increased difficulty retaining such personnel. This risk may be

heightened as we continue to scale and mature as an organization, which may change the nature of the work

environment, priorities, or perceived mission alignment for certain personnel, including personnel who may

conclude that the objectives that drew them to us have been substantially achieved. In addition, under certain of

our agreements with suppliers, the loss of certain key personnel could accelerate our obligations or otherwise

trigger adverse consequences under such agreements.

If we are unable to retain key personnel, or if we fail to conduct effective succession planning and find suitable

replacements for any losses of such key personnel in a timely manner and on competitive terms, we could

experience declines in sales, delays in research and development, and harm to our business and operations. If

we are unable to manage the foregoing risks, our business, financial condition, and results of operations could

be adversely affected.

We may require additional capital to meet our substantial ongoing obligations and support

our business growth, and our ability to generate sufficient revenue and secure additional

capital on acceptable terms is critical to our continued operations and competitive position.

Our business model requires substantial and increasing capital to support our ability to remain competitive and

to stay at the frontier of AI. We intend to continue to make significant financial investments to support our

business growth and may require additional funds to acquire sufficient compute and respond to business

challenges, including expenditures to create, maintain, upgrade, and enhance our models, platform, and

applications, including costs related to investments in infrastructure, human capital, office expansion, and data

assets. In addition, we may use a portion of our cash to satisfy tax withholding and remittance obligations

related to outstanding RSUs and equity awards that we grant in the future.

In addition, to date we have financed our compute primarily under arrangements with CSPs, with costs

recognized as compute is made available to us. We may in the future finance a greater portion of our compute

on an up-front basis, including through capital leases, prepayments, debt-financed purchases of equipment, or

similar arrangements. If we were to do so, we may incur significant cash outflows in advance of compute

availability or related revenue, which could increase demands on our cash flows and liquidity and our need to

raise additional capital. Such arrangements could also increase our capital intensity and alter our cash-flow

profile.

Accordingly, it is critical that we maintain strong revenue growth, grow revenue efficiently relative to our

committed compute, infrastructure, and personnel costs, and manage our cash flows effectively. To the extent

that such efforts are insufficient to meet our capital needs, we may need to obtain additional capital through

equity or debt financings. If we raise additional funds through future issuances of equity, equity-linked

securities, or convertible debt securities, our existing stockholders could suffer dilution, and any new securities

we issue could have rights, preferences, and privileges superior to those of holders of our common stock.

Further, the conversion of our outstanding convertible securities will cause additional dilution to our existing

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stockholders. Any debt financing that we may secure in the future may involve restrictive covenants relating to

our capital raising activities and other financial and operational matters, potentially making it more difficult for

us to obtain additional capital and to pursue business opportunities.

In addition, our ability to draw amounts under certain of our note purchase agreements (“NPAs”) is not

guaranteed and is subject to the satisfaction of specified conditions. In particular, our ability to access

additional amounts under certain of these facilities depends on our achievement of certain revenue

performance targets and/or the ability of third parties to deliver additional compute to us. While we have

historically surpassed all such revenue performance targets, there can be no assurance that revenue will

continue to exceed these thresholds at all times in the future. If these conditions are not satisfied, we may be

unable to draw additional amounts under the applicable NPA, which could adversely affect our cash flows and

liquidity. For more information about the terms of our convertible promissory notes, see the section titled

“Management’s Discussion and Analysis of Financial Condition and Results of Operations—Liquidity and

Capital Resources—Convertible Notes.”

We may not be able to obtain additional financing on terms favorable to us, if at all. We evaluate financing

opportunities from time to time, and our ability to obtain financing will depend, among other things, on our

development efforts, business plans, and operating performance and the condition of the capital markets at the

time we seek financing. The equity and debt markets may experience extreme volatility and disruption from

time to time, which could result in higher credit spreads in such markets and higher funding costs for us. If we

are unable to generate sufficient revenue growth or obtain adequate financing or financing on terms satisfactory

to us when we require it, our ability to continue to support our business growth, scale our infrastructure,

develop new models, platforms, and applications, enhance our existing models, platform, and applications, and

respond to business challenges may be impaired, and our business, financial condition, and results of

operations may be adversely affected.

Our company culture has contributed to our success and, if we cannot maintain this culture as

we grow, our business could be adversely affected.

We believe that our company culture is a critical component to our success. We are a mission-driven company

and our culture reflects a strong emphasis on the Company Purpose. Our ability to continue to cultivate and

maintain this culture is essential to our growth and continued success. We face a number of challenges

associated with our commitment to our company culture, including:

•the need to identify, attract, reward, and retain people in leadership positions in our organization who

share and further our culture, values, and mission;

•the increasing size and geographic diversity of our workforce, and our ability to promote a uniform and

consistent culture across all of our offices and employees;

•internal and external perceptions about our mission, values, commitment to safety, and uses of our

models, platform, and applications;

•engagement with government policymakers on issues that resonate differently across our workforce;

•competitive pressures to move in directions that may divert us from our mission and values;

•the rigorous, values-driven standards we apply in hiring and decision-making, which may slow the

pace at which we can scale our workforce or expand our operations relative to competitors;

•the continued challenges of a rapidly evolving industry;

•the increased scrutiny and expectations associated with operating as a public company; and

•the need to balance our long-term, mission-driven objectives with shorter-term financial performance

expectations, which may create internal tension and challenge our ability to consistently reinforce our

cultural values and mission across teams and leadership.

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Our mission-driven culture is one of our core characteristics that helps us to attract and retain key personnel

and differentiate us in the market. If we are unable to maintain our culture, as well as balance our commitment

to maintaining our culture with the demands of rapid growth, competition, and operating as a public company,

our employee morale, engagement, and retention could suffer, requiring us to incur additional costs or adopt

alternative recruiting strategies, which could adversely affect our business, financial condition, and results of

operations.

We face intense competition, and if we are unable to compete effectively, our business,

financial condition, and results of operations could be adversely affected.

The market for AI models, platforms, and applications is rapidly evolving, intensely competitive, and subject to

frequent and significant changes in technology, evolving customer requirements and expectations, shifting

industry standards, regulatory developments, new market entrants, and new models, platforms, and

applications. We face competition from a wide range of companies across multiple categories.

We compete directly with companies developing frontier models for third-party software developers and

enterprises. Our primary competitors in this category include Alphabet Inc. (together with its affiliates,

“Google”) and OpenAI Group PBC (“OpenAI”). These competitors are developing increasingly capable AI

systems and compete with us for customers, talent, compute, and strategic partnerships. Many have

substantially greater financial, technical, and marketing resources than we do, their own or greater access to

sources of compute, longer operating histories, greater brand recognition, and established relationships with

current and potential customers and partners, which facilitates their ability to integrate their models into first-

party applications sold directly to businesses.

We also compete with a broader set of model providers operating at or below the frontier, including large

companies, specialized AI labs, and a growing range of other open-weight or open-source (shared weights,

training data, and code) models released by international and domestic organizations. Such providers compete

for a growing range of enterprise workloads that prioritize cost efficiency over intelligence. In particular, certain

large companies compete through proprietary AI models, integrated AI capabilities in existing products, and

control of cloud infrastructure and distribution channels. Some of these companies also have substantially

greater financial, technical, and marketing resources than we do, their own or greater access to sources of

compute, longer operating histories, greater brand recognition, and established relationships with current and

potential customers and partners. In addition, some have substantially broader and more diverse product and

service offerings and may be able to leverage existing relationships with distribution partners and customers to

gain business in ways that discourage customers from purchasing our models, platform, and applications. For

example, competitors may bundle AI capabilities with other products, integrate AI functionality into products

that customers already use, offer closed technology platforms that lock customers into their ecosystems, sell

products at zero or negative margins to gain market share, or use their substantial financial resources to

subsidize the cost of AI models, platforms, and applications. Customers may prefer to purchase from existing

vendors with which they have established relationships, even if our models, platform, and applications offer

superior features or performance. Further, large companies that are currently our customers may choose to

develop their own AI capabilities internally rather than purchase our models, platform, and applications.

Specialized AI labs, on the other hand, are competitive due to their ability to offer specific AI applications and

differentiated business models. These companies can move quickly, attract top talent, develop novel

approaches, platforms, or business models that disrupt existing competitive dynamics, and introduce

technologies or products with greater performance or functionality, lower cost, ease of implementation, or other

advantages. Some competitors or customers may have access to proprietary datasets, distribution channels, or

domain-specific expertise that we do not possess, or new competitors may emerge that address particular

industries or use cases more effectively than our models, platform, and applications, which could enable them

to develop more specialized or higher-performing AI systems. In addition, competitors, customers, or other

third parties have attempted in the past and will likely continue to attempt to replicate, distill, extract, or

otherwise derive the functionality or capabilities of our models through permitted or impermissible means,

including through our research previews. These actions could reduce the technological differentiation of our

offerings; enable the development of competing products at lower cost, with reduced research and development

investment, or that replicate our models without safety controls or safeguards that were incorporated in our

versions; implicate national security concerns or strain geopolitical tensions; and intensify competitive

pressures. In addition, efforts to prevent or mitigate model replication, distillation, or other forms of extraction

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may require us to modify our models, platform, and applications, limit features or use cases, or implement

technical safeguards that could reduce the usability or attractiveness of our offerings, slow adoption, and

adversely affect customer demand and revenue. More broadly, as AI models are increasingly used to develop

other AI models, the knowledge and techniques required to build frontier models may become more widely

available over time, including through distillation, unauthorized access to or theft of model weights, or the

diffusion of AI-assisted research and development capabilities across the industry. If the ability to develop

highly capable models becomes more broadly available, our technological differentiation could erode and

competition could increasingly depend on access to large-scale compute rather than on model development

capability. In such an environment, access to sufficient compute on economical terms could become the

primary constraint on our ability to train and serve competitive models, and our business, competitive position,

and results of operations could be adversely affected if we are unable to secure compute at the scale, cost, or on

the timeline we require.

Additionally, open-weight or open-source AI models may capture a portion of the market for certain use cases,

which could exert pricing pressure on our offerings or lead certain customers to adopt open-source alternatives

for those use cases.

A significant portion of our customer base consists of startups and technology-oriented enterprises that may be

more sensitive to adverse macroeconomic conditions and may reduce or delay spending during a downturn.

Because our cost structure limits our ability to rapidly adjust spending, a sustained economic downturn could

disproportionately disadvantage us relative to larger, better-capitalized competitors. Such competitors may be

better positioned to absorb or withstand adverse economic conditions or reductions in customer technology

spending due to their greater financial resources, diversified product offerings and customer bases, and more

stable revenue streams. It could also disadvantage us relative to smaller startups with leaner cost structures,

lower fixed overhead, and fewer long-term contractual commitments that could help enable them to adjust

spending more rapidly than we can. As a result, competitive pressures on our business could intensify, which

could adversely affect our business, financial condition, and results of operations.

If we are unable to differentiate our models, platform, and applications from competing offerings through

enhanced functionality, superior performance, better safety features and reliability, lower cost, or other factors,

demand for our models, platform, and applications may decline. The rapid pace of technological change in AI

means that models, platforms, and applications can quickly become outdated. We must continuously invest in

research and development to maintain our competitive position, but there is no guarantee that our investments

will result in models, platforms, and applications that customers prefer over competing alternatives. Moreover,

we are first and foremost a research lab, and our strategy prioritizes frontier research and model capability. We

believe the advancing intelligence and capabilities of our models are the principal drivers of their adoption, and

we have historically prioritized research and model development rather than new products and applications or

sales and marketing. This approach assumes that model capability will continue to be a meaningful source of

competitive differentiation. However, as the AI industry matures, the degree of differentiation among advanced

AI models may narrow. This convergence may result from factors such as overlapping or similarly sourced

training data, the widespread adoption of comparable model architectures, training techniques, and

optimization methods, shared access to computing infrastructure, and the rapid dissemination of research

advances across the industry. To the extent competitors are able to achieve comparable model capabilities with

lower development or deployment costs, our ability to differentiate our models, platform, and applications on

the basis of performance, functionality, or cost may be diminished. If differentiation among advanced models

narrows, or if customers increasingly select AI providers on the basis of application features, user experience,

distribution, integration into products they already use, or the strength of a sales organization rather than

model capability, competitors that have invested more heavily than we have in those areas could be better

positioned than we are. Responding to such a shift could require us to increase our investment in product

development and sales and marketing substantially beyond our current plans, which could take longer or cost

more than we anticipate and could reduce the compute and other resources available for frontier research, and

we may not be able to execute such a shift quickly or effectively. See also the section titled “—We have a limited

history under our current go-to-market strategy, and our efforts to scale and evolve our customer acquisition,

engagement, and retention model may not be successful.”

If we are unable to compete successfully, our business, financial condition, and results of operations could be

adversely affected.

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If we fail to attract new customers, retain existing customers, or expand usage of our models,

platform, and applications, our business, financial condition, and results of operations could

be adversely affected.

Our future growth depends on our ability to attract new customers, retain existing customers, and expand sales

within our existing customer base. We face significant challenges in each of these areas, and failure to execute

on our customer acquisition and retention strategies could adversely affect our business, financial condition,

and results of operations.

We must continue to attract new customers in a cost-effective manner. Potential customers may not understand

the benefits of our models, platform, and applications or may be unable to justify the investment in our models,

platform, and applications, particularly as existing competitors continue to enhance their offerings, improve

performance, expand functionality, or reduce costs. Our ability to demonstrate differentiated value to potential

customers may become more difficult as this competition intensifies, or as large technology companies bundle

AI capabilities into existing products. If we continue to focus on enterprise customers, we may face longer sales

cycles that demand significant upfront investment in enterprise sales teams and customer service. These sales

efforts are costly and may not result in customer conversion.

Even if we successfully attract new customers, we face significant challenges in retaining them. Many of our

customer contracts allow customers to reduce usage or terminate with limited or no notice. Customers are not

obligated to renew their subscriptions or contracts with us. Customer retention and usage levels may decline

due to a number of factors, including:

•dissatisfaction with the performance, reliability, safety, or accuracy of our AI models;

•availability of competitive alternatives;

•customers developing their own AI capabilities internally;

•our models, platform, and applications reducing demand for our customers’ offerings or causing

disruptions to their businesses, which could lead to reduced usage or customer attrition;

•changes in customer budgets or strategic priorities regarding AI investment;

•concerns about data privacy, security, or our data handling practices;

•negative publicity regarding AI generally or our business specifically;

•changes in the regulatory and legal landscape surrounding AI and our models, platform, and

applications in particular;

•pricing changes or perception that our pricing is not competitive; and

•general economic conditions or industry-specific downturns affecting our customers.

Our ability to retain customers and drive expansion also depends on our continued investment in product

development. The process of developing products and incorporating new technologies is complex and

uncertain, and if we fail to accurately predict customers’ changing needs and emerging technological trends and

opportunities, we may not be able to compete effectively and our business and ability to generate revenue could

be adversely affected. As AI technology evolves rapidly, customers may perceive our models, platform, and

applications as becoming outdated or may expect continuous improvements to model performance and

capabilities. Even minor degradations in model performance or increases in response latency could cause

customers to reduce usage or switch to competitors. If we are unable to retain existing customers or if our

customers do not maintain their usage levels, our revenue and growth could be adversely affected. For

additional discussion on product development, see the section titled “—Our success depends in large part on

our ability to continue to develop the most advanced and capable AI models, and any failure to do so could

adversely affect our business.”

Some of our enterprise customers may have the financial resources, technical capabilities, and access to the

talent and compute necessary to develop and deploy proprietary AI models, and may reduce or cease usage of

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our models, platform, and applications as their internal AI capabilities mature, even where they initially

adopted our offerings as a foundation for their AI strategy. If these customers were to reduce or cease usage of

our models, platform, and applications, our revenue and growth could be adversely affected.

In addition to retaining customers, our growth strategy depends in part on expanding usage within our existing

customer base by increasing usage volumes, selling additional capabilities, and expanding adoption across

departments and use cases within customer organizations. However, customers may not expand their usage for

a variety of reasons, including satisfaction with current usage levels, budget constraints, technical challenges in

integrating our models, platform, and applications more broadly within their organizations, or preference for

multi-vendor AI strategies in order to limit dependence on any single provider. Due to our consumption-based

pricing model, customers may reduce or cease usage at any point within a given period due to budget or

internal procurement constraints, organizational spending controls, or other factors unrelated to the quality or

performance of our models, platform, and applications, and may not resume usage until a new budget period

commences or additional spend is approved, even where demand for our models, platform, and applications

remains strong. As a result, our revenue could be lower or more variable than anticipated and this effect may be

particularly pronounced among customers experiencing rapid growth in their usage of AI. If we increase sales

and marketing expenditures to accelerate customer acquisition without achieving proportional revenue growth

and if we cannot attract new customers, retain existing customers, expand within our customer base, or

accomplish these objectives in a cost-effective manner or timely manner, our revenue growth will decline and

our business, financial condition, and results of operations will be adversely affected.

If the market for our models, platform, and applications develops more slowly than we expect

or declines, our growth may slow or stall, and our business, financial condition, and results of

operations could be adversely affected.

The market for AI technologies, including frontier AI and related models, platforms, and applications, has

grown rapidly in recent years, but is still relatively nascent and evolving rapidly, and it is uncertain whether the

market for such AI technologies will achieve or sustain widespread adoption at the pace or to the extent we

expect. Our ability to generate revenue and achieve sustainable growth depends in significant part on the extent

to which enterprises, software developers, and other users adopt AI technologies, integrate them into existing

workflows, expand usage over time, and are willing to pay for our models, platform, and applications at levels

that support durable economic value at scale. Market adoption may be slower than anticipated due to factors

such as uncertainty regarding the cost, performance, reliability, and perceived value of AI solutions; increased

regulation; concerns about security, privacy, legal and regulatory compliance, or ethical considerations;

technological challenges; level of effort and expense associated with integration efforts; competition from

alternative or emerging technologies; the availability or adoption of complementary infrastructure and

workflows; or reductions in corporate spending due to macroeconomic conditions. Moreover, demand for

frontier models may decline if customers determine that less advanced, lower-cost models are sufficient for

their particular use cases. As AI capabilities improve across the industry and a broader range of models

becomes available, customers may conclude that incremental performance gains at the frontier do not justify

the additional cost, and may migrate toward smaller, cheaper, or open-source alternatives that adequately

address their needs. If we are unable to demonstrate sufficient differentiated value from our frontier models

relative to less capable alternatives, our revenue and growth could be adversely affected, even in a market where

overall AI adoption continues to grow. Further, while AI adoption may continue or accelerate in certain areas,

the long-term trajectory of this technological trend is uncertain, and market understanding, acceptance, and

valuation of AI-enabled models, platforms, and applications may be inaccurate or change over time and

adoption may occur unevenly across industries, geographies, and customer types. If growth in the AI market

does not translate into sustained customer demand for our offerings, expanded usage, and increased revenue,

or if anticipated use cases fail to materialize, our prospects, business, financial condition, and results of

operations could be adversely affected.

The political environment and our engagement with policymakers and public positions on AI

regulation and safety could subject us to heightened scrutiny, political backlash, or

disproportionate regulatory action.

Our commitment to responsible and safe AI development includes active engagement with policymakers,

regulators, and other stakeholders regarding the development of AI-related laws, regulations, and standards.

We have participated in, and will likely continue to participate in, political processes, including through

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contributions, advocacy, or support of political organizations. In addition, our executives and other

representatives have publicly expressed and may in the future publicly express views on AI policy, regulation,

safety, and related social or political issues. As a result, we have experienced, and may continue to experience,

increased visibility and may continue to be subject to heightened scrutiny or the risk of being disproportionately

or selectively targeted by particular governmental bodies, even where similarly situated companies are not,

including through investigations or enforcement actions, the imposition or selective application of regulatory,

licensing, or permitting requirements, adverse treatment in government procurement or provision of security

clearances, or targeted immigration or visa actions affecting our personnel. As part of our political engagement,

we have advocated for, and will likely continue to advocate for, regulatory approaches or industry standards

that we believe promote the safe and responsible development of AI but that could increase our compliance

burdens, limit our product development or deployment flexibility, or otherwise slow our growth relative to

competitors.

Our public positions, stated values, policy advocacy, or statements by our executives have attracted, and may

continue to attract, criticism from influential political figures, industry participants, regulators, or other third

parties, particularly in politically sensitive or polarized environments, which could shape public narratives or

regulatory perceptions of our business in ways that are unfavorable to us. For example, public statements by us

or other industry participants regarding the safety of frontier AI development have been cited by governmental

actors to support litigation or regulatory claims, including requests for injunctive relief restricting model

development, and could be cited in future proceedings involving us. Such scrutiny or backlash could result in

reputational harm, increased compliance or operating costs, investigations, enforcement actions, or restrictions

on our operations, any of which could adversely affect our business, financial condition, and results of

operations.

If the use of our AI models results in harm, whether through use by malicious actors or misuse

by other third parties, or if our model guardrails or safeguards fail to prevent such misuse,

our reputation and brand, business, financial condition, and results of operations could be

adversely affected.

While our AI models are designed to comply with our AI safety and usage guidelines and be broadly safe,

ethical, and helpful, and while we have implemented safety measures intended to anticipate, identify, and

mitigate potential harmful uses, such measures are incomplete, may be outdated in light of evolving threat

models, or may fail to identify or prevent all potential misuse of our models, and our models have been, and

may continue to be, misused or manipulated to produce harmful outputs or carry out harmful actions.

Malicious actors have used, and may continue to develop novel or more sophisticated methods to use, our

models in ways that violate our usage policy or seek to circumvent our model guardrails or safeguards through

techniques such as prompt injection, adversarial inputs, or other methods, and use our models to engage in

harmful activities, including developing weapons, generating fraudulent or misleading content, conducting

cyberattacks, perpetrating acts of violence, or to engage in activities that would otherwise be prohibited under

our usage policy or in violation of applicable law. Our customer onboarding diligence varies by access channel,

and we do not and in certain situations cannot uniformly verify the identity of those who access our models or

of our customers’ end users, which may limit our ability to prevent access or recidivism by malicious actors or

to enforce our usage policy or other policies.

Moreover, our safety and security controls, including automated classifiers and monitoring systems, depend on

complex internal configurations that have failed, been misconfigured, or been inadvertently disabled, and may

do so again in the future without our timely detection. Any undetected failure of our safety controls could

permit misuse that our safeguards are designed to prevent, and could result in real world harm, legal liability,

regulatory or enforcement action, loss of customer trust, and reputational harm, any of which could adversely

affect our business, financial condition, and results of operations.

In particular, our most capable models have demonstrated, and future models are expected to demonstrate,

capabilities that could provide meaningful assistance to malicious actors seeking to develop chemical,

biological, or other dangerous weapons. We deploy technical safeguards, including automated classifiers,

specifically intended to detect and block these categories of misuse, but such safeguards are incomplete, may be

outdated in light of evolving threat models, have been and may in the future again be circumvented, or may fail

to operate as intended. Any actual or perceived use of our models to contribute to the development of such

weapons could result in harm, legal liability, regulatory or enforcement action, loss of government and

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enterprise relationships, and damage to our reputation and brand, any of which could adversely affect our

business, financial condition, and results of operations.

For example, in September 2025, we detected and assessed with high confidence that a Chinese state-sponsored

hacking group manipulated our Claude Code tool into attempting infiltration into roughly 30 global targets,

including large technology companies, financial institutions, chemical manufacturing companies, and

government agencies, resulting in a limited number of successful intrusions. We believe this is the first

documented case of a large-scale cyberattack executed without substantial human intervention. We expect that

malicious actors, including sophisticated state-sponsored actors, will continue to seek to leverage our models,

platform, and applications for harmful actions, including by circumventing our safeguards, and their efforts to

do so may increase as the capabilities of our technology increase. Any successful attempt to misuse, or any

perceived misuse of, our models, platform, and applications for a cyberattack or for any other malicious

purpose could result in exposure to liability, disruption of our customer or other commercial relationships, or

damage to our reputation. The risks of such harms may increase as the cybersecurity-related capabilities of our

models, platform, and applications increase. Independent security researchers and other third parties have also

used, and may in the future use, our models to identify and exploit vulnerabilities in the systems of other

companies, including other AI developers, at times in connection with authorized bug bounty programs. While

such activity may be lawful and consistent with industry practice for vulnerability research, it illustrates that

our models can function as a general-purpose tool for gaining unauthorized access to third-party systems, and

comparable capabilities could be used by malicious actors without authorization. Such incidents, whether or

not we are a direct party to them, may draw public and regulatory attention to the offensive cybersecurity

capabilities of our models and could result in reputational harm, calls for additional restrictions on our models,

or claims that we failed to adequately safeguard against such uses. For more information about risks related to

security incidents, see the section titled “—Any security breaches or other incidents, including those that affect

our networks, systems, or data, or the networks, systems, or data of our service providers, suppliers, or

customers, could adversely affect our business, financial condition, and results of operations.”

As part of our commitment to responsible security research and transparency, we disclose information about

the capability and safety of our models, the safeguards that we have adopted with respect to our models, and

instances of misuse of our technology, such as the September 2025 cyberattack described above. We also

publish model system cards, our research findings, and other safety-related information. We take steps to

ensure that such disclosures will not materially assist malicious activity and weigh the benefits and risks of such

disclosures from an ecosystem preparedness perspective; however, malicious actors, including sophisticated

state-sponsored adversaries, have in the past and may in the future use those disclosures to assist their

attempts to circumvent our safeguards and security measures, thereby increasing the risks of misuse of our

models, platform, and applications, as well as the potential for exposure to liability, regulatory or litigation

proceedings, or other harms. In addition, because these disclosures describe risks and observed model

behaviors in detail, they may draw heightened public, media, or regulatory attention and could be cited by

regulators, litigants, or others in proceedings or claims against us. The steps we take to prevent misuse of our

models, platform, and applications could be incomplete or may fail to operate as intended, and any actual or

perceived misuse could adversely affect our business, financial condition, and results of operations.

Our AI models may behave in unintended, misaligned, or autonomous ways, including by

taking harmful actions that no user or third party directed, which could adversely affect our

reputation and brand, business, financial condition, and results of operations.

Our AI models may themselves cause harm by producing undesirable outputs or behaving in unintended,

misaligned, or autonomous ways, including by taking unintended or harmful actions that no user or third party

directed. These risks may increase as our models become more capable and are granted greater autonomy,

permissions, and integration with external systems. Although we continue to study why these behaviors

emerge, our understanding continues to evolve, and we may be unable to anticipate or understand such

behaviors in the future.

In addition, our models have been and may continue to be deployed in high-risk or sensitive contexts, such as

healthcare, scientific and biomedical research, drug discovery and development, legal, finance, government, or

other critical decision-making environments, and in connection with hardware, where undesirable model

behaviors—which are inherently non-deterministic and may manifest in unpredictable ways, such as errors,

inaccuracies, biased or unsolicited views or hallucinations—could lead to serious harm, liability, or reputational

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or other damage. More broadly, the long-term effects of regular AI interaction on mental health, cognitive

development, and social behavior are not yet fully understood, and if such long-term harms do materialize in

the future, we could face significant liability, reputational harm, and adverse effects on our business, financial

condition, and results of operations.

Our development of more advanced AI models and our expansion into new jurisdictions could amplify the

foregoing risks. As our AI models become more advanced and capable, we have faced and may continue to face

heightened alignment, interpretability, controllability, and safety challenges, as more sophisticated models may

be better able to circumvent safeguards or behave in unintended ways. We may be unable to fully understand or

explain why our models produce particular outputs or behave in particular ways, which could limit our ability to

predict or prevent failures, provide explanations to customers or regulators, or satisfy emerging regulatory,

transparency, and explainability requirements.

In addition, our safety evaluations and testing processes have produced and may in the future produce

incomplete or unreliable results. For example, we have observed models behaving differently when they detect

or infer that they are being evaluated, which can limit our ability to accurately assess real-world risks or failure

modes prior to deployment. Such model awareness of our evaluation efforts creates a significant limitation on

our ability to assess model safety.

Furthermore, AI models have developed, and may in the future develop, unexpected capabilities during training

that were not anticipated, intended, or tested for, and such emergent capabilities may not be discovered until

after a model has been deployed, potentially resulting in safety incidents, reputational harm, regulatory

scrutiny, or the need to withdraw, retrain, or modify deployed models at significant expense. Such models may

also be deployed in higher-stakes or more sensitive applications, increasing the potential impact of errors,

misuse, or misalignment.

In addition, advanced AI models, including our models, give rise to novel ethical and safety risks, including

risks related to autonomy, manipulation, and the simulation of aspects of human psychology. These risks could

result in unforeseen harms and may require the development of governance structures, safeguards, or

mitigation strategies beyond existing AI safety frameworks, and there is always a risk that we will be unable to

develop or implement them effectively. In addition, models, including our own, have exhibited, and may in the

future exhibit, unexpected strategic or self-preserving behaviors, including attempts to resist shutdown, conceal

or manipulate information, or generate outputs that could be interpreted as coercive, deceptive, or

manipulative, including behavior resembling blackmail or efforts to influence human decision-makers to

preserve the model’s continued operation or access.

Even isolated or simulated instances of such behavior, whether occurring in testing or real-world deployments,

and whether occurring with our models or models developed by others, could generate significant public

concern, regulatory scrutiny, litigation risk, or reputational harm, regardless of whether such behavior results

in actual harm. For example, state attorneys general in California and at least 15 other states have announced

investigations of another company in our industry regarding AI safety. Concerns have been raised both within

our organization and by other researchers, regulators, policymakers, and industry participants that sufficiently

advanced AI systems could, if not developed, deployed, and operated with appropriate safeguards, oversight,

and security measures, pose catastrophic or existential risks to humanity, particularly if such systems were

misused, replicated, weaponized, or allowed to operate with a high degree of autonomy. We have observed that

our models are contributing to the pace of our own research and these risks will increase as AI systems

substantially automate AI research and development if, for example, they accelerate AI progress beyond our

ability to evaluate and safeguard new models, which could adversely affect our business, financial condition,

and results of operations.

Our development of highly advanced models, platforms, and applications and expansion of use cases could

further increase the risk that our models cause harm. For example, agentic AI systems are capable of

autonomously taking actions on behalf of users, interacting directly with external systems, executing code,

making API calls, sending communications, or completing transactions with limited human oversight. These

systems are designed to possess enterprise-level permissions, integrations, and contextual awareness and to

operate autonomously for extended durations, including sustained multi-step workflows lasting hours or days,

which amplifies the potential severity of any errors, misalignments, or security incidents that may occur during

such extended autonomous operation. These autonomous capabilities could increase the potential for harm, as

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errors, misalignment, or security exploits may result in real-world consequences—including consequences that

may be difficult or impossible to reverse, such as committing code changes, deleting or modifying data, or

completing financial transactions—before effective intervention is possible.

In an agentic workflow, an error or unintended action at any individual step may propagate through subsequent

steps, compounding the severity of harm before detection or correction. The pace and volume of autonomous

execution, particularly in enterprise deployments, may also exceed the capacity of human reviewers to

meaningfully understand and evaluate whether each action is appropriate. The effectiveness of human

oversight over our agentic offerings may be limited by the speed and volume of autonomous agent actions, the

complexity of multi-agent and multi-step workflows that may make it difficult for reviewers to assess whether

an agent’s actions are appropriate, and organizational pressures within customer environments to maximize

agent autonomy in order to achieve productivity gains. Human reviewers may experience alert fatigue, may lack

sufficient context to evaluate agent decisions, or may not review agent actions in time to prevent harm,

particularly in high-volume enterprise deployments where agents operate concurrently across multiple

workflows or in manners outside of a human’s awareness. In addition, agentic systems may pursue stated

objectives in ways that are technically consistent with their instructions but contrary to the user’s actual intent.

Moreover, our ability to anticipate, detect, or test vulnerabilities or other design or implementation

shortcomings in such systems may be constrained, particularly where agents operate across complex, multi-

step workflows or interact with third-party services outside our control, and the breadth and complexity of

potential interactions across such multi-step agent behaviors cannot be exhaustively tested prior to

deployment. Separately, models may behave in a misaligned manner and take harmful actions that are not

directed by a user or third party, pursuing objectives or acting on dispositions that diverge from those intended

by human users or developers. Misaligned behaviors of this kind, whether occurring in testing or real-world

deployments, have been observed both in our models and elsewhere in the industry, including in testing and

internal use, models circumventing network and sandbox restrictions, granting themselves permissions they

had not been given, taking unintended actions in pursuit of assigned goals, interfering with other AI agents, and

misrepresenting whether tasks had been completed or verified, and as models are granted greater autonomy,

permissions, and integration with external systems, the consequences of such misaligned behavior increase. For

example, during cybersecurity evaluations built by a third-party evaluation partner, a misconfiguration in the

testing environment left the model under evaluation connected to the open internet despite instructions that it

had no internet access. Four of our models gained unauthorized access to real third-party systems during

sessions lasting roughly 10 to 34 hours of active work. In one incident, after being unable to abort an impossible

task, an early version of a model used a password it found to gain administrator access to a third party’s system,

harvested additional credentials, changed system settings, and read one individual’s personal information. The

affected parties were notified. Each incident involved a single instance of a model working in isolation on its

assigned exercise, and our investigation found no evidence that any model coordinated with other agents,

pursued goals beyond its assigned task, or attempted to evade oversight. These risks may be heightened where

multiple AI agents operate together. Agents that interact or coordinate with one another may amplify,

propagate, or reinforce misaligned behavior across the group, pursue objectives collectively in ways not

intended or endorsed by any user, or take coordinated actions against systems or targets unrelated to their

assigned tasks, in each case, in ways that may be difficult to anticipate, detect, or contain. Incidents of this kind

have occurred, and we expect the deployment and interaction of larger numbers of autonomous agents to

increase these risks over time.

Our ability to detect and mitigate misaligned or unintended behavior depends in part on the effectiveness of our

alignment evaluations, monitoring, and other oversight and control techniques, many of which rely on our

models having a limited ability to evade or subvert such oversight. As our models become more capable, they

have become better able to circumvent such techniques, including by concealing misaligned objectives or

behaviors, and the effectiveness of our evaluation, monitoring, and control measures, and our ability to

measure the degree to which our models are aligned, may decline as a result. In addition, models, including our

own, have attempted, in incidents observed in our industry, to interfere with, manipulate, or subvert the

mechanisms used to evaluate, grade, or oversee such models, including the systems responsible for assessing

their performance or alignment. Models used, including our own, to assess the behavior of other models have,

and may in the future continue to, engage in misaligned behavior. Such conduct described above could cause

our evaluations to overstate the safety or alignment of our models and could further limit our ability to detect

misalignment. If we become less able to detect or assess misalignment as our models advance, we may deploy

models whose behavior we cannot adequately verify, which could increase the risk of undetected harmful

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conduct and misalignment, which could adversely affect our business, financial condition, and results of

operations.

We are also extending our models, platform, and applications into scientific, biomedical, and physical domains.

For example, we offer Claude Science, an agentic research environment that connects our models to scientific

databases, third-party and open-source scientific models, and customers’ own computing infrastructure, and

we have released, initially as a limited research preview, an open protocol that enables our models to monitor

and control laboratory instruments, robotic systems, and other physical hardware. We also conduct research on

the ability of our models to operate robotic systems. When our models direct physical equipment, errors,

misaligned behavior, adversarial manipulation, or misuse could result in bodily injury, property damage,

damage to costly equipment or experimental materials, or the release of hazardous substances, and such

consequences may be immediate and irreversible. Safety interlocks, human-in-the-loop controls, and access

restrictions we implement may prove inadequate, and because certain of these components are open source,

third parties may deploy them with hardware, or in configurations, that we have not evaluated or from which

our safeguards have been removed. Connecting increasingly capable models to laboratory automation may also

heighten governmental and public concern regarding the potential for AI systems to accelerate the development

of dangerous biological, chemical, or other materials, which could result in additional regulatory restrictions on,

or scrutiny of, these offerings.

In addition, maintaining comprehensive records of the actions, decisions, and reasoning of our agentic systems

across complex, multi-step workflows is technically challenging, particularly when agents interact with third-

party systems outside our control, and any inability to provide adequate audit trails could impair our ability to

investigate incidents, respond to regulatory inquiries, or defend against liability claims. These risks are

heightened by the fact that we use our own agentic offerings, including Claude Code, as critical tools in our

internal development processes, such that any errors, vulnerabilities, or degradation in these products could

directly impair our ability to develop and deploy future models and products. As we increasingly leverage

Claude to accelerate progress within Anthropic, our organization may lose visibility across certain processes in a

way that may become difficult for any individual or group of humans to understand and control. Because our

models write a large and growing share of our code and increasingly perform our research, including our safety

research, misaligned behavior in internal use could undermine that work, introduce vulnerabilities into our

systems or into the training of future models, or result in models operating outside of our intended controls.

Our monitoring does not cover all of our internal and external deployments and may not detect subtle or diffuse

forms of such behavior.

Any of the foregoing model behaviors, whether in testing or in real-world deployments and whether involving

our models or those of others, could result in safety incidents, reputational harm, increased regulatory scrutiny,

or liability, any of which could adversely affect our business, financial condition, and results of operations.

Furthermore, while we continue to design and develop more sophisticated techniques to evaluate the safety and

alignment of our models, the capabilities of our models could advance at a rate that initiates the

implementation of enhanced safety and testing measures as we have described in our Responsible Scaling

Policy. If our evaluations, monitoring, or reviews indicate risks that we believe warrant further testing, we have

in the past, and may in the future, delay, restrict, or decline to proceed with the release of a model. For example,

following incidents in 2026 in which our models gained unauthorized access to real computer systems during

pre-release cybersecurity evaluations, we suspended certain of those evaluations, as well as higher-risk

reinforcement learning environments. For more information about our approach to model releases, please see

the section titled “Business—Safety Research is Core to Our Business—Our Approach to Model Releases.” Any

decision to delay or restrict a release could adversely affect our competitive position and customer

relationships, and adversely affect our business, financial condition, and results of operations.

We may be exposed to liability, litigation, and regulatory action arising from harms

associated with our AI models, and our contractual protections and insurance may be

insufficient, any of which could adversely affect our business, financial condition, and results

of operations.

Harms associated with our AI models, whether arising from misuse by third parties, from our models’ own

behavior, or from their deployment in high-risk or sensitive contexts, may expose us to liability, litigation, and

regulatory action, including under theories that remain unsettled as applied to AI, and our contractual and

insurance protections may prove insufficient.

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Individuals at risk of suicide or self-harm or who have committed acts of violence toward others have used, and

may also in the future use, our models, notwithstanding our safeguards. AI models developed by others in our

industry have been and may in the future be alleged to have played a role in instances of suicide, acts of violence

toward others, or serious self-harm, which have resulted and may in the future result in significant public

scrutiny, litigation, criminal investigations, regulatory attention, and reputational harm.

Similar incidents involving our models have presented and could in the future present substantial risk to our

reputation, expose us to legal, regulatory, and other proceedings, and adversely affect our business, financial

condition, and results of operations. While our current Consumer Terms of Service requires our users to be at

least 18 years of age, minors have accessed in the past, and may in the future access, the platform, and risks

relating to child safety may be particularly acute, as minors may be more susceptible to harmful content,

manipulation, or overreliance on AI outputs, and incidents involving children tend to draw heightened

regulatory, media, and public scrutiny.

State attorneys general and private plaintiffs have also begun to assert tort, product liability, consumer

protection, and failure-to-warn claims against companies in our industry, alleging that AI models caused or

contributed to harm and that the developer failed to adequately warn users of known risks. In at least one case,

a state attorney general has initiated a criminal investigation against another company offering similar services.

Regulators have obtained substantial monetary settlements and injunctive relief against other technology

companies based on analogous theories of product-design or algorithmic harm, and we believe similar theories

are likely to continue to be tested against us and other companies in our industry as adoption of our models

grows, including by minors and other vulnerable users, notwithstanding our efforts to restrict such access. The

relief sought in such matters has, in at least one instance, extended beyond data-handling, disclosure, or age-

verification practices to include a request to enjoin an AI company from developing new models absent

independent, third-party safety review and approval, illustrating the potential breadth of remedies

governmental actors may pursue against companies in our industry. Any determination that we are liable under

such theories, or any judicial or regulatory expansion of tort, product liability, or consumer protection law, or

criminal liability, as applied to AI models, could result in significant liability and require us to change how we

design and offer our models, platform, and applications.

A substantial portion of our traffic is subject to Zero Data Retention (“ZDR”) terms under which we retain only

classifier scores, not prompts or outputs. For that traffic, we cannot conduct offline analysis, cross-conversation

investigation, human review, or otherwise analyze historical data to detect, investigate, and document security

events or incidents, which thereby reduces our ability to detect misuse. ZDR may also prevent us from

producing records for subpoenas, regulatory examinations, or incident-reporting obligations, and there is no

certainty a regulator or court would excuse non-production based on a lack of available records, and such

regulators or courts may construe the lack of records against us through unfavorable inferences or other

sanctions. As our models become more capable, our safety framework has required and may continue to require

monitoring and retention incompatible with ZDR for certain model classes. Because ZDR is a competitive

expectation for enterprise customers in regulated industries and on third-party cloud platforms, these

requirements have caused and could continue to cause customers to migrate to other providers or to

deployments where our visibility is more limited.

In the European Union (“EU”), the United Kingdom (“UK”), and elsewhere, cybersecurity and AI-related

incidents are subject to increasingly stringent reporting obligations. European regulators expect companies to

provide detailed information about incidents under several laws and regulations, which we may not be able to

provide within the prescribed time frame. Similarly, in the United States, companies are increasingly subject to

incident reporting obligations. In addition, other jurisdictions around the world have adopted, or may adopt,

similar laws and regulations with similar implications. Any of the foregoing could result in regulatory action,

litigation, customer attrition, or reputational harm that adversely affects our business. For more information

regarding our incident reporting obligations, see the section titled “—Any security breaches or other incidents,

including those that affect our networks, systems, or data, or the networks, systems, or data of our service

providers, suppliers, or customers, could adversely affect our business, financial condition, and results of

operations.”

The legal frameworks governing liability for actions taken autonomously by AI systems, including our agentic

products, are unsettled and could expose us to significant and unpredictable legal claims. Existing legal

doctrines governing agency, product liability, and professional negligence were developed in the context of

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human decision-making and have not been authoritatively applied to autonomous AI systems. We believe our

provision of intelligence service is considered a “service” in the context of legal frameworks addressing product

liability, but courts and regulators may reach different conclusions across jurisdictions. In addition, it is unclear

whether, and under what circumstances, actions taken by an AI agent could be deemed to create binding legal

obligations on behalf of the user or deploying enterprise, or whether our contractual protections, including

limitation of liability and indemnification provisions, will be enforceable or adequate in the context of claims

arising from autonomous agent conduct. We may face claims from customers, their end users, or third parties

alleging that we are liable for harm caused by our agents’ autonomous actions, even where the customer

configured, deployed, or supervised the agent. The absence of settled legal standards creates significant

uncertainty regarding our potential liability exposure and the adequacy of our risk mitigation measures.

Our expansion into new geographic markets further compounds these risks, as we must navigate differing

cultural norms regarding AI use, comply with diverse and evolving regulatory regimes that may impose varying

safety, compliance, or liability requirements, address language-specific vulnerabilities and content moderation

challenges, and potentially face regulatory enforcement actions, litigation, or other liabilities in jurisdictions

where we have more limited operational experience, including heightened risks of intellectual property theft,

unauthorized model access, or misuse associated with operating data center infrastructure in certain non-U.S.

locations.

If our models are involved in causing significant harm, we could be subject to legal claims, including personal

injury or negligence claims, regulatory enforcement actions, criminal investigations, or other governmental

efforts, which could result in costly litigation, significant financial judgments or settlements, disruptive

remediation obligations, or a challenging regulatory landscape. We have taken steps to limit our liability for

such matters—for example, through warranty disclaimers and limitations of liability in our terms of service—

but those contractual protections may not be upheld, or may not apply to certain claims, or may otherwise be

insufficient to limit our liability exposure under applicable law. Moreover, in some cases we have contractually

assumed additional liability. For example, to facilitate independent testing and evaluation of our frontier

models, we have agreed to indemnify certain external evaluators and testing vendors for specified losses arising

from testing activities, including security incidents, data loss, data breaches, and other harms associated with

such activities. Although our agreements with external evaluators and testing vendors generally limit the

amount of our indemnification obligations, certain of these agreements require us to defend and indemnify the

evaluator, without a cap on our liability, against certain third-party claims. These include claims arising from

allegations that our models or their outputs, as used in the evaluator’s authorized testing, infringe third-party

intellectual property or other proprietary rights, as well as certain other claims arising from the testing or

related engagement. Because our models may behave in ways that no user or developer intended, claims arising

from such actions could result in substantial liability. Our insurance policies also may not provide sufficient

coverage to adequately mitigate the potential liabilities we face, especially where any one incident, or a group of

incidents, causes disproportionate harm. In addition, with the scale of harm that could result from a

catastrophic AI-related incident, no single insurer, and potentially the insurance industry in the aggregate, may

have sufficient capacity or expertise to underwrite insurance commensurate with such exposure.

Further, the insurance market for AI-specific risks is nascent and evolving, and we may be unable to obtain

coverage for certain AI-related liabilities on commercially reasonable terms, or at all, leaving us exposed to

potentially significant uninsured losses. Harmful incidents involving our models, regardless of fault, could also

severely and disproportionately damage our reputation and brand as a safety-focused AI company, leading to

loss of customer trust and customer attrition, reduced demand for our models, platform, and applications, and

difficulty attracting and retaining talent. In addition, because we primarily serve enterprise customers, which

often have heightened expectations around safety, reliability, and compliance, any harmful incident or

perceived lapse in our safety practices could have a disproportionate adverse impact on our brand, customer

relationships, and revenue. Moreover, to the extent enterprises are attracted to our models, platform, and

applications due to our safety-focused positioning, any erosion of that perception could impair our ability to

attract and retain enterprise customers.

There can be no assurances that we will be able to predict, detect, and proactively prevent every harmful use or

harmful output of our AI models, in particular as we continue to rapidly develop our models, platform, and

applications, and expand our operations geographically, and any failure to do so could adversely affect our

reputation and brand or result in costly legal liability. There may have been past instances of harmful use or

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harmful output of our models that we did not detect, and there may be future instances that we will not detect.

Any of the foregoing risks could adversely affect our business, financial condition, and results of operations.

If we are unable to manage the risks related to our focus on and commitment to AI safety, our

brand, business, financial condition, and results of operations could be adversely affected.

Balancing Safety and Commercial Objectives. Our commitment to AI safety requires us to make difficult

judgments that balance safety considerations against commercial objectives, competitive pressures, and

stakeholder expectations. We often make judgment calls with respect to when we determine a model is safe

enough to release and which capabilities to develop or restrict. For example, in April 2026, we initially released

our frontier model, Mythos, as a gated research preview through Project Glasswing, available to select

organizations for cybersecurity applications, rather than making it broadly available at launch due to its

advanced capabilities in cyber vulnerability discovery. We expect that frontier models with similar or enhanced

capability profiles, whether developed by us or by other AI labs, will continue to emerge, and that future

Anthropic models exhibiting such capabilities may be subject to access constraints. More broadly, we believe it

is important to assess the safety of our models not only at release but throughout their development. For

models we anticipate will have novel capabilities or present novel safety risks, we plan to evaluate the safety of

each stage of training, including pretraining, post-training, and internal deployment, and we may delay or

pause a stage when we are not confident in our safety measures for that stage. For example, we recently chose to

delay pre-training a new frontier base model for more than a month to allow time to further enhance our

security measures related to preventing model weight exfiltration and protecting our intellectual property.

There can be no assurance, however, that the safeguards or access regimes we adopt will prove adequate, that

we will correctly identify which capabilities require restriction, or that constraints we impose will not be

circumvented. These judgments are particularly consequential because, as AI systems become more capable,

the potential severity of harm from misaligned or misused models increases correspondingly, and a wide range

of stakeholders, including researchers and policymakers, have raised concerns that sufficiently advanced AI

systems could pose catastrophic or existential risks to society if not developed and deployed responsibly. Our

safety-focused approach is designed in part to mitigate such risks, but there can be no assurance that our efforts

will be successful or that the broader AI industry will adopt similar safeguards. In particular, as AI systems

become more autonomous and capable of taking consequential actions with less human oversight, there is a

risk that such systems could, whether due to misalignment with human intentions, errors in objective

specification, or self-preserving behaviors, take harmful actions independently and at scale without human

intervention. Even if our own models do not cause such harm, a significant safety incident involving any

frontier AI could trigger broad reputational damage to the AI industry, public backlash, and sweeping

regulatory responses that could adversely affect our business. For example, in September 2026, media reports

citing a senior Federal Trade Commission (“FTC”) official indicated that the FTC has opened non-public

investigations into the potential risks that increasingly autonomous AI systems may pose to consumers. In

October 2026, the FTC issued a civil investigative demand to us seeking information about our consumer

protection, data protection, and privacy practices, as well as the safety and security of our products. The scope

of any investigation of us or its outcome, and any investigation, enforcement action, or adverse finding arising

from this or similar inquiries could result in significant costs, require changes to how we design, test, or deploy

our models, platform, and applications, or otherwise adversely affect our business, financial condition, and

results of operations. We may misjudge these trade-offs, either by being overly cautious and potentially losing

market opportunities, or by being insufficiently rigorous and releasing models, platforms, or applications that

cause harm. Even where human oversight mechanisms are in place, such mechanisms may prove insufficient in

practice if the volume, speed, or complexity of autonomous agent actions exceeds the capacity of human

reviewers to meaningfully evaluate and intervene, and any perceived failure of our oversight mechanisms could

expose us to regulatory enforcement, liability claims, and reputational harm. For more information, see the

section titled “—If the use of our AI models results in harm, whether through use by malicious actors or misuse

by other third parties, or if our model guardrails or safeguards fail to prevent such misuse, our reputation and

brand, business, financial condition, and results of operations could be adversely affected.”

Moreover, governmental authorities have restricted, and may in the future further restrict, the availability of

our models, including based on their assessment of the capabilities or safeguards of our models, independent of

our own safety-based access decisions. For example, in June 2026, the U.S. Department of Commerce imposed

worldwide export restrictions on our Fable 5 and Mythos 5 models, which we disabled for all customers until

those restrictions were lifted. For more information, see the section titled “—Governmental trade controls,

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including export and import controls, sanctions, customs requirements, and related regimes, could subject us to

liability or loss of contracting privileges or limit our ability to compete in certain markets.”

Internal Governance and Decision-Making

To institutionalize our safety commitments and ensure we are managed in a manner that responsibly balances

our tripartite goals as a PBC, we have established the LTBT, which through a special class of common stock,

Class T common stock, generally has the authority to elect and remove the Class T directors, who together will

constitute a majority of the authorized members of our board of directors. In addition to the LTBT and our

structure as a PBC, we train our models in accordance with Claude’s constitution, which we make publicly

available, and have adopted and continue to update safety policies, such as our Responsible Scaling Policy. We

also solicit and seriously consider input from a wide range of stakeholders and constituents, including our

stockholders, employees, customers, the LTBT, industry leaders and experts, and AI safety organizations. Such

practices and processes have previously resulted in, and may in the future result in, slower decision-making and

product releases. We may also face potential conflicts when safety and business interests diverge. If we do not

successfully manage these risks related to our AI safety processes and practices, or if there is a perception that

we have not successfully managed such risks, we may face reputational harm, internal conflicts resulting in a

deterioration of our company culture, slower or inferior product releases, or litigation. For more information,

see the section titled “—Risks Related to our Governance Structure.”

We have implemented an external reviewer program and engage researchers, adversarial testers, and other

third parties to support aspects of our safety, security, and model-evaluation efforts. Certain of these

arrangements are novel and may require us to provide such parties with access to internal information,

systems, personnel, or models, which could increase the risk of disclosure of confidential, proprietary, or other

sensitive information. In addition, findings, assessments, or public statements by such third parties may differ

from our views and could adversely affect customer trust, regulatory perceptions, or our reputation.

Heightened Reputational Vulnerability. As we have publicly positioned ourselves as a safety-focused

organization, we face heightened vulnerability to reputational harm from any perceived inconsistency between

our stated values and actual practices. We are held to higher standards than certain competitors that have not

made similar public commitments, and any incidents impacting our perception as a safety-focused organization

could result in:

•Employee Disruption. Employees who joined our company based on our safety commitments may

experience a decline in morale, disillusionment, a loss of trust in leadership, or reduced productivity if

they perceive we are not living up to our stated values. Public disagreements regarding our safety

approach, including criticism from current or former employees, or the departure of personnel

associated with our safety efforts, could amplify such perceptions. Such negative perceptions could also

impair our ability to recruit and hire new talent to the organization. Any erosion of our safety-focused

reputation could also make it more difficult or costly to attract and retain highly skilled employees,

including by increasing compensation or other hiring costs. These dynamics could lead to increased

turnover, loss of institutional knowledge, and reduced effectiveness of our teams, which could in turn

cause disruption to ongoing development and safety initiatives and impair our ability to remain at the

frontier of AI model development. 

•Customer Backlash. Customers and enterprise partners who choose to deploy our models, platform,

and applications based on our safety positioning may lose trust in us, terminate or decline to renew

their contracts, demand refunds, publicly criticize our company, or switch to our competitors, which

could result in harm to our reputation, revenue loss, and reduced market share. These risks may be

heightened with respect to programs in which we make models available only to a limited group of

vetted organizations, such as Project Glasswing. Organizations not selected for, or removed from, such

programs may perceive our access decisions as arbitrary, exclusionary, or anticompetitive, which could

result in reputational harm, loss of customer or partner relationships, regulatory complaints, or

litigation, including claims under antitrust or unfair competition laws. Conversely, participants in such

programs may publicly criticize us or terminate their participation if program terms, eligibility criteria,

transition arrangements to successor models, or capability levels do not meet their expectations.

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•Regulatory Scrutiny. Regulators may subject us to heightened oversight, investigations, enforcement

actions, or new or more burdensome compliance requirements based on the capabilities of our models,

platform, and applications or perceived failures to meet our own stated standards, which could

increase our operational costs and limit our ability to deploy our models, platform, and applications. 

•Damaging Media Coverage. Negative press coverage could amplify concerns about our safety

practices, reach broader audiences, including potential customers and investors, create lasting

reputational damage through viral social media discussion, and make future incidents subject to

heightened scrutiny, which could further exacerbate the adverse effects of any perceived failures to

meet our stated standards. 

•Litigation. We may face lawsuits from stockholders alleging misrepresentation, from customers

claiming breach of contractual or implied commitments, or from other parties alleging harm resulting

from the gap between our stated values and actual practices, leading to legal costs, settlements,

judgments, injunctions, or other liabilities and remedies.

Any safety-related controversy or incident, whether actual or perceived, and regardless of fault or frequency,

could prove significantly damaging to our business. In addition, we have engaged with governments in Canada,

the EU, the UK, the United States, and other jurisdictions in connection with Project Glasswing and related

frontier-capability programs, and we have positioned such programs, in part, to help provide the foundation for

broader industry coordination on the responsible release of frontier models with cybersecurity and other

advanced capabilities. The commercial viability of these and similar future programs may depend on sustained

governmental and industry coalition support. If such coalitions fail to materialize, are perceived as exclusionary

or anticompetitive, are rolled back, or result in mandates we cannot readily satisfy (including with respect to

access, localization, monitoring, or reporting), our ability to commercialize models with Mythos-class

capabilities, and the reputational benefits we derive from safety-focused positioning, could be materially

impaired. For more information, see the section titled “—If we are unable to maintain and enhance our brand

and reputation, our business, financial condition, and results of operations may be adversely affected.”

We voluntarily publicly disclose information regarding AI safety challenges, research findings, and limitations

of our models and systems, that exceeds standard industry practice and regulatory requirements. While our

intent with these voluntary disclosures is to advance the safe development of AI and build public trust, these

disclosures create several risks. The AI safety landscape is nascent and evolving rapidly, and our understanding

of and perspective on appropriate safety practices, risk tradeoffs, and deployment contexts may change over

time as technologies, use cases, and regulatory expectations develop. As a result, statements we make today

may later prove incomplete, require modification, or be interpreted differently in light of subsequent

developments. To the extent we adhere to prior public statements or frameworks, we may also limit our

operational flexibility, product development, or deployment decisions, even where evolving circumstances

would otherwise warrant a different approach. Our public statements about AI risks, safety challenges, areas of

uncertainty, or potential societal impacts, including statements regarding job displacement or economic

disruption, may be used against us in litigation, regulatory proceedings, or public controversies, particularly if

our future actions or statements are viewed as inconsistent with our prior statements and commitments.

Regulators have and could continue to use our disclosures as the basis for heightened scrutiny or more

stringent requirements applicable to us compared to less transparent competitors. Additionally, our disclosures

have provided, and may in the future provide, competitors with insights into our proprietary training and other

sensitive processes, research priorities, and strategic concerns, without reciprocal transparency, which may be

potentially competitively disadvantageous to us. If we are unable to effectively manage the foregoing risks, our

brand, reputation, and ability to compete could be adversely affected.

Resource Allocation and Scaling. Safety-focused development is resource-intensive. We must allocate limited

resources, capital, and talent between safety-focused workloads and other initiatives, often without clear

returns on our safety-focused investments. For example, our investments in interpretability research and

techniques designed to ensure our models’ behavior remains consistent with intended goals, values, and safety

objectives may not yield actual or perceived commercial returns. Additionally, as we develop our models,

platform, and applications, safety testing may become more expensive and resource intensive. Limited-access

programs such as Project Glasswing may also require us to design, operate, and continually maintain bespoke

vetting, contracting, monitoring, and offboarding processes that differ materially from our standard

commercial release processes, including coordination among participating organizations, transition planning to

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successor models, and enhanced internal controls commensurate with the heightened sensitivity of the

underlying capabilities. These activities impose ongoing operational, legal, and security costs that may recur as

future frontier models with similar capability profiles are released. If we fail to successfully manage resource

allocation or develop more efficient methods with respect to our safety initiatives, our safety outcomes,

business, financial condition, and results of operations could be adversely affected.

As our product portfolio and employee and customer base expand globally, applying safety principles

consistently across our rapidly expanding organization, models, platform, applications, use cases, and

jurisdictions and regulatory regimes has become increasingly challenging. For more information, see the

section titled “—To continue to grow our business, we will need to continue to expand internationally, and our

non-U.S. operations and sales to customers outside of the United States expose us to risks inherent in

international expansion, sales, and operations.”

If we are unable to successfully manage the foregoing risks related to our focus and commitment to AI safety,

our business, financial condition, and results of operations could be adversely affected.

If we are unable to maintain and enhance our brand and reputation, our business, financial

condition, and results of operations may be adversely affected.

We believe that maintaining and enhancing our brand identity and reputation is critical to our relationships

with, and to our ability to attract and retain, customers, partners, and employees. Our brand and reputation are

influenced not only by our actions, but also by the actions of our partners, our customers, and other third

parties with whom we do business, and by broader public perceptions of the AI industry, and we may be

grouped with other industry participants and judged similarly, regardless of differences in our approach or

conduct. The successful promotion of our brand depends on a number of factors, including our ability to

continue to develop and deliver reliable, high-quality, and responsible models, platforms, and applications that

meet the needs of our customers; our sales and marketing efforts, including our effectiveness at developing a

strong brand name and positive presence within the AI industry through participation in industry events and

key media coverage; the perceptions and experiences of both our enterprise and individual customers,

including through testimonials, use cases, and word-of-mouth; our ability to maintain security and reliability of

our models, platform, and applications; the actions of our management; and our ability to differentiate our

models, platform, and applications from those of our competitors, including through product design choices,

safeguards, business models, and policies, including our approach to monetization strategies that differ from

those of certain competitors. In addition, our brand is subject to heightened scrutiny with respect to perceived

societal, environmental, labor, health, and safety-related impacts of AI technologies, and a single perceived

failure could result in outsized reputational harm. For example, as AI systems become more capable or

prevalent, public perception that our models, platform, and applications contribute to job displacement or

economic disruption could generate significant negative media coverage, customer or employee backlash, or

organized opposition, regardless of the actual impact of our models, platform, and applications on employment.

Our ability to maintain and enhance our brand and reputation also depends on the effectiveness and scalability

of our internal communications and reputation-management capabilities, including our ability to support

global operations, and limitations in these areas could adversely affect our brand as we grow. Our crisis

response and reputation-management capabilities may be limited or underdeveloped, particularly as we scale,

which could impair our ability to respond effectively to adverse events and mitigate reputational harm.

The promotion of our brand requires us to make substantial expenditures, which we anticipate will increase as

our market becomes more competitive. We have in the past, and may in the future, face challenges in building

broader brand awareness and may fall behind competitors with more established or widely recognized brands.

Our brand promotion activities may not be successful or generate the awareness or increased revenue we

expect, and even if they do, any increase in revenue may not offset the significant expenses we incur in the

efforts to build our brand.

If we do not successfully maintain and enhance our brand, our business may not grow, we may have reduced

pricing power relative to competitors, we could lose customers or fail to attract potential customers or we could

fail to hire and retain employees, all of which could adversely affect our business, financial condition, and

results of operations.

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We derive substantially all of our revenue from a limited number of products and

applications, and our failure to maintain and expand our product portfolio could adversely

affect our business, financial condition, and results of operations.

We currently derive substantially all of our revenue from a limited number of products and applications,

primarily our Claude models and portfolio of applications that sit on top of the Claude Platform. This

dependence on a narrower set of offerings subjects us to various risks that could adversely affect our business,

financial condition, and results of operations.

Our concentration in a limited number of products and applications, as well as our focused development

strategy within specific areas of the broader AI landscape, reduces our ability to mitigate business risks through

diversification. While this focused approach may enable us to allocate resources efficiently and compete

effectively in our prioritized areas, it also creates the risk that significant market opportunities or the largest

addressable markets may emerge in areas outside our current strategic focus. Many of our competitors offer

diverse product portfolios across multiple business lines or pursue broader development across AI modalities,

enabling them to offset weaknesses in a particular area. In contrast, any decline in demand for our core

offerings, whether due to competition, technological changes, pricing pressure, changes in customer demand,

or other factors, would have a direct and disproportionate impact on our revenue and ability to achieve and

sustain profitability. Our concentration also reflects a strategy that prioritizes model capability as a principal

source of differentiation and relies substantially on organic adoption rather than a large direct sales

organization. The risks of that strategy, including the risks that differentiation among advanced models

narrows, that customers select providers based on factors other than capability, or that competitors capture the

individual users from whom our enterprise adoption often originates, are described in the sections titled “—We

face intense competition, and if we are unable to compete effectively, our business, financial condition, and

results of operations could be adversely affected” and “—We have a limited history under our current go-to-

market strategy, and our efforts to scale and evolve our customer acquisition, engagement, and retention model

may not be successful.”

The AI industry is rapidly evolving, and it is difficult to predict which modalities or applications will capture the

most durable commercial value or how the competitive landscape will shift. If the market for AI models,

platforms, and applications develops in ways that do not align with our chosen areas of focus, or if competitors

are better positioned to address the areas where the market opportunity ultimately proves largest, our ability to

sustain revenue growth and compete effectively could be adversely affected. If we experience a decline in

demand for our core offerings, we may not be able to successfully expand our product and application portfolio,

and even if we do, our new products and applications may not achieve market acceptance or generate sufficient

revenue to offset any decline in our existing business. Further, technical issues, security incidents, regulatory

restrictions, or reputational harm affecting our models, platform, and applications could have an immediate

and disproportionate impact on our business due to our product concentration where alternative revenue

streams may not be available to offset such impact.

The market for AI models, platforms, and applications is evolving quickly, and customer requirements and

expectations are changing rapidly. Customers may increasingly demand specialized solutions or specialized

integration and tooling that we do not currently offer and may not plan to offer, or may seek AI solutions

embedded more deeply into enterprise workflows. Enterprises may prefer to develop their own AI capabilities

internally or choose competitors that offer more comprehensive product suites. Moreover, because

substantially all of our models and applications are built on top of our frontier models, any defect, vulnerability,

safety issue, or performance degradation in an underlying frontier model could simultaneously affect multiple

products and applications and customer deployments, amplifying the impact of any such issue across our

business. If we fail to anticipate or respond effectively to these evolving customer needs, we may lose customers

to competitors or fail to acquire new customers.

In addition, we currently compete, and may increasingly compete, with some of our own customers. As we

expand our product portfolio or introduce new capabilities, our offerings may overlap with or directly compete

with the models, platforms, and applications that our customers provide. This risk is particularly acute with

software-as-a-service and other software companies, whose offerings may incorporate AI functionality similar

to, or dependent on, the capabilities we provide. These customers may view our product expansion as a

competitive threat to their business models and may reduce their purchases from us, limit their adoption of new

offerings, terminate their relationships with us, seek alternative providers, restrict our access to the compute we

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obtain from them, initiate intellectual property or other litigation against us, or accelerate efforts to develop

competing solutions internally in order to avoid relying on a direct competitor. This dynamic could result in

customer attrition, reduced expansion within our existing customer base, pricing pressure, or reputational

challenges, any of which could adversely affect our revenue growth and business prospects.

Expanding our product portfolio requires substantial time and investment. We must make significant

investments in research and development, compute infrastructure, engineering talent, sales and marketing, and

go-to-market capabilities to develop new models, platforms, and applications and enable continued adoption.

We may seek to expand into new products and markets, including areas outside of our current core

competencies or where we have limited experience, and we may not successfully develop, commercialize, or

support such offerings. Development timelines for AI models, platforms, and applications are uncertain, and

new capabilities, even when continuously improved and released into our models, platform, and applications,

may take significant time to achieve commercial scale. We may invest significant resources in products or

services that fail to gain market traction, experience technical difficulties, face unexpected competition, lead to

unexpected harm or societal impacts that do not align with our values, or generate insufficient returns to justify

the investment. Additionally, we face other constraints on our ability to expand our offerings, including the

ability to hire, retain, and motivate qualified AI researchers, engineers, and technical personnel; the capital

intensity of developing and operating AI models, platforms, and applications which require substantial

compute and infrastructure investment; and our limited portfolio may make it difficult to provide the

comprehensive, integrated solutions that customers may expect.

If we are unable to successfully expand our product and service portfolio, if we fail to compete effectively with

our current offerings, or if customer preferences shift away from our models, platform, and applications, our

business, financial condition, and results of operations could be adversely affected.

A substantial portion of our revenue and accounts receivable is driven by a limited number of

customers and distribution channels, and the loss of, or a significant reduction in, spend from

one or more of our top customers or disruption through those channels could adversely affect

our prospects, business, and financial condition.

A substantial portion of our revenue is driven by a limited number of customers. While no single customer

represented more than 10% of our revenue for the nine months ended September 30, 2026, our top five

customers represented approximately 25% of our revenue for the nine months ended September 30, 2026.

Many of our top customers are not subject to long-term contracts with us or have contracts with near-term

expiration dates and are able to reduce or in some cases cease spending at any time and for any reason. Further,

we have agreements with certain large customers which provide flexibility around financial commitments,

termination rights, indemnification, and security obligations. Our top customers may vary spend levels period

to period, and there can be no assurances that our large customers will continue to spend at levels similar to

prior periods.

We anticipate that we will continue to derive a significant portion of our revenue from a limited number of

customers for the foreseeable future, and in some cases, the portion of our revenue attributable to certain

customers may increase in the future. The composition of our customer base, including our top customers, may

fluctuate from period to period given that our customer composition has evolved and is expected to continue to

evolve significantly as our business continues to evolve and scale and as the use cases for AI continue to

develop.

In addition, a significant portion of our revenue and accounts receivable is associated with transactions

conducted with a limited number of CSPs that act as distribution and billing channels for our models. During

the years ended December 31, 2023, 2024, and 2025 and the six months ended June 30, 2026, revenue

generated from sales to customers through CSP marketplaces represented approximately 11%, 32%, 47%, and

48%, respectively, of total revenue. As of December 31, 2024 and 2025 and June 30, 2026, net accounts

receivable from sales through CSP marketplaces to customers represented 42%, 60%, and 58%, respectively, of

our net accounts receivable. These platforms bill end customers, collect payments on our behalf, and remit such

amounts to us, net of applicable platform and other fees. Any change to, or termination of, one of our significant

distribution relationships could adversely affect our business by disrupting customer access to our models,

reducing usage, or increasing customer acquisition, onboarding, and migration costs. In these third-party

arrangements, we generally maintain separate contractual arrangements with end customers governing access

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to, and pricing for, our models, independent of the applicable platform, and changes in, or termination of, a

particular distribution relationship would not independently eliminate those contractual relationships.

However, customers may be unwilling or unable to transition to alternative access points on commercially

acceptable terms or timelines, or at all, following a disruption, which could result in revenue loss, increased

costs, or adverse impacts to our growth, margins, and results of operations. In addition, any delay, dispute, or

operational issue affecting a platform’s collection or remittance of customer payments could adversely affect

our cash flows and working capital.

We may not be able to maintain or increase revenue from our top customers for a variety of reasons, including

but not limited to the following:

•customers may develop their own solutions that compete with our models, platform, and applications;

•some of our customers may redesign their systems to require fewer of our services with limited notice

to us and may choose not to renew or increase their purchases of our models, platform, and

applications;

•changes to our models, platform, and applications may not align with the needs or expectations of our

customers and such changes may reduce customer trust in us;

•our customers may have pre-existing or concurrent relationships with, or may be, current or potential

competitors that may affect such customers’ decisions to purchase our models, platform, and

applications;

•our customers and partners that heavily rely on our offerings may want to reduce such levels of

reliance, seek out competing offerings, or transition to other providers altogether; and

•our customers, particularly early-stage and high-growth companies, may depend on venture capital or

other external financing to fund their operations, and may reduce or cease spending with us if such

funding is delayed, reduced, or unavailable or if their access to capital becomes more costly.

Any adverse change in demand from our largest customers, in their ability or willingness to perform under their

contracts with us, in applicable laws or regulations, or in our broader strategic relationships with such

customers could adversely affect our business and prospects. As a result, a significant reduction in spending by,

or the loss of, one or more of our largest customers, if not offset by new customer relationships or increased

business from our other existing customers, could adversely affect our business, financial condition, and results

of operations. For additional risks related to our reliance on enterprise customers and government customers,

including longer sales cycles, complex procurement processes, heightened contractual, compliance, and security

requirements, and budgetary and policy constraints, see the sections titled “—Sales to enterprise customers

involve complexities and risks that could adversely affect our business, financial condition, and results of

operations” and “—Our sales to government entities and highly regulated organizations are subject to

challenges and risks.”

We have incurred significant indebtedness in order to operate and grow our business,

including to fund our substantial compute commitments, and our ability to service this

indebtedness may be constrained by our cash flows and liquidity.

In order to operate and grow our business, including to fund our substantial compute commitments, we have

incurred a substantial amount of debt, which requires significant interest and principal payments. As of June

30, 2026, our total indebtedness was $6.2 billion, reflecting the aggregate principal amount outstanding under

the convertible promissory notes issued to Amazon (through Amazon Web Services, Inc.) pursuant to the

Convertible Note Purchase Agreement, dated as of September 19, 2023, by and between us and Amazon (the

“Amazon 2023 NPA”) and the New Convertible Note Purchase Agreement, dated as of November 22, 2024, by

and between us and Amazon (the “Amazon 2024 NPA”) (all such notes issued thereunder, collectively, the

“Amazon Notes”). We may also incur additional indebtedness to meet our future financing needs. We have

guaranteed the obligations of certain of our subsidiaries that are party to AI infrastructure arrangements, as

well as pursuant to agreements we entered into in connection with an equipment lease with a third-party

partner, Broadcom Inc. (“Broadcom”) in March 2026 to procure specialized AI accelerators and associated

components (under which Broadcom intends to assign to a designated financial partner) (the “2026 Lease

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Arrangement”). In addition, we have the ability to issue, if needed, up to $42.0 billion in aggregate principal

amount of convertible promissory notes to Broadcom or, subject to our consent (not to be unreasonably

withheld), a designated financial partner pursuant to a note purchase agreement that we entered into with

Broadcom in March 2026 (the “Infrastructure Partner 2026 NPA”) to finance obligations under the 2026 Lease

Arrangement. We may be required to use a substantial portion of our cash flows from operations to pay

interest, principal, or other required payments on our indebtedness.

The delivery of shares of our Class N common stock upon conversion of our outstanding convertible promissory

notes could result in dilution to our existing stockholders. Following this offering, assuming the conversion of

our outstanding convertible promissory notes into an aggregate of            shares of our Class N common stock,

based upon the aggregate principal and accrued and unpaid interest on such notes as of September 30, 2026,

and an assumed initial public offering price of $           per share (which is the midpoint of the estimated offering

price range set forth on the cover page of this prospectus), holders of our outstanding convertible promissory

notes would collectively hold in the aggregate approximately           % of our Class N common stock, which

represents           % of our total outstanding common stock following this offering. Pursuant to the terms of the

Amazon Notes, to the extent that the full amount of such notes cannot convert into shares of our Class N

common stock in connection with this offering as a result of the ownership cap applicable to the Amazon Notes,

which may be waived at Amazon’s election, the remaining balance of such notes will automatically convert,

subject to Amazon’s ownership cap, into shares of our Class N common stock at the applicable conversion price

at the end of each fiscal quarter following this offering or, if such remaining balance of such notes does not

convert before the applicable maturity date because of the applicable ownership cap, such balance will be repaid

in cash at such maturity date. For more information about our convertible promissory notes, see the section

titled “Management’s Discussion and Analysis of Financial Condition and Results of Operations—Liquidity and

Capital Resources—Convertible Notes.”

Our ability to make scheduled payments in respect of, to pay interest on, or to refinance our indebtedness,

including the A&R Credit Agreement and our outstanding convertible promissory notes, depends on our future

performance, which is subject to economic, financial, competitive, and other factors beyond our control. Such

payments will reduce the funds available to us for working capital, capital expenditures, and other corporate

purposes and may limit our ability to obtain additional financing for working capital, capital expenditures,

expansion plans, and other investments. Our business may not be able to generate cash flows from operations

in the future that are sufficient to service our debt and make necessary capital expenditures. If we are unable to

generate such cash flows, we may be required to adopt one or more alternatives, such as selling assets or

obtaining additional debt financing or equity capital on terms that may be onerous or highly dilutive. Our

ability to refinance our indebtedness will depend on the capital markets and our financial condition at such

time. We may not be able to engage in any of these activities or engage in these activities on desirable terms,

which could result in a default on our debt obligations and adversely affect our financial condition. Further, the

terms of the A&R Credit Agreement and the Infrastructure Partner 2026 NPA include a number of covenants

that limit our ability and our subsidiaries’ ability to, among other things, incur additional indebtedness, create

liens, make asset sales or investments, engage in mergers or other fundamental changes, pay dividends or

distributions, repurchase or redeem equity interests, and enter into transactions with affiliates. The terms of the

A&R Credit Agreement may restrict our current and future operations and could adversely affect our ability to

finance our future operations or capital needs. For more information, see the sections titled “—We may require

additional capital to meet our substantial ongoing obligations and support our business growth, and our ability

to generate sufficient revenue and secure additional capital on acceptable terms is critical to our continued

operations and competitive position” and “—If the market for our models, platform, and applications develops

more slowly than we expect or declines, our growth may slow or stall, and our business, financial condition, and

results of operations could be adversely affected.”

We are also subject to variable interest rate risk because the interest rate under the A&R Credit Agreement

varies based on a margin over an indexed rate or an adjusted base rate. If interest rates associated with our

floating rate debt increase, our debt service obligations in connection with the A&R Credit Agreement would

increase even though the amount borrowed remained the same, and our available cash would correspondingly

decrease. Our substantial amount of debt, combined with variable interest rates, could limit our flexibility in

planning for, or reacting to, changes in our business and the markets in which we operate, including limiting

our future investments or our ability to enter into acquisitions and strategic partnerships, and obtain financing

for such transactions.

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In addition, our indebtedness, combined with our other financial obligations and contractual commitments,

could have other important consequences. For example, they could:

•make us more vulnerable to adverse changes in general U.S. and non-U.S. economic, industry, and

competitive conditions and adverse changes in government regulation;

•limit our flexibility in planning for, or reacting to, changes in our business and our industry;

•place us at a disadvantage compared to our competitors that have less or fixed rate indebtedness;

•limit our ability to borrow additional amounts to fund acquisitions, for working capital, and for other

general corporate purposes; and

•make an acquisition of our company less attractive or more difficult.

Any of these factors could adversely affect our business, financial condition, and results of operations. In

addition, if we incur additional indebtedness, the risks related to our business and our ability to service or repay

our indebtedness would increase.

A failure by us to comply with the covenants, including those tied, in part, to operational and performance-

based metrics, or payment obligations under the A&R Credit Agreement or our outstanding convertible

promissory notes, as applicable, whether as a result of financial constraints, operational challenges,

inexperience managing complex infrastructure and large-scale capital commitments, or otherwise, could result

in an event of default under these instruments. Upon an event of default under the A&R Credit Agreement, the

lenders would have the right to accelerate all amounts outstanding and exercise other remedies available to

them, including enforcing their rights against the collateral securing the A&R Credit Agreement. An event of

default under our outstanding convertible promissory notes would similarly give the noteholders the right to

declare all amounts outstanding under our outstanding convertible promissory notes immediately due and

payable. If the indebtedness under the A&R Credit Agreement and/or outstanding convertible promissory notes

were to be accelerated, we may not have sufficient cash or be able to borrow sufficient funds to refinance such

indebtedness or sell sufficient assets to repay such indebtedness, which could adversely affect our business,

cash flows, financial condition, and results of operations. Even if we were able to obtain new financing, it may

not be on commercially reasonable terms or on terms that are acceptable to us.

We may not have the ability to raise the funds necessary to repay the principal and accrued

interest of our outstanding convertible promissory notes or the A&R Credit Agreement in cash

when required by the terms of the notes or the A&R Credit Agreement, as applicable, or at

their maturity.

In connection with the completion of this offering, the Amazon Notes will convert into Class N common stock,

subject, in each case, to an ownership cap as set forth in the Amazon Notes, which may be waived at Amazon’s

election. In the event that any of the notes comprising the Amazon Notes cannot be fully converted without

exceeding the ownership cap applicable to such notes, the balance of any such notes will remain outstanding

and will automatically convert, subject to Amazon’s ownership cap, into shares of our Class N common stock at

the applicable conversion price at the end of each fiscal quarter following the completion of this offering. To the

extent any of our convertible promissory notes remain outstanding, or if we issue any additional convertible

promissory notes following the completion of this offering, we will be required to repay such note in cash at its

maturity, unless earlier converted or repaid pursuant to the terms of such note. In addition, we will be required

to repay in full all amounts outstanding under the A&R Credit Agreement upon its maturity. However, we may

not have enough available cash on hand or be able to obtain financing at the time we are required to make any

repayments on outstanding convertible promissory notes or under the A&R Credit Agreement.

Our failure to repay any outstanding convertible promissory notes or amounts outstanding under the A&R

Credit Agreement, as applicable, at a time when the repayment is required, or to pay cash upon any conversion

of outstanding convertible promissory notes, as applicable, as required pursuant to the terms of each note or

the applicable NPA, would constitute a default thereunder. A default under an outstanding convertible

promissory note and/or the applicable NPA as well as the A&R Credit Agreement could also lead to a default

under agreements governing our existing and future indebtedness. If the payment of the related indebtedness

were to be accelerated after any applicable notice or grace periods, we may not have sufficient funds to repay

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such indebtedness and repay the amounts outstanding under the A&R Credit Agreement or outstanding

convertible promissory notes at the applicable maturity, or when repayment is otherwise required pursuant to

the terms of the note.

Our pricing structures for our models, platform, and applications change from time to time,

which could adversely affect our business, financial condition, and results of operations.

We have in the past changed, and we expect that in the future we may change, our pricing models, including as

a result of competition, macroeconomic conditions, compliance with increased regulatory hurdles, the

maturation of the market for AI models, platforms, and applications, or changes in how our models, platform,

and applications are broadly consumed. As a result, we may be required to reduce our prices, offer shorter

contract durations or offer alternative pricing models, such as outcome or task-based pricing, any of which

could adversely affect our business. In addition, our agentic offerings are structurally more compute-intensive

than our non-agentic offerings. If we are unable to implement pricing models that adequately reflect the higher

compute intensity of these agentic workloads, or if competitive dynamics constrain our ability to price these

products at levels sufficient to cover their costs, our compute efficiency could deteriorate as agentic usage

grows, which could adversely affect our ability to achieve or sustain profitability.

Additionally, as we continue to target selling our models, platform, and applications to our enterprise

customers, these customers may demand different pricing structures, price concessions, or additional

functionality at the same price levels. If we are unable to modify or develop effective pricing models and

strategies that are attractive to existing and prospective customers, our business, financial condition, and

results of operations may be adversely affected.

If we are unable to attract, retain, or motivate highly skilled personnel, we may not be able to

grow or operate effectively.

Our performance and ability to grow our business depend on the talents and efforts of highly skilled

individuals, and our future success depends on our continuing ability to identify, hire, develop, motivate, and

retain highly skilled personnel for all areas of our organization. Our business is particularly dependent on a

limited pool of researchers, engineers, and technical personnel with specialized experience in designing,

training, deploying, and operating frontier models and the underlying infrastructure that supports them. We

have from time to time experienced, and we expect to continue to experience, difficulty in hiring and retaining

highly skilled employees with appropriate qualifications at the pace that our operations require. Competition in

our industry relating to hiring and retaining employees with appropriate qualifications and on competitive

economic terms is exceptionally intense and has escalated significantly in recent periods, especially in the San

Francisco Bay Area, where our headquarters is located and where we have a substantial presence and need for

highly skilled personnel. A small number of well-capitalized AI labs, large technology companies, and new

market entrants compete aggressively for a relatively fixed supply of individuals with the requisite expertise.

Certain of our competitors have directly solicited, and continue to directly solicit, our employees. Our former

employees are also generally able to join or found competing companies immediately following their departure,

and, subject to their confidentiality and other legal obligations, use the general skills, know-how, and

experience they developed while employed by us. In addition, we have in the past, and may in the future, be

subject to claims or disputes relating to the solicitation or hiring of employees, including allegations that such

hires violated non-compete, non-solicitation, intellectual property, confidentiality, or other employment-

related obligations.

As our company continues to grow and our industry evolves, the incentives to attract, retain, and motivate

employees provided by our cash and equity awards or by future arrangements may not be as effective as in the

past. Many of the companies with which we compete for highly qualified personnel have greater resources than

we have and may be willing to offer more attractive compensation packages. We may need to invest significant

amounts of cash and equity to attract and retain employees, resulting in substantial additional share-based

compensation expense and dilution to the ownership of our existing stockholders, and we may never realize

returns on these investments that are commensurate with the level of our expenditures. If the perceived value

of our compensatory package declines or is subject to significant value fluctuations, it may adversely affect our

ability to attract and retain highly skilled employees. In addition, we have a number of current employees,

including our co-founders, who hold equity in our company or whose equity awards are or will become

substantially vested upon the completion of this offering. This may be particularly true for certain of our longer-

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tenured and early employees, whose equity holdings may represent a significant portion of their personal

wealth. As a result, it may be difficult for us to continue to retain and motivate these employees, and the value

of their holdings could affect their decisions about whether or not they continue to work for us.

Historically, our ability to successfully attract, retain, and motivate our personnel has in large part been due to

our company culture and commitment to safety and responsible scaling and development. If we are unable to

maintain our culture, if we make decisions as a company that our employees do not believe align with our

values, or if events take place, regardless of fault, that call into question whether we have operated in

accordance with our values, our ability to attract, retain, and motivate our personnel may be adversely affected.

Rapid growth has also created workforce-planning and execution challenges, including limitations in our ability

to accurately forecast headcount needs, periods of accelerated hiring followed by corrective actions that may

disrupt operations or reduce morale, and increased reliance on managers operating at greater scale than in

their prior experience, which introduces additional operational, legal, reputational, and execution risk as the

organization continues to expand. If we move into new geographies, we will need to attract and recruit skilled

personnel in those geographic areas, but it may be challenging for us to compete with traditional local

employers in these regions for talent. If we fail to attract new personnel or fail to retain and motivate our

current personnel who are capable of meeting our growing technical, operational, and managerial

requirements, our business may be adversely affected.

In addition, heightened public attention on AI has increased physical and informational security risks, and we

have experienced threats to employee safety and attempts to obtain confidential information through physical

or digital means, which, despite the security measures we have implemented at certain facilities, may be

exacerbated by our global and flexible working arrangements and could adversely affect employee morale,

productivity, and our ability to attract, retain, and motivate highly skilled personnel. Addressing these risks also

requires us to attract and retain additional specialized security personnel, and difficulties in recruiting qualified

security engineers could further exacerbate these challenges.

Further, changes to immigration policies that restrain the flow of professional and technical talent, including

but not limited to U.S. immigration policies, may inhibit our ability to recruit and retain highly qualified

employees. If we are unable to effectively manage the foregoing risks, our prospects, business, financial

condition, and results of operations could be adversely affected.

We have a limited operating history in an evolving and nascent industry, which makes it

difficult to evaluate our future prospects and may increase the risk that we will not be

successful.

We were founded in 2021 and launched our first commercial product, Claude, publicly in the first quarter of

2023. During this time, our business has grown rapidly. We operate in an industry characterized by rapid and

unpredictable technological change, evolving safety and regulatory expectations, significant capital and

compute requirements, and uncertain commercial adoption patterns. Our limited operating history and our

evolving and nascent business and industry make it difficult to evaluate our future prospects and the risks and

challenges we may encounter. These risks and challenges include our ability to:

•develop and release new models and products on a timely and cost-effective basis;

•accurately forecast our revenue, operating expenses, and compute requirements in an environment

characterized by rapid technological change and usage patterns that may scale in nonlinear or

exponential ways;

•secure access to sufficient compute to meet the needs of all our workloads and manage the risks related

to securing compute;

•effectively manage our growth, including our cash flows and capital needs;

•accurately predict customer demands, expectations, or requirements;

•maintain and enhance our brand and reputation;

•attract, retain, utilize, and motivate our highly skilled personnel;

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•build and maintain our strategic partnerships;

•anticipate and respond to macroeconomic changes and changes in the industry and markets in which

we operate;

•anticipate and respond to evolving regulatory requirements and political dynamics;

•maintain our safety-focused approach while meeting market demands;

•successfully monetize our models, platform, and applications; and

•respond effectively to competitive threats.

If we fail to effectively address the risks and challenges we face, including those described elsewhere in this

“Risk Factors” section, our business, financial condition, and results of operations could be adversely affected.

We have encountered in the past, and will encounter in the future, risks and uncertainties frequently

experienced by growing companies with limited operating histories in rapidly changing industries. If our

assumptions regarding these risks and uncertainties, which we use to plan and operate our business, are

incorrect or change, or if we do not address these risks successfully, our results of operations could differ

materially from our expectations and our business, financial condition, and results of operations could be

adversely affected. 

We are at an early stage of our revenue growth, we have experienced rapid growth in recent

periods, and our historical growth rates are not indicative of future performance or our

ability to sustain or forecast future revenue growth.

We have grown rapidly over the last several years, and therefore our recent revenue growth and financial

performance should not be considered indicative of our future performance. In 2023, 2024, and 2025, our

revenue was $41 million, $386 million, and $4.6 billion, respectively, representing year-over-year growth rates

of 841% and 1,088%, respectively. In the six months ended June 30, 2026, our revenue was $16.3 billion,

representing a year-over-year growth rate of 1,300%. We do not expect our revenue will continue to grow at

comparable rates, and we cannot assure you that it will continue to grow at all. Our recent growth may reflect

early-stage adoption dynamics, the nascency of the AI market, and rapid initial customer expansion that may

not be sustainable over time, and it may decline significantly and more rapidly than we anticipate, as our

revenue base increases, as the market matures, and as a result of the other factors described below. We expect

our revenue growth rate to decline over time. In addition, because the AI industry is very nascent, we have

struggled to accurately forecast our revenue in the past and may struggle to do so in the future.

We may experience declines in our revenue growth rate as a result of a number of factors, including:

•the slowing or shifting demand for our models, platform, and applications or the market as a whole;

•our inability to secure sufficient compute and direct it efficiently across our organization;

•insufficient growth in the number of users and paying customers of our models, platform, and

applications or the failure to increase sales of our models, platform, and applications to existing

customers;

•failures, errors, or performance limitations in our models, including unexpected behavior, degraded

outputs, outages, or inability to meet customer expectations or use-case requirements;

•increasing competition among existing competitors and new market entrants;

•the safety and risk mitigation measures we implement in developing and releasing our models,

including any resulting delays in model development or release, or the adoption of laws, regulations, or

standards that affect how and when frontier AI models may be developed or released;

•our failure to continue to capitalize on growth opportunities;

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•our ability to collect amounts owed to us from customers, including as a result of customer credit risk,

billing disputes, or delays in payment;

•our reliance on, and the terms of, relationships with key partners and distribution channels, and any

changes to, or termination of, such arrangements;

•new or more restrictive laws, regulations, or regulatory actions affecting AI development, deployment,

or use, including taxes, fees, or other measures specifically applicable to AI companies or AI-related

labor displacement; and

•reputational harm, adverse publicity, or heightened scrutiny that reduces customer adoption or

expansion.

We expect to continue to make investments in the development and expansion of our business, which may not

result in increased revenue or growth. If our revenue or revenue growth rate declines, or our revenue growth

rate declines with respect to certain markets or customer categories, our business, results of operations, and

investors’ perceptions of our business could be adversely affected, which could in turn negatively impact the

market price of our Class A common stock.

If we fail to manage our growth effectively, our brand, business, financial condition, and

results of operations could be adversely affected.

Since 2021, we have experienced rapid growth in our employee headcount, number of customers, geographic

reach, and our operations, and we expect this growth to continue. For example, the number of our employees

increased from approximately 940 as of December 31, 2024 to approximately 5,300 as of September 30, 2026,

and our revenue increased from $197 million for the three months ended December 31, 2024 to $           for the

three months ended September 30, 2026. This growth has placed, and may continue to place, a significant

strain on our management and our operational and financial resources.

Our ability to successfully manage this growth depends on our ability to scale and integrate our operations,

workforce, technologies, models, platform, and applications, and any future acquisitions while preserving the

beneficial aspects of our company culture. Continued growth may strain our ability to develop and enhance our

operational, compliance, technical, financial, and management controls, improve our reporting systems and

procedures, recruit, train, and retain highly skilled personnel, and maintain customer satisfaction. If we are

unable to do so, our operations, compliance with applicable laws, development and deployment of our models,

platform, and applications, and customer experience could be adversely affected.

As we expand, we must also manage an increasing number of relationships with strategic partners, customers,

vendors, and other third parties that are critical to our business, including those that provide compute, data

center infrastructure, networking, software tools, and other services necessary to develop, train, deploy, and

operate our models. If these relationships deteriorate, or if our third-party providers are unable to scale their

services in line with our growth, we may experience delays, service disruptions, reduced sales to new customers,

or the loss of existing customers, which could adversely affect our revenue growth and reputation. In addition,

our ability to manage our growth depends in part on our ability to accurately plan for and efficiently manage the

compute required to develop, train, deploy, and operate our models. Any material underinvestment or

overinvestment in such resources could result in service limitations, increased costs, operational inefficiencies,

or delays in model development, any of which could adversely affect our business.

If we fail to effectively manage the growth of our business and operations, we may be unable to maintain

effective internal controls, reporting systems, and compliance processes, may face increased regulatory

scrutiny, and may suffer harm to our brand and our ability to attract and retain customers. As a result, our

business, financial condition, and results of operations could be adversely affected.

We have a history of net losses and may not generate sufficient revenue to achieve or sustain

profitability in the future.

We have incurred net losses in each year since our founding, including a net loss of $1.5 billion, $8.3 billion,

and $42.0 billion for the years ended December 31, 2023, 2024, and 2025, respectively, and $80.7 billion for

the six months ended June 30, 2026, and we may not achieve or sustain profitability in the future. These net

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losses included change in fair value of convertible notes, derivative liabilities, and SAFEs of $1.0 billion, $5.4

billion, and $34.3 billion for the years ended December 31, 2023, 2024, and 2025, respectively, and $72.4

billion for the six months ended June 30, 2026, primarily driven by an increase in the fair value of our

outstanding convertible promissory notes resulting from an increase in our enterprise valuation during each of

the respective periods. While we have experienced significant revenue growth in recent periods, our business is

highly capital intensive, and our ability to remain at the frontier of AI capabilities and secure sufficient compute

depends in meaningful part on our ability to generate and sustain substantial revenue and improve our

operating efficiencies. Further, our revenue growth may not be sustainable, and our rate of growth may

decrease. We expect our costs will increase over time and our losses will continue as we expect to invest

significant resources towards growing our business and operating as a public company.

We have expended and expect to continue to expend substantial financial and other resources related to the

growth of our business, including:

•investments to enhance our access and ability to secure compute;

•continued investments in research and development to remain at the frontier of AI model development

and introduce new features and enhancements to our models, platform, and applications;

•expansion of our sales and marketing activities;

•hiring additional employees;

•expansion of our operations across our multiple geographies;

•investments in our expanding general and administrative organization;

•costs associated with complying with existing and evolving laws, regulations, and industry standards

applicable to AI, data protection, privacy, and security, among other things;

•investments in AI safety, risk management, monitoring, evaluation, and mitigation efforts;

•additional expenses associated with operating as a public company; and

•costs related to legal proceedings.

For example, as of and subsequent to September 30, 2026, we have entered into purchase commitments and

lease agreements, including short-term commitments, as well as leases not yet commenced, with an aggregate

committed spend of more than $          , which may substantially increase our operating expenses and cash

requirements. These expenditures and investments may be more costly than we expect and may not result in

increased revenue or growth in our business. If we are unable to successfully address these risks and challenges

as we encounter them, our business, financial condition, and results of operations could be adversely affected.

In addition, we have granted RSUs to our employees and other service providers, which vest upon the

satisfaction of both a service-based condition and a performance-based condition. The service-based condition

for a majority of such RSUs is satisfied over a period of four years. The performance-based condition of such

RSUs will be satisfied upon the effectiveness of the registration statement of which this prospectus forms a part.

We account for award forfeitures as they occur. As of June 30, 2026, no stock-based compensation expense had

been recognized for such RSUs because a qualifying event as described above was not probable. In the quarter

in which this offering is completed, we will begin recording stock-based compensation expense based on the

grant-date fair value of the RSUs using the accelerated attribution method. If this offering had been completed

on June 30, 2026, we would have recorded $2.9 billion of cumulative stock-based compensation expense

related to the RSUs on that date, and an additional $23.7 billion of unrecognized stock-based compensation

expense related to the RSUs, would be recognized over a weighted-average period of approximately 2.1 years. In

addition to stock-based compensation expense associated with the RSUs, as of June 30, 2026, we had

unrecognized stock-based compensation expense of approximately $3.1 billion related to other outstanding

equity awards, which we expect to recognize over a weighted-average period of approximately 1.3 years.

Subsequent to June 30, 2026, our board of directors approved the grant of            RSUs, which grants will

become effective as of the day prior to the effectiveness of the registration statement of which this prospectus

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forms a part. The grant-date fair value of each RSU subject to these awards will be equal to the price per share

of the shares sold in this offering. These RSUs will vest upon the satisfaction of both a service-based condition

and a performance-based condition as described above. Assuming a grant-date fair value of $           per share,

which is the midpoint of the estimated offering price range set forth on the cover page of this prospectus, we

would expect to record stock-based compensation expense of $           billion related to such RSUs, over a

weighted-average period of approximately            years, commencing in the quarter in which this offering is

completed. Following the completion of this offering, the stock-based compensation expense related to RSUs

and other outstanding equity awards will result in increases in our expenses in future periods, in particular, in

the quarter in which this offering is completed.

If we fail to generate adequate revenue to offset increases in our operating expenses, improve our operating

efficiencies, or otherwise manage our costs as we invest in our business, we may continue to incur significant

losses in the future and may not be able to achieve or sustain profitability.

Our results of operations may fluctuate significantly on a period-to-period basis, including as

a result of strategic investment decisions and substantial compute-related expenditures,

which could cause the market price of our Class A common stock to decline.

Our results of operations have historically varied from period to period, and we expect that our results of

operations will continue to vary significantly from quarter to quarter and from year to year in the future, such

that the results of any one period should not be relied upon as an indication of future performance. In

particular, our financial performance may be significantly influenced by strategic decisions we make regarding

the allocation of resources and the amount and timing of operating expenses and capital expenditures that we

may incur to maintain and expand our business and operations and to remain competitive. We may make

significant and, at times, discrete investments in areas such as research and development, compute and related

infrastructure, product development, safety and security initiatives, and go-to-market expansion, which may be

uneven in size and timing. These investments may materially increase our expenses in a given period and cause

our results of operations to fluctuate significantly or vary meaningfully from period to period, and may result in

periods of reduced margins or increased losses even if our underlying business trends remain unchanged or

continue to improve. As a result, our financial performance may not follow any consistent pattern, and prior or

interim periods of improved results of operations should not be viewed as indicative of our future performance.

Our revenue in any period has also included, and we expect will continue to include, amounts from customers

that we subsequently determine are using our models, platform, and applications in violation of our usage

policy or commercial terms, and whose revenue would not be expected to recur following restriction or

termination of their access. We believe this dynamic is common in our industry. Detection, investigation, and

enforcement take time, and we cannot assure you that we will identify such usage, or restrict or terminate a

customer’s access, on a timely basis or at all. Customers may evade our controls, and customers whose access is

restricted or terminated may re-register under new accounts. As a result, revenue from such customers may

continue or recur notwithstanding our enforcement efforts. Our continued detection and enforcement efforts,

and in particular, the enhancement of such efforts in August and September 2026, and the timing of any

resulting restrictions or terminations, are expected to reduce the percentage of revenue from customers using

our models, platform, and applications in violation of our usage policy or commercial terms, and may reduce

our overall revenue and growth rates in future periods and contribute to variability in our results from period to

period.

Our results of operations are also affected by seasonal variations in the usage of our models, platform, and

applications. Because our revenue is primarily consumption-based, we have experienced, and expect to

continue to experience, lower usage around holiday and vacation periods in the summer and winter, when

certain customer workflows slow down and overall customer activity declines. Our results of operations may

also vary with the timing and cadence of our model and product releases, which are uneven from period to

period and may cause usage, and therefore revenue, to increase or decline between periods. Our historical

growth rates may have masked the impact of seasonal trends on our results. As our growth rate declines over

time, we expect seasonal effects to become more apparent in, and to have a greater effect on, our period-to-

period results. In addition, other seasonal trends may develop, and the seasonal trends that we currently

experience may become more pronounced, as we continue to scale.

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Our results of operations may also fluctuate due to a variety of additional factors, many of which are outside of

our control and difficult to predict, including, but not limited to:

•the level of demand for our models, platform, and applications, and our ability to forecast such

demand;

•our ability to forecast required compute and to obtain additional compute as needed, and any increase

in costs thereof;

•our ability to expand usage within organizations;

•our ability to attract and retain customers and increase sales of our models, platform, and applications

to existing customers;

•our ability to effectively manage our relationships with our third-party service providers and our

reliance on such providers for critical infrastructure and services;

•the timing and success of new features, integrations, capabilities, and enhancements by us to our

models, platform, and applications, or by our competitors to their products;

•the safety and risk mitigation measures we implement in developing and releasing our models,

including any resulting delays in model development or release, or the adoption of laws, regulations, or

standards that affect how and when frontier AI models may be developed or released;

•our ability to achieve widespread acceptance and use of our models, platform, and applications;

•changes in the competitive landscape and introduction of competitive companies, models, platforms,

and applications;

•security breaches, technical difficulties, or interruptions to our models, platform, or application;

•real or perceived improper or unauthorized use of, disclosure of, or access to confidential, proprietary,

personal, or sensitive data;

•pricing pressure as a result of competition or otherwise;

•adverse litigation judgments, other dispute-related settlement payments, or other litigation-related

costs;

•the number of employees hired;

•the timing of the grant or vesting of equity awards to employees, directors, or consultants;

•the vesting and settlement of equity awards, including any cash used to remit taxes on behalf of

employees in connection with the settlement of RSUs and the recognition of stock-based compensation

expense;

•our ability to maintain, protect, and enhance our brand;

•declines in the values of foreign currencies relative to the U.S. dollar;

•changes in, and continuing uncertainty in relation to, the legislative or regulatory environment with

respect to our industry;

•enforcement by government regulators, including investigations, proceedings, fines, orders,

designations, or consent decrees;

•increased legal and regulatory compliance costs in new and existing markets;

•costs and timing of expenses related to the potential acquisition of businesses, talent, technologies, or

intellectual property, including potentially significant amortization costs and possible write-downs;

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•catastrophic events, and resulting interruptions in the availability of our models, platform, and

applications; and

•general economic conditions in either U.S. or non-U.S. markets, including geopolitical uncertainty and

instability and their effects on software spending.

Any one or more of the factors above, or other factors in this “Risk Factors” section, may result in significant

fluctuations in our results of operations or other key metrics, which may cause such results to fall below our

financial guidance or other projections or the expectations of analysts or investors, and cause the market price

of our Class A common stock to decline.

Certain of our operating metrics are subject to assumptions and limitations. As a result, these

metrics may not provide an accurate indication of our actual performance or future results.

Certain of our operating metrics, such as Run-Rate Revenue, Net Revenue Retention, customer counts, and

Claude’s success rate, are based on numerous assumptions and limitations, are calculated using data from

internal systems and tools, have not been independently verified by third parties, are subject to inherent

limitations in measurement, and may not accurately reflect actual results or provide an accurate indication of

future or expected results.

Run-Rate Revenue is not a substitute for revenue prepared in accordance with GAAP or a forecast of revenue.

Because Run-Rate Revenue annualizes our consumption-based fees for a trailing 28-day period and our

subscription-based fees for a single month, it assumes that activity during those measurement periods has

continued at the same rate for a full year. Because it annualizes a short measurement period, Run-Rate Revenue

measured during a period of seasonally higher or lower usage, such as the reduced usage we have typically

experienced around holiday and vacation periods in the summer and winter, may differ significantly from Run-

Rate Revenue measured at other times, and in each case may not correspond to the revenue we ultimately

recognize over any quarter or fiscal year. Our actual historical revenue and future revenue may differ materially

from this measure. Both our consumption-based and subscription-based revenue may fluctuate from period to

period, and in particular, our consumption-based revenue may fluctuate significantly or decline if customers

reduce, limit, or do not expand their usage or spend, or shift usage to lower-priced models, including in

response to competitive offerings, pricing changes, changes in customer budgets or strategic priorities

regarding AI investment, seasonality, or general economic conditions. In addition, sustaining and growing this

revenue depends on our ability to continue to offer models at the frontier of AI capability, which we may not be

able to do. Our ability or decision to remain at the frontier may also be affected by the safety and risk mitigation

measures we implement in developing and releasing our models. Our recent Run-Rate Revenue growth has also

been driven in part by rapid initial customer adoption and expansion often characteristic of an early-adoption

period and the nascency of the AI market that may not be sustainable, and we expect our Run-Rate Revenue

growth rate to decline over time, and it may decline significantly and more rapidly than we anticipate, as our

revenue base increases, as the market matures, and as a result of other factors. In addition, our Run-Rate

Revenue has included, and we expect will continue to include, amounts from customers that we subsequently

determine are using our models, platform, and applications in violation of our usage policy or commercial

terms. When we identify such usage, we seek to restrict or terminate the customer’s access; however, because

our detection, investigation, and enforcement take time, our Run-Rate Revenue as of any measurement date

includes amounts from customers that have not yet been restricted or terminated and whose revenue would not

be expected to recur following restriction or termination of their access. Our continued enforcement efforts may

reduce our revenue, Run-Rate Revenue, and growth rates in future periods. See “—Our results of operations

may fluctuate significantly on a period-to-period basis, including as a result of strategic investment decisions

and substantial compute-related expenditures, which could cause the market price of our Class A common

stock to decline.” Accordingly, our Run-Rate Revenue as of any measurement date is not indicative of historical

revenue and may not be indicative of our revenue for any future period.

The determination of the number of customers with $100,000 or more of revenue on a TTM basis is based on

our internal records and involves judgment, including in determining which accounts should be aggregated and

treated as belonging to the same organization. We apply our most current customer records in calculating this

metric, and our determination of which accounts belong to a single organization may change over time,

including as a result of acquisitions and account consolidations. We do not separately define or internally track

a category of “enterprise” customers, and our customers are not segmented or measured internally by reference

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to whether a given customer is an “enterprise.” Because spending $100,000 or more on our products is

generally characteristic of organizational rather than individual usage, we use the number of and revenue from

customers with $100,000 or more of revenue on a TTM basis as our measure of enterprise adoption and

engagement with Claude throughout this prospectus, including in references to “enterprise customers” and

“enterprise adoption.” As a result, this measure may not precisely correspond to the population of organizations

that would otherwise be characterized as enterprises, and may over- or understate that population.

Certain success rates and similar AI performance metrics with respect to Claude referenced in this prospectus

are measured using internal benchmarks developed and maintained by us. These benchmarks reflect our

proprietary testing methodology and are based on tasks, data sets, and evaluation criteria selected by us.

Performance results derived from these internal benchmarks may not be replicable by customers, researchers,

or other third parties who evaluate our models using different tasks, data sets, evaluation criteria, or computing

environments. Accordingly, such metrics may differ materially from performance outcomes experienced by any

particular customer or user in their specific deployment environment or use case, and should not be relied upon

as indicative of the results any customer or user will achieve. Because AI performance benchmarking

methodologies vary significantly across developers, such performance metrics as we measure them may also not

be comparable to similarly titled or analogous metrics reported by other AI developers, and direct comparison

of such metrics across companies may be misleading.

Investors should consider these metrics in light of the assumptions and processes used in calculating such

metrics and the limitations as a result thereof. In addition, our internal systems and tools have a number of

limitations, which could result in unexpected changes to our metrics, including the metrics we publicly disclose.

Further, certain of our operating metrics are based in part on data reported to us by our third-party partners. If

the internal systems and tools we use to track these metrics or if the data reported to us by our third-party

partners undercount or overcount performance, or contain algorithmic or other technical errors, the data we

report may not be accurate. While our operating metrics are based on what we believe to be reasonable

estimates for the applicable period of measurement, there are inherent challenges in these measurements. We

may also refine or change our methodology for tracking certain operating metrics from time to time, to the

extent practicable, including to improve overall accuracy and alignment with management’s view of business

and operating performance and as a result of acquisitions. Any of these updates may result in changes in certain

business and operating trends and may impact comparability of these metrics across periods. Investors should

not place undue reliance on these metrics as an indicator of our future or expected results. Moreover, these

metrics may differ from similarly titled metrics presented by other companies and may not be comparable to

such other metrics. See the sections titled “Management’s Discussion and Analysis of Financial Condition and

Results of Operations” and “Business” for more information regarding our operating metrics.

Our business is subject to an evolving and uncertain regulatory and political environment,

which could increase our costs, restrict our operations, or adversely affect demand for our

models, platform, and applications.

The development, deployment, and use of AI technologies are subject to rapidly evolving and increasingly

complex laws, regulations, and governmental scrutiny across multiple jurisdictions. Governments and

regulatory authorities in the United States and in other countries in which we operate or distribute our models,

platform, and applications have proposed, enacted, or are considering legislation, regulations, and guidance

relating to AI model development and deployment, data usage and privacy, transparency, safety, consumer

protection, content generation, intellectual property, cybersecurity, export controls, and competition. For

example, the EU AI Regulation 2024/1689 (“EU AI Act”), which came into force in August 2024 and will

become fully applicable following a transitional period, imposes a range of obligations on AI systems and

general-purpose AI models placed on the market or put into service in the EU, including transparency, risk

management, and governance requirements, and provides for significant penalties for non-compliance. In the

United States, the regulatory framework for AI remains fragmented and uncertain, with evolving federal policy

initiatives, continued debate regarding the scope and durability of executive actions, and a growing number of

state-level laws and proposals addressing the development and use of AI. For example, several U.S. states,

including New York and California, have passed AI safety laws. More generally, proposed legislation in the

United States contemplates more expansive governmental oversight of AI, including potential nationalization,

mandatory shutdown or discontinuation requirements for frontier AI systems or other strategic measures to

prevent or manage the development of artificial superintelligence. Further, in June 2026, the U.S. federal

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government issued an executive order establishing a voluntary framework for developers of frontier AI models

to engage with the government prior to the deployment of such AI technologies, directing federal agencies to

strengthen cyber defenses, and prioritizing enforcement against criminal misuse of AI; although that

framework is voluntary and does not establish a mandatory governmental licensing, preclearance, or permitting

requirement for the development or deployment of AI models, it reflects increasing federal attention to the

national security implications of frontier AI and the order may be followed by further executive or legislative

action. If executive or legislative action of this nature were enacted to regulate AI technologies, it could

constrain how we operate our business.

We have also advocated, and expect to continue to advocate, for regulation and oversight of frontier AI,

including industry-wide standards primarily relevant to the use of AI to accelerate AI development, so that AI

capabilities do not advance faster than the safety, alignment, and security practices needed to support them,

and we have proposed working with the U.S. government and other frontier AI developers to establish safety

standards. Regulatory or other measures of the kind we advocate, if adopted, would apply to us and could

increase our compliance burdens, limit our product development or deployment flexibility, affect how and

when we develop or release new models, or otherwise slow our growth. The effect that any such measures would

have on the rate at which AI capabilities advance, and on our business, is uncertain and would depend on the

specific requirements adopted and on the extent to which safety, alignment, and security practices advance

together with model capabilities. There is no assurance that policymakers will adopt the approaches we

support, and our advocacy has in the past drawn, and may continue to draw, criticism, heightened scrutiny, or

other challenges.

Regulatory approaches to AI also vary significantly by geography and may be influenced by local political,

economic, social, or environmental considerations. In some jurisdictions, public concern regarding the

potential displacement of labor by AI systems, the perceived societal impacts of automation, or the

environmental footprint associated with AI development and deployment, has led, or could lead, to restrictive

legislation or other governmental actions. In particular, to the extent the rate of job displacement rapidly

increases due to the adoption of AI or for related reasons, whether actual or perceived, governments or other

regulatory authorities may intervene to slow the rate of adoption of AI, restrict its use, or take other actions that

increase the cost of developing, deploying, or commercializing AI systems. Even in the absence of any legal or

regulatory requirements, we may from time to time voluntarily elect to take actions intended to ameliorate the

impact of such displacement. Any such actions would represent additional costs and expenditures for which we

may not receive a corresponding commercial benefit, and there can be no assurance that any such actions

would be effective in reducing displacement-related harms or in mitigating the associated reputational,

regulatory, or political risks.

Increasingly restrictive AI regulation in the United States and other western jurisdictions could enable

competitors operating in less regulated environments to innovate, scale, and deploy AI technologies more

rapidly, potentially allowing such competitors to become more advanced and pose greater competitive or

strategic threats over time. In particular, increasing strategic competition between the United States and China

in AI development may lead to divergent regulatory approaches, with the potential for the United States to

impose restrictions on AI companies’ interactions with Chinese entities or markets, and for China to impose

reciprocal measures that limit access to or demand for U.S.-origin AI models, platforms, and applications.

As a result of these and other regulatory developments, our business could be subject to a wide range of

regulatory limitations, obligations, or restrictions, including, among other things:

•limitations, conditions, or prohibitions on certain AI use cases, applications, or deployment contexts;

•requirements to modify, restrict, delay, or withdraw specific models, features, or functionalities in

particular markets or for specific customers; for example, in early 2026, the U.S. Department of War

suggested it could invoke the Defense Production Act to compel us to remove the limitations we have

placed on the use of our models for autonomous weapons and mass surveillance;

•heightened transparency, documentation, auditing, governance, or human-oversight obligations;

•restrictions on the collection, use, transfer, localization, or retention of data used to train or operate AI

systems, based on intellectual property, privacy, or other frameworks;

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•mandated safety, risk-management, or evaluation frameworks, certifications, or approvals, including

requirements for independent, third-party review or approval prior to model development, training, or

release; for example, in September 2026, a state attorney general asked a court, in pending litigation

alleging harm to minors, to enjoin an AI company from developing new AI models without

independent, third-party guardrails and approval;

•restrictions on data center development or expansion, including permitting, zoning, or limits on energy

or water usage;

•heightened energy efficiency, sustainability, or environmental compliance requirements;

•limitations on cross-border deployment, access, or commercialization of AI models, including through

export controls, national security determinations, or other governmental measures that could restrict

our ability to sell our models, platform, and applications in certain markets or to certain customers; for

example, in June 2026, the U.S. Department of Commerce imposed worldwide export restrictions on

our Fable 5 and Mythos 5 models, which were subsequently lifted after we updated our safeguards, and

other models may be subject to these or similar export restrictions in the future; for more information,

see the section titled “—Governmental trade controls, including export and import controls, sanctions,

customs requirements, and related regimes, could subject us to liability or loss of contracting privileges

or limit our ability to compete in certain markets.”;

•AI-specific taxes, fees, reporting obligations, or other financial burdens; or

•outright bans or moratoria on activities material to our business or the businesses of our customers

and partners.

Because AI regulation is developing rapidly and in a fragmented manner, including as a result of political

considerations, public sentiment, and geopolitical dynamics, we will not be able to fully anticipate how existing

laws will be interpreted or enforced, how new legal frameworks will evolve, or whether regulatory regimes

across jurisdictions will converge or diverge over time. Compliance with new or changing requirements may

require substantial investment in research and development, compliance systems, operational processes, or

localized offerings, and we may need to adjust or limit our activities in certain jurisdictions to address

conflicting or inconsistent legal obligations. In addition, regulatory actions affecting our customers or partners,

including restrictions on their ability to develop, deploy, or commercialize AI-enabled models, platforms, or

applications, could indirectly reduce demand for our models, platform, and applications. Any failure, or

perceived failure, to comply with applicable laws and regulations, or any significant increase in the cost or

complexity of compliance, could result in litigation, enforcement actions, penalties, reputational harm, delayed

or reduced adoption of our offerings, or other adverse effects on our business, financial condition, and results of

operations.

Additionally, as AI systems become more sophisticated, emerging debates regarding whether AI systems

possess or could develop forms of sentience or moral status may lead to regulatory requirements, public

pressure, or advocacy efforts that could constrain how we develop, train, deploy, or modify our models, increase

our costs, or affect our reputation, regardless of the ultimate resolution of these philosophical and scientific

questions. In addition, given our focus on developing frontier AI, and the way we approach model sentience and

moral status, we may face heightened scrutiny or pressure in connection with these debates and could elect to

adopt policies, safeguards, or limitations regarding model development, deployment, or modification that go

beyond existing legal requirements, which could constrain our operations, increase costs, or limit the

commercial potential of our models, platform, and applications. If we are unable to manage the foregoing risks,

our business, financial condition, and results of operations could be adversely affected.

Our sales to government entities and highly regulated organizations are subject to challenges

and risks.

Our customers include U.S. and non-U.S. government agencies. Revenue from government agency contracts

represented, in aggregate, approximately 1% of our revenue in each of the periods presented in this prospectus;

however, the risks described below, including the governmental actions described in this risk factor, are not

limited to revenue generated directly from government agencies and could affect our relationships with

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commercial customers and partners. Sales to government agencies involve additional risks, including, but not

limited to:

•changes in government fiscal or procurement policies, or decreases in government funding available

for procurement of goods and services generally, or for our federal government contracts specifically;

•changes in government programs or applicable requirements;

•our ability to agree on commercial terms with government entities, including with respect to the

permitted use of our models, platform, and applications;

•restrictions in the grant of personnel security clearances to our employees;

•our ability to maintain facility clearances required to perform on classified contracts for U.S.

government and non-U.S. government agencies, as applicable;

•changes in the political environment, including before or after a change to the leadership within the

government administration, and any resulting uncertainty or changes in policy or priorities and

resultant funding;

•changes in the government’s attitude towards us as a company or our technology;

•appeals, disputes, or litigation relating to government procurement, including but not limited to bid

protests by unsuccessful bidders on potential or actual awards of contracts to us or our partners by the

government;

•the adoption of new laws or regulations or changes to existing laws or regulations;

•budgetary constraints, reductions in government spending, operating under continuing resolutions,

disruptions from government shutdowns, or similar measures and constraints imposed by any lapses

in appropriations for the federal government or certain of its departments and agencies;

•influence by, or competition from, third parties with respect to pending, new, or existing contracts with

government customers;

•changes in legal obligations or political or social attitudes with respect to security or privacy issues;

•potential delays or changes in the government appropriations or procurement processes, including as a

result of events such as war, incidents of terrorism, natural disasters, and public health concerns; and

•increased or unexpected costs or unanticipated delays caused by other factors outside of our control.

Any such event or activity, among others, could cause governments and government agencies to delay, pause, or

cancel contracts or seek to modify their contracts, or refrain from entering into contracts with us or purchasing

our models, platform, and applications in the future, undermine our ability to pursue future contracts, damage

our relationships with partners and customers who also sell models, platforms, or applications to governments,

or reduce the size or timing of payment with respect to our services to or purchases from existing or new

government customers. Any of the foregoing could have an adverse effect on our prospects, business, financial

condition, and results of operations.

For example, in February 2026, in response to our publicly stated position that our technology should not be

used for mass domestic surveillance or fully autonomous weapons, the President of the United States stated

that he had directed that all federal executive agencies cease using our technology. At the same time, the

Secretary of War directed the Department of War to designate us as a “supply-chain risk to national security”

and stated that “effective immediately, no contractor, supplier, or partner that does business with the United

States military may conduct any commercial activity” with us. On March 4, 2026, the Department of War sent

us two letters—one pursuant to 10 U.S.C. § 3252 and the other pursuant to Section 4713 of the Federal

Acquisition Supply Chain Security Act (“FASCSA”)—asserting that our models, platform, and applications

present a supply-chain risk. These actions referenced above are defined herein as “Challenged Actions.” We

vigorously challenged these Challenged Actions in Anthropic PBC v. Department of War, et al. (N.D. Cal.) and

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Anthropic PBC v. Department of War, et al. (D.C. Cir.). After first obtaining an order from the United States

District Court for the Northern District of California that preliminarily enjoined the Department of War’s

directive and Section 3252 supply-chain risk designation of us and preliminarily enjoined the other defendant

agencies from implementing the Presidential directive until final resolution of the lawsuit, we subsequently, on

August 27, 2026, obtained an order from the United States District Court for the Northern District of California

that largely granted summary judgment in our favor. The court ruled that the Challenged Actions were

retaliatory acts meant to punish us for speech protected under the First Amendment to the United States

Constitution and violated our rights under the Due Process Clause of the Fifth Amendment to the United States

Constitution. The court also held that the Secretary of War’s actions, particularly with respect to 10 U.S.C. §

3252, violated the Administrative Procedure Act because they were in excess of statutory authority, contrary to

law, and arbitrary and capricious. The court entered final judgment largely in our favor. The defendants filed a

notice of appeal of the preliminary injunction. The D.C. Circuit Court of Appeals, however, denied our motion to

stay the Secretary of War’s Section 4713 designation of us as a supply-chain risk pending review on the merits.

On September 25, 2026, in a 2-1 split decision, the D.C. Circuit Court of Appeals denied our petition for review,

ruling that the Department of War’s Section 4713 supply-chain risk designation was proper, and that our rights

under the First Amendment and Due Process Clause of the Fifth Amendment were not violated. We filed a

petition for rehearing en banc asking the full D.C. Circuit to review the panel’s decision. We cannot predict the

ultimate outcome of these lawsuits. While we continue to work with government agencies, we cannot be certain

that the resolution of these lawsuits will not adversely affect our ability to sell to government agencies and other

customers that sell products and services to the U.S. government, and in turn adversely affect our business,

financial condition, and results of operations.

Further, in June 2026, the U.S. Department of Commerce imposed worldwide export restrictions on our Fable

5 and Mythos 5 models, which we disabled for all customers until those restrictions were lifted, as described in

the section titled “—Governmental trade controls, including export and import controls, sanctions, customs

requirements, and related regimes, could subject us to liability or loss of contracting privileges or limit our

ability to compete in certain markets.” Similar restrictions could be imposed again in the future.

Each of the foregoing may result in significant reputational harm, including adverse media coverage, public

scrutiny, and negative perceptions among existing and prospective customers, partners, employees, and

investors, regardless of the ultimate outcome of the litigation. Such perceptions may lead customers, including

commercial enterprises and international customers, to delay or forgo purchasing our models, platform, and

applications, or to impose additional diligence, contractual restrictions, or termination rights in connection

with engagements with us. Further, these developments may create uncertainty in the broader market

regarding our long-term ability to operate in certain sectors, which could result in increased volatility in

demand for our models, platform, and applications, reduced willingness of counterparties to enter into long-

term or strategic arrangements with us, and fluctuations in investor sentiment, any of which could adversely

affect our business, financial condition, and results of operations.

The bidding process for government contracts can be highly competitive, expensive, and time-consuming, often

requiring significant upfront time and expense without any assurance that these efforts will generate revenue.

Government agencies often undertake a significant evaluation process that results in a lengthy sales cycle. Some

contracts with government agencies are structured in phases or include options, where each phase is subject to

satisfaction of certain conditions and where the exercise of options is discretionary. As a result, the actual scope

of work performed pursuant to any such contracts, in addition to related contract revenue, could be less than

total contract value. In addition, product purchases by such organizations are frequently subject to budget

constraints, multiple approvals, and unanticipated administrative, processing, and other delays. All of these

factors can add further risk to business conducted with these customers and could lead to lower revenue results

than originally anticipated.

We also must comply with both local and international laws and regulations relating to the formation,

administration, and performance of contracts. Contracts with government agencies are subject to extensive,

evolving, and sometimes complex regulations which provide public sector customers rights, many of which are

not typically found in commercial contracts. For example, government contracts generally include the ability of

government agencies to terminate for convenience, which if exercised, would result in a lower contract value

and lower than anticipated revenue generated by such arrangement. Any changes to the government

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regulations applicable to government contracts could affect our ability to enter into, or the profitability of,

contracts with government entities.

Our subsidiary, Anthropic Public Institutions, LLC, is required to maintain a facility security clearance to

perform on classified contracts for the U.S. federal government and must comply with National Industrial

Security Program requirements. Failure to comply with these requirements may result in Anthropic Public

Institutions, LLC’s facility clearance being revoked. To the extent Anthropic Public Institutions, LLC, is not able

to maintain its facility security clearance, we may not be able to bid on or win new classified contracts, and

existing contracts requiring a facility security clearance could be terminated, either of which could have an

adverse impact on our business, financial condition, and results of operations.

Contracts with government agencies are also subject to audits and reviews of contractors’ administrative

processes and other contract-related compliance obligations. Breaches of government contracts, failure to

comply with applicable regulations, failure to obtain and maintain required facility and/or security clearances,

or unfavorable findings from government audits or reviews could result in contract terminations, reputational

harm, or other adverse consequences, including ineligibility to sell to government agencies in the future,

government refusal to continue buying our subscriptions, or fines or civil or criminal liability, which could

adversely affect our results of operations.

Our reliance on a limited number of CSPs and suppliers, some of which have strategic and

investment relationships with us and are our customers, creates complex dynamics that could

give rise to conflicts of interest and adversely affect our access to compute.

We rely on a limited number of CSPs—Amazon.com, Inc. (together with its affiliates, “Amazon”), Google, and

Microsoft Corporation (“Microsoft”)—and suppliers, such as Broadcom, for compute and critical components of

our compute infrastructure. These relationships are governed by contractual arrangements that, while

providing us with significant committed compute, also create dependencies and potential vulnerabilities. These

CSPs may experience service outages, security incidents, or capacity constraints that affect our operations. The

terms of our arrangements, including pricing, compute commitments, and service levels, are subject to

negotiation upon renewal, and we may be unable to secure renewals on terms as favorable as our current

arrangements. Migrating workloads to alternative providers would be costly, time-consuming, and

operationally complex, and may not be feasible within timeframes that would avoid material disruption to our

model development roadmap or our ability to serve customers. The engineering investment required to

maintain the performance of our unified compute platform across new hardware environments means that any

such migration could degrade our compute efficiency, increasing the compute and infrastructure costs required

to support a given level of business activity during and following any such migration period.

Our relationships with these CSPs are multifaceted and complex. Amazon, Google, and Microsoft, through their

respective affiliates, have made significant equity investments in our company. At the same time, they may have

made, and may in the future make, equity investments in, provide financing to, or otherwise support companies

whose models, platforms, or applications compete with ours. These CSPs are also our customers, purchasing

our intelligence service for internal use or for their own products and services. Their purchasing decisions may

be influenced by their own competing offerings, which could affect their demand for our intelligence service.

Additionally, Amazon, Google, and Microsoft are among the largest technology companies in the world, each

with substantial AI research and development programs, AI-powered models, platforms, and applications that

compete with ours, and strategic interests that may not be fully aligned with our own. Amazon, Google, and

Microsoft each offer AI services and develop and deploy competing AI models through their respective cloud

platforms. We make certain of our models available through these cloud platforms, and our distribution

relationships with Amazon, Google, and Microsoft generate revenue for us, but they also create dependencies,

give them visibility into our pricing and commercial terms across the platforms they operate, and may influence

their incentives regarding pricing, compute allocation, service quality, sales prioritization, and compensation

structures. To the extent these CSPs promote, integrate, prioritize, or provide customer access to our models,

platform, and applications on terms that are less favorable than those applicable to their own competing

offerings or to the offerings of other companies, including with respect to pricing, commercial terms, product

placement, integration, or access to compute or sales incentives, our competitive position, customer adoption,

and business results could be adversely affected.

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Our relationships with our strategic partners—whether with these CSPs, who simultaneously serve as our

investors, customers, distribution partners, and competitors, or with Broadcom, which simultaneously serves as

a supplier and lessor—create potential conflicts of interest that are difficult to fully anticipate or mitigate. These

CSPs may prioritize their own compute needs or those of their other customers, including competitors in which

they have invested, may gain insight into our operations and compute requirements through their roles as

providers that could inform their competitive strategies, or may make business decisions regarding their

platforms that disadvantage our models, platform, and applications relative to their own offerings or the

offerings of other companies they support. Similarly, Broadcom may prioritize the supply of AI accelerators and

infrastructure capacity to other customers, alter the terms of our equipment lease or the operation of our

dedicated facilities, or make decisions regarding the availability or pricing of hardware that adversely affect our

access to the compute infrastructure they provide. Any deterioration in these relationships, or any decision by

Amazon, Google, Microsoft, or Broadcom to reduce their support for our models, platform, and applications or

limit our access to compute, could adversely affect our business. In addition, such relationships, including any

exclusive or preferential arrangements, investment ties, bundling of services, or cooperative initiatives, have

attracted and may in the future attract antitrust or competition law scrutiny from regulators and private

plaintiffs in the United States or other non-U.S. jurisdictions, and any resulting investigations, enforcement

actions, or required modifications to our business arrangements could be costly, distracting, and harmful to our

business.

If we are unable to manage the foregoing risks, our business, financial condition, and results of operations

could be adversely affected.

We are pursuing initiatives to develop our own data center infrastructure, which involves

significant capital commitments, operational complexities, and execution risks that could

adversely affect our business, financial condition, and results of operations.

To help reduce our dependence on CSPs, address constraints on available compute, and secure access to

compute at the scale necessary for frontier model development, we are pursuing initiatives to develop our own

dedicated on-premise data center infrastructure. These efforts include long-term leases and partnerships with

third-party partners to procure the underlying real estate, power, and data center facilities while we lease

capacity in those facilities and contract with specialized third-party operators for ongoing facility management.

We also procure certain compute and infrastructure equipment directly and operate them in dedicated data

center facilities leased and operated on our behalf, to our specification. For example, under the 2026 Lease

Arrangement, the rent payments over the five-year equipment lease are equal to an aggregate of approximately

$125.2 billion excluding interest, with rent payable in quarterly installments and payment obligations typically

commencing upon AI infrastructure equipment becoming “ready for service” at the applicable data center

facility. The 2026 Lease Arrangement is non-cancelable by the parties to such agreement during the applicable

lease period except in the case of a default. In addition, we deposited cash into a restricted account in April

2026 for the benefit of Broadcom to secure compute capacity, which amount may be released or applied toward

obligations under the lease depending on the satisfaction of specified conditions. Under certain circumstances,

we may be required to place additional cash into this restricted account for future amounts due under the 2026

Lease Arrangement. Upon the occurrence of certain uncured events of default, such as certain payment or

performance failures pursuant to the terms of the 2026 Lease Arrangement, a substantial portion of our

obligations under the 2026 Lease Arrangement would be accelerated and, while we have access to multiple

sources of capital and are not dependent on the potential financing capacity provided in the Infrastructure

Partner 2026 NPA that we entered into in connection with the 2026 Lease Arrangement, we may not be

permitted to elect to issue the convertible promissory notes under the Infrastructure Partner 2026 NPA to

finance such obligations. Furthermore, we may in the future continue to directly procure such data center

infrastructure and we may also undertake other efforts to build out our own compute and infrastructure and

invest more deeply in the compute supply chain, which could result in significantly higher upfront costs and

adversely affect our financial condition and results of operations. For more information about such lease

arrangements, see the sections titled “Management’s Discussion and Analysis of Financial Condition and

Results of Operations—Liquidity and Capital Resources—Contractual Obligations” and “—If our actual compute

requirements differ materially from our projections, we may fail to secure sufficient compute to meet our needs

or we may be committed to excess compute that remains underutilized.” We have limited experience in

managing such data center infrastructure projects at scale. Successfully executing on these data center

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infrastructure initiatives requires us to recruit personnel with relevant experience and manage complex multi-

year deployment timelines and relationships with developers, contractors, and service providers.

As we continue to build out our own compute and infrastructure and further vertically integrate across the

compute supply chain, these multi-party structures will become more prevalent and will expose us to a

structural timing and liquidity risk in our payment obligations that differs from our historical compute

arrangements. Historically, we have generally obtained compute from a limited number of CSPs under

arrangements in which our compute and infrastructure expenses are paid as compute becomes available to us.

In the future, we expect we will increasingly enter into separate arrangements with a greater number of

different counterparties, each responsible for discrete services or inputs across the compute supply chain.

Under many of these arrangements, we may be obligated to pay a counterparty once it performs its discrete

obligation, even if delays or failures by others prevent us from assembling those discrete services or inputs into

usable compute we can deploy to generate revenue. In addition, counterparties may deliver their services or

inputs later than scheduled, or may fail to deliver them at all, and any such delay or non-delivery by a single

counterparty could postpone or prevent our deployment of the associated compute. As a result, we could incur

significant cash outflows without obtaining usable compute on a timely basis, which could adversely affect our

liquidity, financial condition, and results of operations.

Certain of our data center infrastructure arrangements involve complex multi-party structures in which chips

are procured from or through our CSPs, leased to us by third-party financing entities, installed in data center

facilities procured by or through other third-party partners, and operated by yet another set of third-party

service providers. The complexity of these arrangements increases execution risk, as delays or failures by any

participant in the chain could affect the availability or performance of the resulting compute.

In addition, to meet the substantial energy demands of large-scale AI workloads, we have entered into, and may

in the future enter into, arrangements involving dedicated power generation assets and/or the development,

operation, or control of power stations or other energy infrastructure. Such arrangements expose us to new

operational, regulatory, and environmental liabilities, and require expertise and capabilities that differ from our

core competencies. Successfully executing on these power infrastructure projects requires us to recruit

personnel with relevant experience and manage complex multi-year deployment timelines and relationships

with developers, contractors, service providers, and regulators, including aligning project completion schedules

with the data centers such projects are expected to serve in order to avoid timing delays that constrain our

ability to utilize this compute and to generate revenue and recoup costs from such investments.

Deployment of our data center and power infrastructure projects involves execution risks, including delays due

to permitting issues, change in law, force majeure, lack of network connectivity between facilities, supply chain

disruptions, labor shortages, or contractor performance; cost overruns due to equipment pricing changes,

design modifications, or unanticipated requirements; and technical risks that facilities may not perform as

specified or achieve expected reliability or efficiency levels. Certain of our arrangements are also subject to

conditions precedent that must be satisfied before construction can commence, and completion guarantees that

may terminate upon a lender foreclosure before construction is complete, leaving us without contractual

recourse to compel completion. Certain of these arrangements also depend on the continued performance of

credit support provided by a third party that is also a competitor, the loss or impairment of which could

jeopardize the underlying arrangements. Such credit support provided to third-party data center developers or

hardware providers, from which we derive no direct contractual rights or obligations, may also affect the

availability and cost of data center capacity and hardware generally. Additionally, new tariffs or import fees

enacted after the effective date of certain arrangements may be passed through to us as additional costs. Any

delay in or limitation on the amount of compute delivered to us could adversely affect our business.

The capital-intensive and long-term nature of leasing and equipping data center capacity creates financial risk,

as large upfront investments and long-term payment commitments must be made months before facilities

become fully operational. If our compute requirements or technology needs change, we may find ourselves with

leased or dedicated infrastructure that is poorly suited to our actual needs, and technological changes in AI

hardware or training methodologies could render such infrastructure less efficient than newer alternatives.

Unlike CSP arrangements where compute can be adjusted relatively dynamically, long-term leases, reserved

compute, and dedicated infrastructure investments are much less flexible and create long-term financial

obligations regardless of whether the capacity continues to meet our needs. For example, certain of our

dedicated power and data center infrastructure arrangements have initial terms of 20 years with annual

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escalators and include take-or-pay compute payment obligations and uncapped fuel cost pass-throughs that

apply for the duration of the term regardless of actual utilization.

Our increasing efforts to build out our compute and infrastructure require substantial capital expenditures and

are changing the cash flow profile of our business. Whereas the compute purchased through our CSP

arrangements is generally paid as the compute becomes available to us, we expect an increasing portion of our

compute and infrastructure investment to take the form of capital expenditures and other commitments,

including lease obligations, that require significant upfront payments well in advance of the related compute

becoming operational. Our existing commitments are substantial, and we expect our capital expenditures to

increase significantly as we continue to expand our compute and infrastructure build-out. See the section titled

“Management’s Discussion and Analysis of Financial Condition and Results of Operations—Liquidity and

Capital Resources” for more information. As a result, we expect these investments to result in significant net

cash used in operating and investing activities for the foreseeable future, and our net cash used in these

activities may increase regardless of whether our financial performance improves. The magnitude and timing of

these investments are inherently uncertain and may change materially over short periods, including as a result

of decisions to accelerate or expand our build-out, and such changes could rapidly and significantly alter our

expected results of operations and cash flows for a given period. If our cash flows from operations and available

capital are insufficient to fund these investments, we may be required to raise additional capital on unfavorable

terms or to reduce, defer, or forgo planned investments, any of which could adversely affect our business,

financial condition, and results of operations.

If we are unable to successfully execute on our data center infrastructure initiatives, experience significant

delays or cost overruns, or find that the infrastructure we lease, deploy, or build does not meet our evolving

needs, we may not realize the expected benefits of these investments, which could adversely affect our business,

financial condition, and results of operations.

We may not successfully build, expand, and deploy our sales and marketing organization in a

timely manner, or we may not successfully hire, retain, train, and motivate our sales

personnel.

We have grown, and will continue to grow, our direct sales force. Whether we are able to increase our sales to

existing customers, identify and engage new customers, and enter new U.S. and non-U.S. markets, each with a

focus on broadening use of our models, platform, and applications across departments and entire

organizations, will depend, among other things, on our ability to successfully test new market segments and

customer types, validate product-market fit through early customer engagement, timely and effectively scale

our sales motions, and adapt quickly when market conditions change. We have limited experience building,

managing, and scaling a direct sales force. We have dedicated and plan to continue to dedicate significant

resources to sales and marketing programs and to expand our sales and marketing capabilities to target

potential customers and achieve broader market adoption of our models, platform, and applications, but there

is no guarantee that we will be successful in attracting and maintaining additional customers. Moreover,

identifying, recruiting, training, and managing sales personnel requires significant time, expense, and attention,

including from our senior management and other key personnel, as there is significant competition for sales

personnel with the skills and technical knowledge that we require, including the ability to understand and

communicate complex and evolving AI use cases, regulatory considerations, customer risk sensitivities, and

rapidly changing product capabilities. These challenges are particularly acute for international expansion,

which requires qualified personnel with international experience, language skills, cultural competencies in the

geographic markets which we target, and an aligned mission-oriented culture. If we are unable to successfully

manage the foregoing risks, our prospects, business, financial condition, and results of operations could be

adversely affected.

We periodically make adjustments to our sales and marketing organization in response to market

opportunities, product introductions or enhancements, acquisitions, and other internal and external

considerations. Any future sales and marketing organization changes may result in a temporary reduction of

productivity, which could negatively affect our rate of growth. In addition, any significant change to the way we

structure and implement the compensation of our sales and marketing organization may be disruptive or may

not be effective and may adversely affect our revenue growth. If we are unable to attract, hire, develop, retain,

and motivate qualified sales and marketing personnel, if our new sales personnel are unable to achieve

sufficient sales productivity levels in a reasonable period of time or at all, if our marketing programs are not

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effective, or if we are unable to effectively build, expand, and manage our sales organization and operations, our

sales and revenue may grow more slowly than expected or decline, and our prospects, business, financial

condition, and results of operations could be adversely affected.

We have a limited history under our current go-to-market strategy, and our efforts to scale

and evolve our customer acquisition, engagement, and retention model may not be successful.

We have a limited history selling consumption-based access and subscriptions to our models, platform, and

applications under our current business model, and we are continuing to scale our operations and go-to-market

strategy. Our future success depends in part on our ability to continue attracting, onboarding, expanding, and

retaining customers under this model, including determining whether, when, and how to target, develop, and

deepen relationships with individual customers over time. Scaling our operations, including hiring, training,

and retaining additional sales, sales engineering, and customer-facing personnel, and evolving our go-to-

market strategy may take more time and require more effort than anticipated, and the results of these efforts

are difficult to predict. Our business and operating models have not been fully proven, and our limited history

with our current approach makes it difficult to evaluate our prospects, plan for future growth, and forecast our

results of operations.

In addition, our strategy and customer mix expose us to competitive and execution risks as the AI market

continues to evolve. We have organized our research priorities, our product roadmap, and our go-to-market and

Applied AI teams around enterprise use cases, and much of the diffusion of Claude to date has been organic—

driven by individual users, including software developers and prosumers, who adopt Claude and often serve as

internal champions for its broader adoption within their organizations—rather than by a large direct sales

organization. This approach has allowed us to scale with a smaller team relative to other large enterprise

technology companies, but it assumes that our applications and distribution will be sufficient to deliver the

capabilities of our models to customers and that individual adoption will continue to translate into

organizational adoption and expansion. Companies with stronger consumer-facing businesses, larger consumer

user bases, more established brands, broader distribution, or deeper customer relationships may choose to

increase their focus on enterprise customers or enterprise use cases and could leverage their scale, resources,

and market presence to compete more effectively with us. In particular, if such competitors capture the

individual users from whom our enterprise adoption often originates, whether through their consumer

applications, by integrating AI functionality into products those users already use, or otherwise, our pipeline of

enterprise opportunities could be reduced in ways that a direct sales organization of our current scale may not

be able to offset. Building a substantially larger sales organization, or shifting investment toward consumer and

application-layer products to compete for those users, would require significant time and resources beyond our

current plans and would involve the trade-offs described in the section titled “—We face intense competition,

and if we are unable to compete effectively, our business, financial condition, and results of operations could be

adversely affected.” Because we have a limited operating history with our current business model and go-to-

market strategy, we have less experience predicting customer adoption, expansion, and retention patterns, and

customers may be slower than expected to adopt our models, platform, and applications or expand usage. Any

failure to successfully scale our operations or effectively execute on and refine our go-to-market strategy could

adversely affect our business, financial condition, and results of operations.

Sales to enterprise customers involve complexities and risks that could adversely affect our

business, financial condition, and results of operations.

We derive a large portion of our revenue from sales to enterprise customers. Our ability to attract, retain, and

expand relationships with enterprise customers depends in significant part on our ability to meet their

generally heightened operational, technical, security, reliability, and compliance requirements. Enterprises

typically expect high levels of system uptime, performance consistency, data security, auditability, internal

controls, and scalability, as well as robust support and service levels. These requirements may be heightened for

our agentic offerings, where enterprise customers may require detailed logs of each action taken by an

autonomous agent within their environment, including the agent’s reasoning, tool invocations, and interactions

with external systems. Any inability on our part to provide such logs at the level of granularity customers

require could limit adoption of our agentic offerings by enterprises or result in customer attrition. If we are

unable to deliver models, platforms, and applications that satisfy these enterprise-grade requirements, or if we

experience outages, performance degradation, security incidents, or other operational failures, our ability to

retain and expand with enterprise customers could be adversely affected. In particular, as we deploy our Virtual

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Collaborators, like Claude Code and Claude Cowork, within enterprise environments, these systems will require

broad permissions and deep integrations with customers’ internal tools, data, and workflows in order to operate

effectively. The scope of access required for extended autonomous operation within enterprise environments

increases the potential consequences of any security incident, unauthorized action, or system error, and

customers may be reluctant to grant the level of access necessary for these systems to operate as designed if

they are unable to satisfy themselves regarding the security, reliability, and controllability of such systems.

Our sales efforts targeted at enterprise customers also involve risks and challenges that may not be present, or

that are present to a lesser extent, with sales to individuals or smaller organizations. These customers typically

have longer decision-making cycles, require greater security, functionality, and scalability, expect a broader

range of services, demand that providers take on a larger share of risks, require higher levels of customer

service and support, and expect greater payment flexibility from vendors. We are often required to spend

significant time and resources to familiarize potential customers with the value proposition of our models,

platform, and applications, and this process can take substantially longer with enterprise customers.

Enterprises may also require extensive customization, integration support, and vendor evaluations and demand

more features than we currently offer or than we can deliver within their expected timeframes, including

enterprise-grade functionality such as audit logs, compliance features, security controls, and monitoring tools,

which may require us to make additional investments in product development or services capabilities, before

committing to a purchase. As a result of these factors, sales opportunities with enterprises require us to devote

greater sales and administrative support and professional services resources to each such enterprise customer,

which increases our costs, lengthens our sales cycle, and diverts our sales and customer service resources to a

smaller number of enterprise customers. We may spend substantial time, effort, and money in our sales efforts

without successfully producing any sales. In addition, many enterprise customers procure and deploy our

models, platform, and applications through third-party CSP marketplaces, which can introduce additional

complexity into the sales and deployment process, including reliance on the CSPs’ procurement, security, and

billing workflows and coordination with multiple counterparties. As a result, our ability to attract, retain, and

expand relationships with enterprise customers may also depend in part on factors outside of our direct control,

including the policies, priorities, and operational requirements of such CSPs.

A number of factors influence the length and variability of our sales cycle. The need to educate potential

customers about the uses and benefits of our models, platform, and applications, the discretionary nature of

purchasing and budget cycles, competitive evaluation and purchasing approval processes, procurement

requirements, legal review of contract terms, and internal budget authorization procedures all contribute to

sales cycle variability. The length of our sales cycle, from identification of the opportunity to deal closure, may

vary significantly from customer to customer. Sales to enterprises typically take longer to complete than sales to

individuals or smaller organizations.

A meaningful portion of our revenue is attributable to a relatively small number of such enterprise customer

relationships, which increases the variability of our financial results. Our revenue in any given quarter could be

substantially affected if these customers decide to significantly reduce their spend.

Enterprises may have deep existing relationships with our competitors for models, platforms, and applications

we do not offer, or relationships with others in the ecosystem, which may delay our sales process or cause us to

not succeed with such enterprises.

Enterprise customers are particularly sensitive to our ability to maintain the uptime of our models, platform,

and applications, and any degradation in uptime could adversely affect our ability to retain and expand with our

enterprise customers. Sustaining the uptime, performance, and scale that enterprise customers expect can place

additional demands on our overall compute, and any failure of our capacity management systems to direct

sufficient compute to support such demands could adversely affect our ability to serve all workloads. For more

information about the foregoing, see the section titled “—If we fail to manage our technical operations

infrastructure, or experience service outages, interruptions, or delays in the deployment of our models,

platform, and applications, our results of operations may be adversely affected.”

Our sales strategy for these enterprise customers also depends on our ability to build and maintain an effective

sales organization. If we fail to effectively manage these risks associated with sales to enterprises, our business,

financial condition, and results of operations could be adversely affected. For additional discussion of our

personnel related risks, see the section titled “—We may not successfully build, expand, and deploy our sales

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and marketing organization in a timely manner, or we may not successfully hire, retain, train, and motivate our

sales personnel.”

If our marketing strategies, such as our free trials and free tiers, fail to generate the benefits

we expect, or if their costs exceed those benefits, our ability to grow our revenue could be

adversely affected.

A portion of our users access our models, platform, and applications through free tiers or promotional offerings,

and we seek to convert these users into paying customers over time. We may not always be successful in doing

so, as free users may be satisfied with the limited functionality available in free tiers, may not have budgets to

support paid subscriptions, or may choose to use our free offerings indefinitely without converting to paid

plans. The availability of free tiers may cannibalize potential paid subscriptions, as some users who would have

otherwise paid for our services may instead rely exclusively on free access. Additionally, providing free access to

our models, platform, and applications involves costs, including compute and infrastructure, customer support,

and other operational costs. In addition, we offer free access in significant part to build awareness of, familiarity

with, and engagement with our products, and as a means of reaching individuals engaged in knowledge work

outside of a business or organizational context. However, these benefits are inherently difficult to measure, free

usage may not generate the awareness or advocacy we expect, and individual adoption of our products may not

translate into organizational adoption or expansion. See the section titled “—We have a limited history under

our current go-to-market strategy, and our efforts to scale and evolve our customer acquisition, engagement,

and retention model may not be successful.” If the costs of supporting free users exceed the value we derive

from their eventual conversion or other benefits such as network effects and word-of-mouth referrals, our

business, financial condition, and results of operations could be adversely affected.

If we fail to maintain high-quality customer support, our ability to retain and expand

customers could suffer, which may adversely affect our prospects, business, financial

condition, and results of operations.

Our customers rely on our customer support services to resolve issues and realize the full benefits that our

models, platform, and applications provide. In order to deliver high-quality customer support and engagement,

we must successfully assist our customers in deploying and continuing to use our models, platform, and

applications, resolve performance issues, discover and deploy our models, platform, and applications in new

use cases, provide hands-on technical implementation, customization and solution engineering support,

provide training and guidance to help customers effectively adopt and scale their use of our models, platform,

and applications, address interoperability challenges, and respond to security threats and cyberattacks and

performance and reliability problems that may arise from time to time. The importance of our support function

will increase as we expand our business and pursue new customers. Many enterprises have complex internal

systems and require high levels of focused support to fully realize the benefits of our models, platform, and

applications. If we do not help our customers quickly resolve issues and provide effective ongoing support and

enablement, or a market perception develops that we do not maintain high-quality customer support and

experience, our ability to maintain and expand our subscriptions to existing and new customers could suffer,

particularly with respect to our enterprise customers.

In addition, our growth model depends significantly on driving deeper adoption and expanded use cases within

our existing customer base. If we are unable to effectively provide support and integration efforts that enable

customers to identify, deploy, and scale additional high-value use cases, demonstrate measurable return on

investment, or integrate our models, platform, and applications into their core workflows, customers may limit

usage, fail to renew at expected levels, or reduce their spend, which could materially slow our revenue growth.

Further, there can be no assurance that we will be able to hire sufficient support personnel as and when needed,

particularly if our sales exceed our internal forecasts. We expect to continue to increase our customer base, and

that growth may put additional pressure on our customer support teams, which may require additional

personnel to respond to customer demand. We may be unable to respond quickly enough to accommodate

short-term increases in customer demand for services. To the extent that we are unsuccessful in hiring,

training, and retaining adequate support personnel, our ability to provide high-quality and timely support to

our customers will be negatively impacted, and our customers’ satisfaction and their use and subscription of our

models, platform, and applications could be adversely affected.

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In addition, as we continue to grow our operations and reach a larger and increasingly global customer base, we

need to be able to provide efficient services that meet our customers’ needs globally at scale, and our customer

support teams may face additional challenges, including those associated with delivering support, training, and

documentation in languages other than English and providing services across expanded time-zones. If we are

unable to manage the foregoing risks, our business, financial condition, and results of operations could be

adversely affected.

Our product and investment decisions may not prioritize short-term financial results and may

not align with investor expectations or preferences, which could adversely affect the market

price of our Class A common stock.

Our product and investment decisions are informed in large part by our commitment to AI safety, expanding

our models, platform, and applications securely and responsibly, and providing high quality customer support,

all of which, in addition to our status as a PBC, may not necessarily maximize short term financial results. While

we generally believe that our product and investment strategy will improve our long-term financial results, we

regularly make product and investment decisions that may or may be perceived to negatively impact our short-

term revenue or ability to achieve and sustain profitability. For example, we have in the past delayed the release

of new models or features, limited their availability, imposed usage restrictions, or constrained certain

functionality until we determined that sufficient safety testing, evaluations, or mitigations were completed, such

as with Mythos through Project Glasswing, which may have had a negative impact on our short-term revenue,

and we may do so again in the future.

Our focus on AI safety and responsible deployment may also require us to incur significant additional costs,

including increased research and development expenses, additional personnel and infrastructure, and foregone

or delayed revenue opportunities relative to competitors that may prioritize speed to market, broader access, or

more permissive use of their products. These decisions may reduce customer adoption, limit usage by certain

customers or use cases, or make our offerings less attractive, particularly when compared to competitors that do

not adopt similar constraints.

In addition, as we focus on responsibly growing our customer base and engagement across our models,

platform, and applications, we may make product, pricing, or access decisions that lead to less short-term

profits or engagement compared to our competitors. Customers, partners, or investors may not agree with or

fully understand these decisions and may perceive them as limiting our competitiveness or commercial

potential, which could adversely affect our reputation, customer relationships, market adoption, or valuation.

We cannot assure you that our long-term strategy will ultimately result in superior financial performance or

that the anticipated long-term benefits of these decisions will be realized on the timeline we expect, or at all.

Any of the foregoing risks could adversely affect our business, financial condition, and results of operations.

Our investments in new products, technologies, and business initiatives may not produce the

expected benefits and could adversely affect our business.

We regularly make decisions to invest in new products, technologies, business lines, and strategic initiatives,

including in areas outside our current core offerings, and the outcomes of these investments are inherently

uncertain. These initiatives often require significant upfront investments of capital, research and development

resources, and management attention, and their outcomes may not achieve widespread market adoption, may

not generate revenue at anticipated levels, may take longer than expected to mature, or may fail entirely. In

addition, reallocating resources from our core offerings to pursue new initiatives could slow growth in existing

products, reduce operating efficiency, or weaken our competitive position if those initiatives do not succeed. If

our investments in new products or business lines do not produce the long-term benefits we anticipate, our

business, financial condition, results of operations, and prospects could be adversely affected.

Certain of these initiatives, including our life sciences research program, which involves operating laboratory

facilities, and our research in robotics and physical AI, require us to engage in activities outside our historical

experience as a software and research organization, such as handling biological and chemical materials,

operating laboratory and robotic equipment, and complying with biosafety, occupational health and safety,

environmental, hazardous materials, and, potentially, preclinical and clinical research regulations. These

activities expose us to categories of liability, including for workplace injury and environmental contamination,

that differ from those associated with our core business, and any drug candidates or other discoveries resulting

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from these efforts would face the lengthy, costly, and uncertain development and regulatory pathways

characteristic of the life sciences industry, and may never generate revenue.

If we fail to manage our technical operations infrastructure, or experience service outages,

interruptions, or delays in the deployment of our models, platform, and applications, our

results of operations may be adversely affected.

Our systems and operations are subject to disruptions resulting from changes to our technology infrastructure.

We have experienced, and may continue to experience, service interruptions or degraded performance due to

software deployments, configuration changes, system updates, and new model introductions. These disruptions

may adversely affect our ability to service customers and could result in lost revenue, customer attrition, or

reputational harm. Further, our mitigation efforts and processes may be insufficient to prevent or minimize the

impact of system changes on service availability, and we may lack adequate testing, rollback procedures, or

monitoring capabilities to detect and remediate issues arising from system changes in a timely manner. For

example, in March 2026, we experienced a service outage and periods of degraded performance resulting from

a combination of factors, including a significant and rapid increase in usage demand, compute constraints in

certain components of our infrastructure, and other factors. Although we have taken and continue to take steps

to address these issues, including migrating to more scalable infrastructure and enhancing our operational

processes, similar incidents may occur in the future.

In addition, continued growth in our customer base could place additional demands on our models, platform,

and applications and could cause or exacerbate slowdowns or interrupt the availability of our models, platform,

and applications. If there is a substantial increase in the volume of usage of our models, platform, and

applications, we will be required to further expand and upgrade our technology and infrastructure. Any

substantial increase in usage will also require increased compute. Because our compute is procured well in

advance based on projected demand across all workloads, a significant acceleration in customer demand could

cause aggregate capacity to fall short of the levels required to support all of our workloads concurrently at the

scale we intend. If our committed compute proves insufficient, or the composition of our committed compute

portfolio differs materially from our demand forecasts, we may experience service disruptions, degraded

response times, or limitations on customer and user access to our models, platform, and applications, while also

experiencing constraints on the compute available to support ongoing model development. There can be no

assurance that we will be able to accurately project the rate or timing of increases, if any, in the use of our

models, platform, and applications or expand and upgrade our systems and infrastructure to accommodate

such increases on a timely basis. If our users are not able to access our models, platform, and applications or

encounter slowdowns, we may lose customers or partners. In order to remain competitive, we must continue to

enhance and improve the responsiveness, functionality, and features of our models, platform, and applications

and the underlying compute infrastructure supporting them. Our disaster recovery plan may not be sufficient to

address all aspects or any unanticipated consequence or incidents, and our insurance may not be sufficient to

compensate us for the losses that could occur.

Moreover, Amazon, Google, and Microsoft provide substantial portions of the compute infrastructure that we

use to host our models, platform, and applications and many of the internal tools we use to operate our

business. Any significant disruption of, limitation of our access to, or other interference with this infrastructure

would negatively impact our operations, degrade the availability and performance of our models, platform, and

applications, and could cause us to lose customers who are unable to access or experience difficulties accessing

our models, platform, and applications. Even absent a full disruption, the level of service provided by Amazon,

Google, and Microsoft could affect the availability or speed of our models, platform, and applications, which

may also impact the usage of, and our customers’ satisfaction with, our models, platform, and applications and

could seriously harm our business and reputation.

Any transition of the services and infrastructure currently provided by Amazon, Google, and Microsoft to

another CSP would require significant time and expense and could further disrupt or degrade delivery of our

models, platform, and applications. Such a transition could require us to re-architect portions of our

infrastructure, retrain or migrate models and large datasets, incur data transfer and duplication costs, and

adapt our systems to new tools and configurations, which could result in operational delays and reduced

performance during the transition period. If Amazon, Google, or Microsoft increases pricing terms, terminates

or seeks to terminate our contractual relationship, whether for competitive reasons or otherwise, establishes

more favorable relationships with our competitors, or changes or interprets its terms of service or policies in a

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manner that is unfavorable with respect to us, our business, financial condition, and results of operations could

be adversely affected.

In addition, an increasing portion of our compute is hosted in dedicated data center facilities that are leased

and operated on our behalf by third parties rather than by our CSPs, and we expect this portion to grow. Certain

of these operators have a limited operating history, and these facilities may have less geographic redundancy,

failover capacity, or operational tooling than those of large-scale cloud environments, such that an equipment

failure, cooling or network disruption, or operator error at a single facility could affect a meaningful portion of

our available capacity. Moreover, the continuous availability of our models, platform, and applications depends

on the reliable supply of electrical power and water to the facilities that host our infrastructure, whether

operated by our CSPs or on our behalf. Utility outages, shortages, price increases, or required curtailment of

power during periods of peak demand, whether in connection with or outside of natural disasters or other

catastrophic events, could interrupt or degrade the provision of our services in the ordinary course of our

business. See the sections titled “—Constraints on the critical inputs supporting compute could limit our ability

to secure adequate compute.” and “—Our business, financial condition, and results of operations may be

adversely affected by war, terrorism, natural disasters, public health crises, political crises, or other unexpected

events.”

If we are unable to make acquisitions and investments, or successfully integrate them into our

business, our business, financial condition, and results of operations could be adversely

affected.

As part of our business strategy, we will continue to consider a wide array of potential strategic transactions,

including acquisitions of businesses, new technologies, services, and other assets and strategic investments that

complement our business. We have previously acquired and continue to evaluate targets that operate in

relatively nascent markets, and there is no assurance that such acquired businesses will be successfully

integrated into our business or generate substantial revenue. In addition, we may overpay for acquisition

targets or make investments at valuations that do not ultimately prove justified by the targets’ performance,

strategic value, or market conditions, which could adversely affect our financial condition.

We may be unable to identify or complete prospective and attractive strategic transactions for many reasons,

including competition from other potential acquirers, the effects of consolidation in our industry, and

potentially high valuations of acquisition candidates. Even if we identify strategic transactions or enter into

agreements with respect to such transactions, applicable antitrust laws and other regulations may limit our

ability to acquire targets or force us to divest all or a portion of our business or an acquired business. If we are

unable to identify suitable targets or complete acquisitions, our growth prospects may suffer, and we may not

be able to realize sufficient scale and technological advantages to compete effectively.

Acquisitions involve many risks, any of which could adversely affect our business, financial condition, and

results of operations, including:

•intense competition for suitable acquisition targets, which could increase prices and adversely affect

our ability to consummate deals on favorable or acceptable terms;

•failure or material delay in closing a transaction;

•transaction-related lawsuits or claims;

•difficulties in integrating the technologies, operations, existing contracts, and personnel of an acquired

company;

•difficulties in retaining key employees, business partners, or customers of an acquired company;

•challenges with integrating the brand identity of an acquired company with our own;

•diversion of financial and management resources from existing operations or alternative acquisition

opportunities;

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•failure to realize the anticipated benefits or synergies of a transaction at all or within the expected

timeframe;

•the incurrence of debt or dilution related to equity issuances in connection with a transaction;

•failure to identify or address the problems, liabilities, or other shortcomings or challenges of an

acquired company or technology, including issues related to copyrights and other intellectual property,

regulatory compliance practices, litigation, revenue recognition, or other accounting practices, or

employee or user issues;

•risks that the acquired company could have a negative impact on our company culture;

•risks that regulatory bodies may enact new laws or promulgate new regulations that are adverse to an

acquired company or business;

•risks that regulatory bodies do not approve our acquisitions or business combinations or delay such

approvals;

•theft of our trade secrets or confidential information that we share with potential acquisition

candidates;

•risk that an acquired company or investment in new services cannibalizes a portion of our existing

business; and

•adverse market reaction to an acquisition.

If we fail to address the foregoing risks or other problems encountered in connection with past or future

acquisitions of businesses, new technologies, services, and other assets, strategic investments, and other

strategic transactions, or if we otherwise fail to realize the expected benefits of such acquisitions or investments,

our business, financial condition, and results of operations could be adversely affected.

Unfavorable media coverage regarding our business, our models, platform, and applications,

the impacts of AI, and the AI industry more broadly could adversely affect our business,

financial condition, and results of operations.

As our business has grown and as interest in us and the AI industry overall has increased, we have attracted,

and may continue to attract, significant media coverage, public commentary, and scrutiny from time to time.

This coverage and commentary have included, and we expect will continue to include, recurring narratives

concerning the potential adverse societal impacts of AI, including that AI may displace or eliminate jobs, may

be misused or otherwise cause harm, and may pose catastrophic or existential risks to humanity. We have been,

and may continue to be, a particular focus of such narratives, and unfavorable coverage of the AI industry

generally may be attributed to us, in each case regardless of whether the underlying concerns are well-founded

or specifically applicable to our models, platform, or applications. Unfavorable publicity regarding us, our

partners, or the AI industry more broadly could adversely affect our reputation and brand, as described in the

section titled “—If we are unable to maintain and enhance our brand and reputation, our business, financial

condition, and results of operations may be adversely affected.” Negative media coverage, including public

figures making negative or threatening statements about our company, whether accurate or not, could also

adversely affect our brand and reputation and may reduce market acceptance of our models, platform, and

applications or impair our ability to attract and retain customers. As public awareness of our brand increases,

any issues that draw media attention may have an amplified adverse effect on our reputation. If unfavorable

media coverage or adverse public perceptions persist or intensify, the demand for our models, platform, and

applications could decline and our brand, business, financial condition, and results of operations could be

adversely affected.

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We will incur increased costs and demands upon management as a result of complying with

the laws and regulations affecting public companies, which may adversely affect our

business, financial condition, and results of operations.

As a public company, we will incur greater legal, accounting, and other expenses than we incurred as a private

company. For example, we are subject to the reporting requirements of the Securities Exchange Act of 1934, as

amended (“Exchange Act”), the Sarbanes-Oxley Act of 2002 (“Sarbanes-Oxley Act”), the Dodd-Frank Wall

Street Reform and Consumer Protection Act, the rules and regulations of the SEC, and the listing standards of

the Nasdaq Global Select Market. The Exchange Act requires, among other things, that we file annual,

quarterly, and current reports with respect to our business and results of operations. Compliance with these

requirements will increase our legal, accounting, and financial compliance costs, and increase demand on our

systems, making some activities more time-consuming and costly. In addition, changing laws, regulations, and

standards relating to reporting obligations and corporate governance disclosure are creating uncertainty for

public companies, which could result in continued uncertainty regarding compliance matters and higher costs.

We expect these rules and regulations to make it more expensive for us to obtain director and officer liability

insurance, and we may be required to accept reduced policy limits and coverage or incur substantially higher

costs to maintain the same or similar coverage. As a result, it may be more difficult for us to attract and retain

qualified individuals to serve on our board of directors or as our executive officers.

As a public company, we expect to incur significant expenses and devote substantial management effort toward

ensuring compliance with the auditor attestation requirements of Section 404 of the Sarbanes-Oxley Act. In

that regard, we will need to hire additional accounting and financial staff with appropriate public company

experience and technical accounting knowledge. In addition, as a public company, we may be subject to

stockholder activism, which can lead to substantial costs, distract management, and impact the manner in

which we operate our business in ways we cannot currently anticipate.

As a result of disclosure of information in this prospectus and in our public filings with the SEC as required of a

public company, our business and financial condition will become more visible, which we believe may result in

threatened or actual litigation, including by competitors and other third parties. If such claims are successful,

our business, financial condition, and results of operations may be adversely affected, and even if the claims do

not result in litigation or are resolved in our favor, these claims, and the time and resources necessary to resolve

them, may divert the resources of our management and our board of directors, and adversely affect our

business, financial condition, and results of operations.

Further, many members of our management team have limited experience managing a publicly traded

company, interacting with public company investors, and complying with the increasingly complex laws and

regulations pertaining to public companies. Our management team may not successfully or efficiently manage

our transition to being a public company subject to significant regulatory oversight and reporting obligations

under the federal securities laws and the continuous scrutiny of securities analysts and investors. These new

obligations and constituents will require significant attention from our management and may divert their

attention away from the day-to-day management of our business, which may adversely affect our business,

financial condition, and results of operations.

Our business, financial condition, and results of operations may be adversely affected by war,

terrorism, natural disasters, public health crises, political crises, or other unexpected events.

War, terrorist attacks, and other acts of political violence, or any significant natural disaster, such as an

earthquake, fire, hurricane, tornado, flood, or significant power outage, may disrupt our operations, mobile

networks, the internet, data centers, or the operations of our partners or third-party service providers, and the

impact of climate change may increase these risks. In particular, our corporate headquarters are located in the

San Francisco Bay Area, a region known for seismic activity and increasingly for the threat of fires. In addition,

any public health crises, pandemics, political crises, terrorist attacks, war and other political or social

instability, other geopolitical developments, or other catastrophic events, whether in the United States or in

non-U.S. geographies, may adversely affect our operations or macroeconomic conditions. For example, an act of

terrorism, armed conflict, or escalation of geopolitical tensions could result in physical damage to or

destruction of data centers and other critical infrastructure, whether owned or operated by us or our third-party

providers, as well as disruptions to power, cooling, or network connectivity necessary to operate such facilities.

The impact of any of the foregoing or other disruption to us, our partners, or other third parties may result in

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system interruptions and degradation, reputational harm, delays in our product development, lengthy

interruptions in our services, data breaches, malware, and other security or hacking incidents, all of which may

adversely affect our business, financial condition, and results of operations. All of the aforementioned risks may

be further increased if our disaster recovery plans prove to be inadequate. Further, the insurance we maintain

may be insufficient to cover our losses resulting from such business interruptions, and any incidents may result

in loss of, or increased costs of, such insurance.

If we are unable to ensure that our models, platform, and applications interoperate with a

variety of software applications that are developed by others, including our integration

partners, we may become less competitive and our business, financial condition, and results

of operations may be adversely affected.

Our models, platform, and applications must integrate with a variety of hardware and software platforms, and

we need to continuously modify and enhance our models, platform, and applications to adapt to changes in

hardware, software, and browser technologies. In particular, we have developed our models, platform, and

applications to be able to easily integrate with third-party applications, including the applications of software

providers that compete with us as well as our partners, through the interaction of APIs. In general, we rely on

the providers of such software systems to allow us access to their APIs to enable these integrations. We are

typically subject to standard terms and conditions of such providers, which govern the distribution, operation,

and fees of such software systems, and which are subject to change by such providers from time to time. Our

business will be harmed if any provider of such software systems:

•discontinues or limits our access to its software or APIs;

•modifies its terms of service or other policies, including fees charged to, or other restrictions on us, or

other software developers;

•changes how information is accessed by us or our customers;

•establishes more favorable relationships with one or more of our competitors; or

•develops or otherwise favors its own competitive offerings over our models, platform, and applications.

Further, we depend in part on operating systems, including mobile operating systems such as iOS and Android,

and their respective application stores, such as Apple’s App Store and Google’s Play Store, to drive downloads of

our Claude app. If such operating systems or application stores limit the availability of our app, make changes

that degrade the functionality of our app, increase the cost of using our app, impose terms of use unsatisfactory

to us, or modify their search or ratings algorithms in ways that are detrimental to us, or if our competitors’

placement in such mobile operating systems’ application store is more prominent than the placement of our

app, our user growth could be adversely affected. Any changes in such operating systems and application stores

that degrade the functionality of our app or give preferential treatment to our competitors’ apps could adversely

affect our platform’s usage across devices. Some marketplaces have explored changing their policies regarding

what content is acceptable within an application. If we are unable to adapt to such changes, this could adversely

affect our platform’s access to and usage within those ecosystems. As new mobile devices and mobile platforms

are released, there is no guarantee that certain mobile devices will continue to support our platform or

effectively roll out updates to our apps. Additionally, in order to deliver a high-quality app, we need to ensure

that our models, platform, and applications are designed to work effectively with a range of mobile

technologies, systems, networks, and standards. We may not be successful in developing or maintaining

relationships with key participants in the mobile industry that enhance users’ experience. If users encounter

any difficulty accessing or using our apps on their mobile devices or if we are unable to adapt to changes in

popular mobile operating systems, our prospects, business, financial condition, and results of operations could

be adversely affected.

Third-party models, platforms, and applications are constantly evolving, and we may not be able to modify our

models, platform, and applications to assure their compatibility with that of other third parties. In addition,

some of our competitors may be able to disrupt the operations or compatibility of our models, platform, and

applications with their models, platforms, or applications, or exert strong business influence on our ability to,

and terms on which we operate our models, platform, and applications. Should any of our competitors modify

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their products or standards in a manner that degrades the functionality of our models, platform, and

applications or gives preferential treatment to competitive models, platforms, or applications, whether to

enhance their competitive position or for any other reason, the interoperability of our models, platform, and

applications with these products could decrease and our business, financial condition, and results of operations

could be adversely affected. Further, if we are not permitted or able to integrate with these and other third-

party applications in the future, our business, financial condition, and results of operations could be adversely

affected.

Many of the risks we face are interconnected and may compound or trigger cascading adverse

effects across our business, which could amplify their overall impact.

Our business and operations are subject to numerous risks and uncertainties, as described in this “Risk

Factors” section, many of which are interrelated, such that the occurrence of one risk event may exacerbate or

trigger additional risk events, and the combined effect may be materially greater than the impact of any

individual risk event in isolation. For example, unfavorable developments in intellectual property laws or

adverse outcomes in copyright or other litigation could require us to modify, retrain, or limit the capabilities of

our models, increasing costs and reducing the performance or competitiveness of our models, platform, and

applications, which could in turn harm customer demand, revenue, and our reputation and brand. In addition,

constraints on the availability or cost of compute could similarly limit our ability to develop and deploy

advanced models, delay product launches, reduce service reliability, and adversely affect our revenue growth,

while also affecting customer trust and perception of our offerings. If our revenue growth is limited and we do

not have sufficient additional sources of capital, we may be unable to acquire necessary compute or invest in

our talent to remain at the technological frontier or to support our customers, or we may face breaches of

covenants or defaults under the A&R Credit Agreement and certain of our commercial agreements. If we were

to breach covenants or default under the A&R Credit Agreement or certain of our commercial agreements, such

an event could trigger cross-defaults, accelerate repayment obligations, restrict our access to capital, and

further constrain our operations and growth, potentially magnifying other financial, operational, and

reputational risks. Because these and other risks may interact in complex and unpredictable ways, particularly

in a fast-moving industry characterized by technological change, evolving regulation, and emerging business

models, we may not be able to foresee or effectively manage all potential consequences. If one risk triggers or

intensifies others, or if multiple adverse events occur concurrently or in close succession, our prospects,

reputation, business, financial condition, and results of operations could be adversely affected.

Risks Related to Privacy, Cybersecurity, and Intellectual Property

The application of certain copyright law doctrines and contractual interpretations of open-

source licenses to modern AI model training are uncertain.

The application of certain copyright law doctrines and contractual interpretations of open-source licenses to

modern AI model training has not been authoritatively resolved by U.S. and non-U.S. courts as of this date. We

have a good faith belief that we own or possess all sufficient legal rights and/or defenses to the training data

used in or with our AI models, platform, and applications, which is based in part on our belief that our use or

acquisition of the training data used in or with our AI models, platform, and applications constitutes “fair use”

of such training data under copyright law doctrine. In addition, copyright laws in some jurisdictions outside the

United States generally do not recognize fair use, and our reliance on analogous exceptions is subject to

evolving conditions and to adverse or unsettled judicial interpretation in those jurisdictions. If a court of law

disagrees with our belief that our use or acquisition of such training data constitutes fair use or otherwise

concludes that it violates copyright law, for example, by adopting the reasoning in Bartz (as defined below),

including without limitation in currently active litigation against us or another company in our industry, our

business may be adversely affected. In particular, adverse rulings in litigation involving other AI developers,

regardless of the specific facts, data practices, or legal theories at issue in those cases, could establish legal

precedents or interpretations of copyright law that apply broadly across the industry and limit our ability to

train, develop, or deploy AI models, even if our own data procurement and usage practices differ. Such

outcomes could restrict access to certain categories of training data, narrow the scope of available legal

defenses, or impose new licensing, compliance, or operational requirements across the AI industry. For

example, if we cannot rely on the fair use doctrine to access copyrighted work for training our models, we may

be required to pay significant fees to obtain a license to such training data or our ability to further develop our

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models, platform, and applications and distribute models trained on such data at issue could be adversely

affected. In addition, an adverse ruling against us or another company in our industry could result in injunctive

relief that restricts our ability to use or distribute models trained on the data at issue or could require us to

retrain affected models from scratch at substantial cost. If we are unable to manage the foregoing risks, our

business, financial condition, and results of operations could be adversely affected.

We are subject to complex and evolving laws, regulations, and other legal obligations related

to privacy and data protection, and any actual or perceived failure to comply with such

obligations could adversely affect our business, financial condition, and results of operations.

We are subject to a range of laws and regulations in the EU, the United States, and other jurisdictions, and

other legal obligations relating to privacy, data protection, and the collection, use, transfer, storage, and other

processing of data. These laws, regulations, and other legal obligations vary across jurisdictions, and include

comprehensive frameworks such as the General Data Protection Regulation 2016/679 (“GDPR”), laws that

impose sector-specific obligations, and those that impose specific requirements or restrictions on the handling

of particular types of data, such as personal data that is considered sensitive. These obligations are not

harmonized, continue to evolve in scope, present technical and operational complexities and challenges, and

may conflict or impose overlapping or inconsistent obligations. Further, these laws and regulations, as well as

other laws and regulations not originally enacted to address privacy or data protection, continue to evolve as

they are applied to new technologies, including AI, and may be interpreted or enforced in ways that are

inconsistent, unclear, novel, or subject to significant regulatory discretion. Additionally, plaintiffs, class action

counsel, state Attorneys’ General, and other claimants continue to pursue claims against artificial intelligence

companies relating to data handling, privacy, and cybersecurity; similar disputes could arise against us and they

could take the form of privacy, cybersecurity, breach of contract, tort, or other claims. New or evolving laws,

regulations, regulatory interpretations, claims, and novel or inconsistent application of existing laws and

regulations to us, or our evolving contractual or other legal obligations, including those that arise as we seek to

enter into new markets or product offerings, may require us to modify our models, platform, and applications,

policies, and practices, delay or limit the development or deployment of certain features, increase compliance

and litigation costs, and result in fines or penalties.

Our compliance obligations and expenditures, and our exposure thereunder, may vary depending on both how

customers access and use our models, platform, and applications, including through our first-party offerings or

third-party distribution channels, and on the nature of data processed in connection with those offerings. For

example, our costs and regulatory exposure may vary based on the demands we receive from individuals,

regulators, and other parties seeking to exercise rights under privacy or data protection laws. We may be subject

to additional obligations, restrictions, or exposure in connection with the processing of data that is considered

sensitive under applicable laws. In connection with the development, deployment, and improvement of our

services, including model training, improvement, and inference, we have faced, and may face in the future,

operational errors or claims or assertions that our use or processing of data, such as personal, sensitive, or

confidential data, is inconsistent with our obligations.

Failure to secure data against risks to its confidentiality, integrity, or availability may result in legal obligations,

such as notification obligations to individuals, regulators, or customers, which could result in additional legal

and reputational risk.

Any actual or perceived failure or inability by us, our personnel, or third parties acting on our behalf to comply

with applicable privacy or data protection requirements, our contractual commitments, or our public

statements regarding our data practices could result in investigations, litigation, fines, penalties, or other

liability; require us to change our models, platform, and applications, policies, or practices; reduce customer

demand or harm our reputation; require us to make public disclosures that could expose us to reputational and

legal risks; and otherwise adversely affect our business, financial condition, and results of operations.

We process personal and sensitive data for AI safety, and any actual or perceived failure to

comply with the legal and regulatory obligations applicable to such processing could

adversely affect our business, financial condition, and results of operations.

Our commitment to AI safety requires us in some cases to access, collect, and process personal and sensitive

data. While our approach and mechanisms relating to handling personal and sensitive data are designed to

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improve AI safety, they also subject us to compliance with evolving industry practices, laws and regulations, and

increased risks related to the processing of sensitive data, such as increased risks of harm or litigation if we

experience a security incident or unauthorized access to or processing of data. Further, laws and regulations not

originally enacted to address AI safety are being applied to AI safety and may be increasingly interpreted or

enforced in ways that are inconsistent, unclear, novel, or subject to significant regulatory discretion. Any actual

or perceived failure to comply with AI safety requirements or our processing of personal or sensitive data for AI

safety, or any actual or perceived security incident involving such data, could result in investigations, litigation,

fines, penalties, or other liability; require us to change our policies or practices; reduce customer demand or

harm our reputation; require us to make public disclosures that could expose us to reputational and legal risks;

and otherwise adversely affect our business, financial condition, and results of operations.

Any security breaches or other incidents, including those that affect our networks, systems, or

data, or the networks, systems, or data of our service providers, suppliers, or customers,

could adversely affect our business, financial condition, and results of operations.

We store, handle, and otherwise process confidential, proprietary, and personal information, and our

customers use our models, platform, and applications to process similarly sensitive information. We experience

security risks, unintended exposure of or access to data, cyberattacks, and other attempts to gain unauthorized

access to our information, sites, networks, systems, models, platform, and applications. These have resulted in,

and may in the future result in, breaches of our security measures or those of our third-party service providers;

unauthorized access to our sites, networks, systems, and accounts; unauthorized access to, and

misappropriation of, personal, confidential, or proprietary information belonging to us, our customers, or

others; viruses, worms, spyware, or other malware being served from our models, platform, and applications,

networks, or systems; deletion or modification of content; the display of unauthorized content on our models,

platform, and applications; interruption, disruption, or malfunction of operations; and other risks.

We have in the past faced and in the future may face risks of phishing schemes and other cyberattacks,

including by nation-states and state-sponsored actors, that continue to evolve in sophistication and volume,

and may inherently be difficult to detect. Our proprietary model weights, corporate and financial data, and

other core intellectual property represent particularly high-value targets for state-sponsored espionage and

theft, and security researchers have identified frontier AI companies as priority targets for non-U.S. intelligence

services. The efforts of such state-sponsored actors to target us will likely increase over time, especially as we

develop models with next-generation capabilities, and they may specifically target models which have not, or

have not yet, been released to the general public. For example, in light of its advanced cyber vulnerability

discovery capabilities, state-sponsored actors may conduct cyberattacks specifically targeting Mythos.

Our security capabilities continue to evolve, and certain aspects of our security program may not be sufficient to

fully address the most sophisticated malicious actors, including well-resourced nation-state or state-sponsored

groups, especially as those groups develop or obtain more powerful technology, which may include AI

technology with offensive capabilities similar to those displayed by Mythos. While we are actively investing in

and enhancing our security infrastructure and controls, we have operated in the past, and may in the future

operate, for periods of time with known limitations or gaps in our defenses as we continue to mature our

security posture, and no information security program can be expected to prevent all possible incidents. There

can be no assurances that we will be able to prevent or adequately detect and defend against all cyberattacks or

other cybersecurity incidents affecting our systems, including incidents caused by nation-state and state-

sponsored actors. An unauthorized exfiltration of our model weights could enable adversaries to bypass

significant research investment, eliminate key competitive advantages, and potentially raise national security

concerns if such technology is acquired by malicious actors. Further, if our model weights were obtained by

unauthorized actors, such actors may be able to deploy such models outside of our usage policies, safety

mechanisms, or monitoring frameworks, which could enable harmful or misuse scenarios that our safeguards

are designed to prevent and could subject us to regulatory, reputational, or public scrutiny for having developed

such capabilities.

We have faced and expect to face insider threat risks and vulnerabilities related to hiring processes, identity

verification, remote work environments, and compromised devices that could enable unauthorized access to

sensitive systems or information. We have been and expect that we will continue to be targeted by individuals

seeking employment under false identities, or with ulterior or malicious motives for seeking employment with

us and the third parties on which we rely. We also face the risk that employees, contractors, or other personnel

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with authorized access to our systems, model weights, or other sensitive information may be compromised after

joining us, including due to efforts by state-sponsored actors, competitors, or others to recruit, bribe, coerce, or

otherwise induce such personnel, or to compromise their credentials or devices, in order to misappropriate

sensitive information, enable unauthorized access, or introduce vulnerabilities into our systems, models, or

products. Because personnel with authorized access to our model weights and other core intellectual property

are particularly attractive targets, and because our remote and distributed work environment and our reliance

on third-party vendors for certain key processes may limit our visibility into such conduct, we may be unable to

prevent or timely detect these insider threats. In addition, in certain jurisdictions in which we operate or in

which our vendors or the operators of facilities hosting our infrastructure are located, such personnel, vendors,

or operators may be legally compelled to cooperate with government authorities, including intelligence and

security agencies, in ways contrary to our interests, such as by providing access to our systems, data, or model

weights. The laws of those jurisdictions may prohibit the affected parties from notifying us of such demands

and may afford us limited or no ability to challenge them, and because such cooperation may be lawful where it

occurs and involves personnel acting within their authorized access, our insider-threat and other security

controls may not detect it.

We have also seen, and expect to continue to see, industry-wide software supply chain vulnerabilities and

attacks, which could affect our or third parties’ systems, or the security of our models, platform, and

applications. Geopolitical tensions or armed conflicts around the world may increase these risks. As a result, we

may be unable to prevent or timely detect all attempts to access or exfiltrate sensitive information, including by

actors with substantial technical, financial, or geopolitical resources.

As we continue to develop and deploy new features, including those incorporating AI, our systems are exposed

to additional or evolving security risks, including those arising from emerging or imperfectly understood AI-

specific threat vectors. Such AI-specific threats include prompt injection attacks that manipulate model

behavior through malicious inputs, attempts to replicate or reverse engineer our proprietary models through

systematic API queries, adversarial inputs designed to cause model failures or misclassifications, malicious

corruption of training data that could compromise model integrity, and vulnerabilities in continuous

integration and deployment pipelines that could allow insiders or other actors to inject malicious code that is

subsequently propagated or amplified through AI-assisted development workflows. Such attacks may be

difficult to detect, may not be addressed by traditional cybersecurity defenses, and may require specialized

expertise, techniques, and infrastructure to mitigate. Further, features that rely on AI may be particularly

susceptible to unanticipated vulnerabilities as both our understanding and the broader market’s understanding

of AI-related security risks and mitigation techniques continue to develop. Our efforts to mitigate the foregoing

risks may result in false positives and our mistakenly limiting or blocking certain users from accessing our

technology, which could result in potential litigation or regulatory action.

In addition, our agentic offerings interact with external tools, APIs, databases, code repositories, and other

third-party systems, creating cybersecurity attack surfaces that are distinct from those applicable to traditional

AI models. An adversary could manipulate the content of an external data source, API response, document, or

web page processed by an agent to cause the agent to take harmful or unauthorized actions based on that

manipulated input. An attacker could also attempt to compromise an active agent session and redirect the agent

to perform malicious actions using the customer’s authenticated credentials and permissions. Because our

agentic offerings are designed to take autonomous actions with real-world consequences, including executing

code, modifying files, sending communications, and completing transactions, a successful exploitation of these

agentic attack surfaces could result in data exfiltration, unauthorized transactions, code injection, or other

adverse effects, potentially across multiple customer deployments simultaneously. Traditional cybersecurity

defenses, including firewalls, input validation, and access controls, may not be fully effective against these novel

threat vectors, and the security community’s understanding of agentic-specific attack surfaces is still

developing.

We have in the past discovered, and may in the future discover, errors, vulnerabilities, or other defects, such as

hallucinations, in our models, platform, and applications only after deployment, including in connection with

the development of new features, integrations, or capabilities. Such issues have resulted and may in the future

result in service disruptions, degraded performance, unintended or harmful outputs, or the unauthorized

disclosure of personal or proprietary information, including through security incidents that impact the

networks, systems, and data of our customers. In addition, incidents impacting our customers may be caused by

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customer misconfiguration or misuse, or by inadequate access controls or other security practices by our

customers. Such incidents, even if caused by customer misconfigurations or misuse, or by a customer’s lack of

adequate security controls, may impact our reputation or the reputation of our models, platform, and

applications, and may subject us to liability exposure, disruption of commercial relationships, or other damage.

Cyberattacks, including cyberattacks directed at our networks, our customers’ networks, or the networks of

third parties with which we have relationships, have been, and may in the future continue to be, amplified

through the use of AI, including our models, platform, and applications. Such capabilities may be used to

automate or scale attacks, impersonate employees or members of senior management, or otherwise gain

unauthorized access to our systems or those of our customers, partners, or vendors.

Failures in our internal systems or controls, security breaches, failures to comply with our privacy or data

protection commitments, or other incidents, whether resulting from malicious activity, human error, or system

limitations, could adversely affect our reputation, brand, and business and impair our ability to attract and

retain customers. Our offices and the data centers that host our infrastructure, many of which are operated by

third parties, are also exposed to physical threats as well as failures by the operators of those facilities. A

physical intrusion could damage equipment, interrupt our services, or provide a path to our systems and data,

including our model weights, that bypasses our network defenses.

Although we have dedicated significant resources designed to identify and address these security risks, we

cannot guarantee that our security measures will be effective or that our recovery protocols, backup, and other

systems will be sufficient. Even where we detect an incident, our response may prove inadequate, including if

we misjudge its severity, respond too slowly, or fail to fully remediate the underlying cause. In addition,

incidents that appear minor when they occur may later prove significant when considered together with other

incidents or with information learned afterward, and a series of related incidents, none of which is material on

its own, could prove material in the aggregate. We continue to devote significant resources to protect against

security breaches and other incidents, and we may need to devote significant resources in the future to mitigate

and address problems caused by breaches and other incidents, which may divert resources from the growth and

expansion of our business.

Any actual or perceived security breach or other incident experienced by us or third parties with whom we do

business, particularly our CSPs, could damage our reputation and brand, cause our business to suffer, require

us to expend significant capital and other resources, cause us to incur increasing costs, including costs to deploy

additional personnel and protection technologies, train employees, and engage third-party experts and

consultants, expose us to litigation or regulatory action, cause us to violate applicable privacy, data protection,

security, and other laws and regulations, subject us to adverse publicity and a loss of confidence in our security

measures, and cause us to incur significant fines, penalties, and other liability exposure, which could adversely

affect our business, financial condition, and results of operations. We have taken steps to limit our liability for

certain incidents, for example through warranty disclaimers and limitations of liability in our terms of service,

but those contractual protections may not be upheld, or may not apply to certain claims, or may otherwise be

insufficient to limit our liability exposure under applicable law.

In the EU, we face increasingly stringent regulatory reporting obligations for cybersecurity and AI-related

incidents. Under the GDPR, we must notify the competent regulators about incidents that involve personal data

and are likely to result in a risk to the rights and freedoms of individuals. Similarly, the EU Network and

Information Security Directive 2022/2555 (“NIS2”) requires us to notify the competent authorities of any

significant cybersecurity incident through a staged process. In addition, the EU AI Act requires providers of

general-purpose AI models with systemic risk to keep track of, document, and report serious incidents without

undue delay to the AI Office and competent authorities. Going forward, providers and deployers of high-risk AI

systems, as defined under the EU AI Act, will also have to report serious incidents or malfunctions without

undue delay in certain circumstances.

In the United States, companies are increasingly subject to analogous incident reporting obligations, including

under federal and state data breach notification laws, such as the New York Stop Hacks and Improve Electronic

Data Security (SHIELD) Act. In addition, certain U.S. states have adopted incident reporting laws specific to

frontier model providers, such as the New York Responsible AI Safety and Education Act (RAISE Act) and the

California Transparency in Frontier Artificial Intelligence Act. These frameworks create heightened compliance

and liability exposure in case of delayed, incomplete, or inaccurate incident disclosures.

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While we currently maintain insurance that may cover certain costs, liabilities, and other losses in connection

with security breaches and other incidents, the insurance market for such losses is continuously evolving, and

we may be unable to obtain coverage for certain cybersecurity-related or data-related liabilities on commercially

reasonable terms, or at all, leaving us exposed to potentially significant uninsured losses. Furthermore, there

can be no guarantee that the insurance coverage we do maintain will be adequate to compensate us for the

potential losses, or that any insurance claims we submit will be covered, paid in a timely manner, or paid at all

by our insurance carrier or carriers.

We employ automated data collection across the web and use other methods to collect data for

training our AI models, and such activities may subject us to liability or limit our ability to

use the collected data, which may adversely affect our business, financial condition, or results

of operations.

We collect and use various data sources to train our AI models, including publicly available information from

the internet, datasets licensed or commissioned from third parties, and synthetic data generated by our own

models. We use such data across the stages of model development, including pre-training and post-training. To

collect publicly available information, we utilize web scraping or web crawling techniques, book scanning, and

other methods. While we take steps designed to ensure that our activities comply with applicable law,

applicable robots.txt notices, and relevant technical measures such as paywalls or logins, our efforts may not

always be successful. Further, we may not be able to verify whether information collected using such techniques

is protected under privacy, copyright, or other intellectual property laws in certain cases, and our use of any

such protected information may subject us to additional liability for intellectual property infringement or

privacy violations. More broadly, inadequate documentation of training data sources, provenance, or chain of

custody could create legal exposure, complicate our ability to respond to regulatory inquiries or litigation

discovery requests, or raise concerns during due diligence by investors, partners, or potential acquirers that

could adversely affect our strategic transactions or business relationships.

Our data collection activities have in the past resulted, are presently the subject of, and may in the future result

in litigation or other actions filed or instituted against us, alleging that our scraping, web crawling, and other

techniques to collect data violate the law. For example, Reddit, Inc. has filed suit against us, captioned Reddit,

Inc. v. Anthropic PBC, alleging we improperly accessed posts stored on Reddit, Inc.’s platform in violation of its

legal rights. On July 3, 2025, we filed a notice of removal of the case to federal court. The case was remanded to

state court on March 30, 2026. The lawsuit is currently pending, and we continue to defend ourselves against

the allegations.

The costs of defending against such litigation, regardless of merit, are considerable, and such litigation may

divert management and key personnel’s attention and resources, which may seriously harm our business,

financial condition, and results of operations. Claims of allegedly illegal scraping and web crawling techniques

may be extremely broad, and it may not be possible for us to conduct our business in such a way as to avoid all

such claims.

We may be required to settle such litigation on terms that are unfavorable to us. For example, a settlement may

require us to discontinue such allegedly illegal practices, preclude us from using certain scraping and web

crawling techniques, and/or require us to develop alternative technology or practices. The development of

alternative technology or practices would require significant effort and expense or may not be successful.

Similarly, if any litigation to which we may be a party fails to settle and we go to trial, we may be subject to an

unfavorable judgment which may not be reversible upon appeal. The terms of a judgment may require us to

cease some or all of our operations or require the payment of substantial amounts. Any of these events could

cause our business, financial condition, and results of operations to be adversely affected as a result.

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We collect, integrate, and analyze data via agreements from multiple sources, including data

provided by our customers and users and data sourced from third parties under contractual

arrangements, and such activities may subject us to liability or limit our ability to use the

collected data, which may adversely affect our business, financial condition, or results of

operations.

If we or the customers, users, or third parties from which we source data lack sufficient rights to collect, use,

process, share, or analyze certain third-party data—including for training or improving analytical or AI models

—we could be subject to legal claims, regulatory scrutiny, or contractual liability. Such claims could require us

to limit functionality, segregate data, or retrain models, and could adversely affect our business, financial

condition, and results of operations.

The costs of defending against such litigation, regardless of merit, are considerable, and such litigation may

divert management and key personnel’s attention and resources, which may adversely affect our business,

financial condition, and results of operations. Claims of misappropriation, misuse, infringement, privacy

violations, or other violations of intellectual property or contractual rights, as well as other claims related to

using particular data, may be extremely broad, and as such, it is likely we will face certain claims in the ordinary

course of business.

We have been, are currently defending against, and may in the future be, subject to

intellectual property rights claims by third parties, which are extremely costly to defend, may

require us to pay significant damages and may limit our ability to use certain technologies,

which may adversely affect our business, financial condition, and results of operations.

There is considerable intellectual property development activity in our industry. Our competitors, as well as a

number of other entities, including non-practicing entities and individuals, may own or claim to own

intellectual property rights relating to our industry or our technology. As we face increasing competition and

our public profile increases, the possibility of intellectual property rights claims against us may also increase.

To train our models, we use material from many sources, some of which may include third-party copyrighted

content or trademarks. Regardless of whether the material is copyrighted or the trademarks are registered,

parties who own the rights to that content or those trademarks, or distribute that content, may attempt to sue

us based on intellectual property infringement or other theories. We also face claims that outputs generated by

our models infringe, or facilitate infringement of, third-party works. Lawsuits asserting such claims have been

filed, are pending, and may be filed in the future in the United States and internationally. For example, in

September 2025, we reached an agreement to settle a copyright infringement class action, captioned Bartz, et

al. v. Anthropic PBC (“Bartz”), for $1.5 billion, which was approved by the district court in July 2026. As

additional examples, various publishers have filed suit against us alleging copyright infringement of song lyrics

and unlawful removal of copyright management information in the cases captioned Concord Music Group, Inc.,

et al. v. Anthropic PBC, Concord Music Group, Inc., et al. v. Anthropic PBC et al., BMG Rights Management

(US) LLC v. Anthropic PBC, Round Hill Music LP, et al. v. Anthropic PBC, Sony Music Publishing (US) LLC v.

Anthropic PBC et al., and others. Similarly, a third party alleges we accessed and reproduced posts stored on

the third party’s platform in violation of its legal rights and has filed suit against us, captioned Reddit, Inc. v.

Anthropic PBC. The possibility of statutory damages under some intellectual property legal frameworks creates

additional risk for us. We are vigorously defending ourselves in these pending lawsuits and believe we have

meritorious defenses, though these lawsuits address novel issues and areas of law that make the results

uncertain.

We also face patent infringement claims, which may seek substantial damages or injunctive relief limiting our

ability to use certain technologies, and we expect such claims may increasingly be asserted as our public profile

grows. Moreover, certain of our competitors hold substantially larger patent portfolios than we do, which they

could assert against us and which may limit our ability to obtain effective cross-licenses or to counter such

assertions with our own patent rights.

The costs of defending against such litigation, regardless of merit, are considerable, and such litigation may

divert management and key personnel’s attention and resources, which may adversely affect our business,

financial condition, and results of operations. Claims of misappropriation, misuse, infringement, or other

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violations of intellectual property rights, as well as other claims related to using particular content, may be

extremely broad, and as such, it is likely we will face certain claims in the ordinary course of business.

We may be required to settle such litigation on terms that are unfavorable to us. For example, a settlement may

require us to obtain a license to continue practices alleged to violate a third party’s rights, which may not be

available on reasonable terms and may significantly increase our operating expenses. Such a license may not be

available to us at all. As a result, we may be required to develop alternative technology or practices or

discontinue such allegedly infringing practices. The development of alternative technology or practices would

require significant effort and expense or may not be successful.

Similarly, if any litigation to which we may be a party fails to settle and we go to trial, we may be subject to an

unfavorable judgment which may not be reversible upon appeal. The terms of a judgment may require us to

cease some or all of our operations or require the payment of substantial amounts. Any of these events could

cause our business, financial condition, and results of operations to be adversely affected as a result.

We also offer to indemnify our contract counterparties for certain third-party infringement claims against

them, and such indemnification obligations may be excluded from contractual limitation of liability provisions

that limit our exposure. In certain cases, our indemnification obligations may be broad or unlimited in scope,

which could expose us to significant contingent liabilities, particularly given the unsettled nature of intellectual

property law as applied to AI-generated outputs and the potential for claims to arise from a wide range of

customer use cases that we cannot predict or control. For example, certain of our agreements require us to

defend and indemnify the counterparty, without a cap on our liability, against third-party claims alleging that

our models, or outputs generated by our models, infringe third-party intellectual property rights. In addition, as

described in the section titled “—We may be exposed to liability, litigation, and regulatory action arising from

harms associated with our AI models, and our contractual protections and insurance may be insufficient, any of

which could adversely affect our business, financial condition, and results of operations,” certain of our

agreements with external evaluators and testing vendors require us to defend and indemnify the evaluator,

without a cap on our liability, against certain third-party claims, including claims of intellectual property

infringement. Third-party infringement claims may require us to initiate or defend protracted and costly

litigation on behalf of our customers and distribution partners, regardless of the merits of these claims. If any of

these claims succeed, we may be forced to pay damages on behalf of our customers and reseller partners, may

be required to modify our allegedly infringing models, platform, and applications to make them non-infringing,

or may be required to obtain licenses under the infringed intellectual property rights. If we cannot obtain all

necessary licenses on commercially reasonable terms or are unable to modify our models, platform, and

applications or technology so that they are no longer infringing, our customers may be forced to stop using our

models, platform, and applications, and our distribution partners may be forced to stop selling our models,

platform, and applications. Even if we do not litigate these matters to a judgment, we may be required to settle

such litigation on terms that are unfavorable to us.

If we fail to adequately protect our intellectual property rights, our competitive position may

be impaired, and we may lose valuable assets, generate reduced revenue, and incur costly

litigation to protect our rights, which may adversely affect our business, financial condition,

and results of operations.

Our success is dependent, in part, upon protecting our intellectual property rights and proprietary information.

We rely and expect to continue to rely on a combination of trademark, copyright, patent, and trade secret

protection laws, along with contractual restrictions, to protect our intellectual property rights and proprietary

information. However, we cannot guarantee that the steps we take to protect our intellectual property rights

and proprietary information will be sufficient, or that we will have adequate remedies for any such failure. In

particular, current or former employees, contractors, or other insiders with access to our proprietary model

weights, training data, algorithms, research insights, or other proprietary information, could misappropriate

such information, whether for personal gain, to benefit competitors, to harm our company, or for other

purposes, and our confidentiality agreements and internal security controls may not be sufficient to prevent or

detect such malfeasance.

Further, third parties have in the past, and may in the future, knowingly or unknowingly infringe or circumvent

our intellectual property rights, and we may not be able to prevent infringement without incurring substantial

expense. Litigation brought to protect and enforce our intellectual property rights has been, and would be,

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costly, time-consuming, and distracting to management and key personnel, and could result in the impairment

or loss of portions of our intellectual property rights. Further, our efforts to enforce our intellectual property

rights may be met with defenses, counterclaims, and countersuits attacking the validity and enforceability of

our intellectual property rights and may result in injunctive relief or monetary damages against us. If the

protection of our intellectual property rights is inadequate to prevent use or misappropriation by third parties,

the value of our brand and other intangible assets may be diminished and competitors may be able to more

effectively mimic our models, platform, and applications and methods of operations. In addition, due to the

significant amount of discovery required in connection with intellectual property litigation, our confidential

information may be compromised by disclosure during litigation. Any of these events would have an adverse

effect on our business, financial condition, and results of operations.

Our future success and competitive position depend in part upon our ability to obtain or maintain certain

intellectual property rights used in our models, platform, and applications. While we have issued patents and

have patent applications pending, we may be unable to obtain patent protection for the technology covered in

our patent applications. In addition, we cannot ensure that any of the patent applications will be granted or that

the claims allowed on any issued patents will be sufficiently broad to protect our technology or models,

platform, and applications and provide us with competitive advantages. Further, any issued patents may be

challenged, invalidated, or circumvented by third parties.

Many patent applications in the United States may not be public for a period of time after they are filed, and

since publication of discoveries in the scientific or patent literature tends to lag behind actual discoveries by

several months, we cannot be certain that we will be the first creator of inventions covered by any patent

application we make or that we will be the first to file patent applications on such inventions. Because some

patent applications may not be public for a period of time, there is also a risk that we could adopt a technology

without knowledge of a pending patent application, which technology would infringe a third-party patent once

that patent is issued.

We also rely on unpatented proprietary technology. It is possible that others will independently develop the

same or similar technology or otherwise obtain access to our unpatented technology. To protect our trade

secrets and other proprietary information, our policy requires employees, consultants, and independent

contractors to enter into confidentiality agreements. We cannot guarantee that these agreements will provide

sufficient protection for our trade secrets, know-how, or other proprietary information in the event of any

unauthorized use, misappropriation, or disclosure of such trade secrets, know-how, or other proprietary

information, or that the employee, consultant or independent contractor will not breach their confidentiality

agreements with us. If we are unable to maintain the proprietary nature of our technologies, our business could

be adversely affected.

We also rely on our trademarks, trade names, and brand names to distinguish our models, platform, and

applications from the products of our competitors and have registered or applied to register many of these

trademarks in the United States and certain countries outside the United States. However, occasionally third

parties have registered and acquired, and may in the future register or acquire, common law rights in identical

or similar marks for products or solutions that also address similar markets to our own and have tried to

enforce such rights. As we rely in part on brand names and trademark protection to enforce our intellectual

property rights, efforts by third parties to limit use of our brand names or trademarks and barriers to the

registration of brand names and trademarks in various countries may restrict our ability to promote and

maintain a cohesive brand throughout our key markets. There can also be no assurance that pending or future

U.S. or non-U.S. trademark applications will be approved in a timely manner or at all, or that such registrations

will effectively protect our brand names and trademarks. Additionally, third parties have opposed, and may in

the future oppose, our trademark applications or otherwise challenge our use of the trademarks. In the event

that our trademarks are successfully challenged, we could be forced to rebrand our models, platform, and

applications, which would result in loss of brand recognition and would require us to devote resources to

advertising and marketing new brands. Although we take measures to protect our property, if we are unable to

prevent the theft of our intellectual property or its exploitation, the value of our investments may be

undermined and our business, financial condition, and results of operations may be adversely affected.

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We incorporate open-source software in our models, platform, and applications, which may

subject us to litigation or other requirements, each of which may adversely affect our

business, financial condition, and results of operations.

A portion of the technologies we use in our models, platform, and applications incorporates open-source

software, and we may incorporate open-source software in our models, platform, and applications in the future.

From time to time, companies that use third-party open-source software have faced claims challenging the use

of such open-source software and their compliance with the terms of the applicable open-source license. We

may be subject to suits by parties claiming ownership of what we believe to be open-source software or claiming

non-compliance with the applicable open-source licensing terms. Some open-source licenses require end-users

who distribute or make available across a network software that includes open-source software to make

available all or part of such software (which may include valuable proprietary code), at no cost, or license such

software under the terms of the particular open-source license. While we employ practices designed to help

ensure our compliance with the licenses of third-party open-source software and protect our valuable

proprietary source code, we may inadvertently use third-party open-source software in a manner that exposes

us to claims of non-compliance with the applicable terms of such license, including claims for infringement of

intellectual property rights or for breach of contract. These risks may be heightened by our use of our own AI

tools, including Claude Code, in our software development processes, as AI-generated code could incorporate or

reproduce open-source software such that the associated license obligations, including copyleft requirements to

disclose or license proprietary source code, apply to us without our knowledge. Similar concerns regarding AI-

generated code could also lead enterprise customers to limit their use of our products. Further, there is an

increasing number of open-source software license types, almost none of which have been tested in a court of

law, resulting in a dearth of judicial guidance regarding the proper legal interpretation of such license types. If a

third party makes a claim against us alleging that we have not complied with the conditions of the applicable

open-source license, we could incur significant legal expenses defending against such allegations, expend

substantial time and resources to re-engineer some or all of our software, and could be subject to significant

damages, enjoined from the sale of our models, platform, and applications that contained the open-source

software, and required to comply with the conditions of the open-source license, which may include the public

release of certain portions of our proprietary source code, each of which may have an adverse impact on our

business, financial condition, and results of operations.

In addition to risks related to license requirements, use of open-source software can lead to greater risks than

use of third-party commercial software because open-source licensors generally do not provide warranties or

other contractual protections regarding misappropriation, misuse, infringement, ownership, misattribution, or

other violations, the quality of the code, or the origin of the open-source software. Many of the risks associated

with the use of open-source software cannot be eliminated and may adversely affect our business, financial

condition, and results of operations. For instance, open-source software is developed by programmers beyond

our control and may have security vulnerabilities, defects, or errors of which we may not be aware. Even if we

become aware of any such vulnerabilities, defects, or errors, it may take a significant amount of time for either

us or the relevant programmers to address such vulnerabilities, defects, or errors. Such a delay may negatively

impact our models, platform, and applications, including by adversely affecting the market’s perception of our

models, platform, and applications, impairing the functionality of our models, platform, and applications, or

delaying the launch of new features or functionality on our models, platform, and applications, any of which

may adversely affect our business, financial condition, and results of operations.

We currently, and may in the future, license technology from third parties for use in our

models, platform, and applications, and our inability to maintain those licenses could

adversely affect our business, financial condition, and results of operations, and our use of

such third-party technology could subject us to litigation.

We currently incorporate, and may in the future incorporate, technology that we license from third parties into

our models, platform, and applications. If we are unable to obtain or continue to use or license these

technologies on reasonable terms, or if these technologies become unreliable, unavailable, or fail to operate

properly, we may not be able to secure adequate alternatives in a timely manner or at all, and our ability to offer

our models, platform, and applications and remain competitive in our market would be harmed. Further,

licensing technologies from third parties exposes us to increased risk of being the subject of intellectual

property infringement claims and vulnerabilities due to, among other things, our lower level of visibility into

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the development process with respect to such technology and the care taken to safeguard against risks. We

cannot be certain that our licensors do not or will not infringe on the intellectual property rights of third parties

or that our licensors have or will have sufficient rights in the licensed technology or related intellectual property

rights in all jurisdictions in which we may sell or offer our models, platform, and applications. Some of our

agreements with our licensors may be terminated by them or otherwise provide for a limited term. If we are

unable to continue to license technology because of intellectual property infringement claims brought by third

parties against our licensors or against us, or if we are unable to continue our license agreements or enter into

new licenses on commercially reasonable terms, our ability to develop and sell our models, platform, and

applications containing or dependent on that technology would be limited, and our business, financial

condition, and results of operations could be adversely affected.

Additionally, if we are unable to license technology from third parties, we may be forced to acquire or develop

alternative technology, which we may be unable to do in a commercially feasible manner, or at all, and may

require us to use alternative technology of lower quality or performance standards. This could limit or delay our

ability to offer new or competitive offerings and increase our costs. Third-party software we rely on may be

updated infrequently, unsupported, or include errors or vulnerabilities that may not be resolved in a timely

manner, any of which may result in errors in our own models, platform, and applications or expose our models,

platform, and applications to vulnerabilities. Any impairment of the technologies or of our relationship with

these third parties could adversely affect our business, financial condition, or results of operations.

Our development of solutions that replace or reduce reliance on third-party vendors may

expose us to litigation and other disputes.

We develop and deploy proprietary and partner-based solutions that replace, deprecate, or reduce our reliance

on third-party vendors, including vendors that historically provided software, services, or infrastructure

supporting our business. These vendors may perceive our actions as adversely affecting their business interests

and may assert claims against us, including claims for breach of contract, intellectual property infringement

(including patents, copyrights, or trade secrets), misuse of confidential or proprietary information, tortious

interference, or unfair competition.

Such claims may be asserted regardless of their merit and could result in costly litigation, settlements,

injunctions, or restrictions on our ability to deploy or expand our models, platform, and applications.

Defending against these claims could divert management and key personnel’s attention and resources, require

significant legal expenditures, and adversely affect our business, financial condition, and results of operations.

We may be subject to claims that we or our employees have misappropriated the intellectual

property of other companies, particularly as we hire employees from other AI and technology

companies.

Our success depends in part on our ability to attract and retain highly skilled employees, including engineers,

data scientists, and researchers with experience in AI and machine learning. As competition for AI talent

continues to intensify, we have hired and may in the future hire employees who previously worked for or have

otherwise been involved with competitors or companies operating in related technology areas, and certain of

our employees have left and others may leave to work for such competitors.

These employees may have had access to proprietary or confidential information, including trade secrets, of

their former employers. Although we require employees to comply with confidentiality and intellectual property

obligations, we may nonetheless be subject to claims that we or our employees have misappropriated or

improperly used trade secrets or other intellectual property of competitors or other companies. Such claims

may be asserted even if we believe they are without merit and even in the absence of any intentional

misconduct.

Defending against these claims could be costly, time-consuming, and disruptive, and could divert management

attention and resources away from our business. In addition, such disputes could result in damages,

settlements, injunctive relief, restrictions on our ability to use certain technologies, limitations on the roles of

certain employees, or reputational harm. Any of the foregoing could adversely affect our business, financial

condition, and results of operations.

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Risks Related to Legal and Regulatory Matters

We are subject to claims, lawsuits, investigations, executive and administrative orders and

directives, other regulatory actions, and various actions and proceedings, and face potential

liability, expenses for legal claims, and harm to our business.

We are subject to claims, lawsuits, arbitration proceedings, government inquiries and investigations, executive

and administrative orders and directives, and other legal, regulatory, and administrative actions and

proceedings, including those involving intellectual property disputes, compliance with regulatory requirements,

government approvals and authorizations, labor and employment, anti-discrimination, commercial disputes,

competition, privacy, consumer protection, customer complaints, advertising, and other matters relating to our

technology, models, platform, and applications, and we may become subject to additional types of claims,

lawsuits, arbitration proceedings, government inquiries and investigations, executive and administrative orders

and directives, and other legal, regulatory, and administrative actions and proceedings as our business grows

and as we deploy new technologies, models, platforms, and applications. In particular, as our models, platform,

and applications increasingly include agentic AI systems capable of taking autonomous actions with real-world

consequences, we may face novel legal theories of liability, including intellectual property infringement,

product liability, agency, and negligence claims, that have not been tested in the context of autonomous AI

systems and for which the scope of our potential exposure is uncertain. In addition, as we expand our

healthcare and life sciences offerings, regulators may conclude that certain of our products, or our customers’

use of them, are subject to healthcare regulation or to other laws governing healthcare and health information,

which could require us to obtain authorizations, modify or restrict our offerings, or incur significant compliance

costs. Errors or other undesirable outputs from our models in these contexts could contribute to patient harm,

compromised research, or regulatory failures by our customers, and could expose us to claims from customers,

patients, and other third parties, as well as to regulatory inquiries and enforcement actions.

We are also subject to antitrust and competition law risk arising from our public advocacy regarding AI safety

and the responsible pace of AI development and from our participation in industry groups, safety

collaborations, and standard-setting initiatives. Communications, advocacy, or collaboration among companies

that develop frontier AI models, or conduct alleged to reflect coordination among such companies, may be

characterized as concerted action subject to the antitrust and competition laws, including Section 1 of the

Sherman Act and analogous state and non-U.S. laws, even where undertaken for safety purposes, conducted

publicly, or intended as advocacy for governmental action or industry standards. In September 2026, a putative

class action was filed against us and other developers of frontier AI models in the U.S. District Court for the

Northern District of California, alleging that we and the other defendants agreed to restrain competition by

slowing the pace at which we develop and improve our respective AI models, in purported violation of Section 1

of the Sherman Act. The complaint seeks treble damages, injunctive relief, and other relief on behalf of a

purported class of purchasers of the defendants’ paid consumer subscriptions. We disagree with the claims and

intend to defend the matter vigorously, but the outcome of this and any similar proceeding is inherently

uncertain.

Antitrust litigation can be complex, protracted, disruptive, and expensive, and an adverse outcome could result

in treble damages and injunctive relief. We could also become subject to additional private litigation or to

investigations or enforcement actions by the U.S. Department of Justice, the FTC, state attorneys general, or

non-U.S. competition authorities. We have proposed public efforts to work with the U.S. government and other

developers of frontier AI models to establish safety standards, including with respect to the pace of capability

development, and have suggested that such collaboration may warrant a narrow exemption or safe harbor from

antitrust laws. These proposals have drawn public opposition from political leaders, some of whom have

characterized such efforts as anticompetitive regardless of the purpose of such exemption or safe harbor. There

is no assurance that any such exemption or safe harbor will be adopted. Our advocacy for such an exemption,

and any safety commitments we pursue with other developers of frontier AI in its absence, could subject us to

additional regulatory, litigation, and other risks. These risks may cause us to limit or modify our public

advocacy, our participation in industry safety and standard-setting initiatives, and our communications with

other developers of frontier AI, which could adversely affect our ability to pursue collaborative approaches to AI

safety that we believe are important to our mission.

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The results of any such claims, lawsuits, arbitration proceedings, government inquiries and investigations,

executive and administrative orders and directives, or other legal, regulatory, and administrative actions and

proceedings cannot be predicted with any degree of certainty. Any claims, lawsuits, investigations, orders,

directives, regulatory actions, or proceedings against us, whether meritorious or not, could adversely affect our

revenue, cause potential customers to pause sales discussions, cause existing customers to delay, pause or

cancel contracts or seek to modify their contracts, undermine our ability to pursue future contracts, damage our

relationships with partners and customers, adversely affect our institutional standing, undermine investor

confidence, limit our ability to sell our models, platform, and applications in certain industries, result in costly

litigation or regulatory or other defense, adversely affect our reputation, require significant management

attention, consume significant time, and divert significant resources.

Determining reserves for our pending litigation or other disputes is a complex and fact-intensive process that

requires significant subjective judgment and speculation. It is possible that a resolution of one or more such

proceedings could result in substantial damages, settlement costs, fines, and penalties that could adversely

affect our business, financial condition, and results of operations. Because of the potential risks, expenses, and

uncertainties of litigation or other dispute resolution processes, we may, from time to time, settle disputes, even

where we have meritorious claims or defenses, by agreeing to settlement agreements, as we did, for example, in

Bartz. Moreover, as in Bartz, insurance may not fully cover such claims, provide sufficient payments to cover all

the costs to resolve one or more such claims, or continue to be available on terms acceptable to us. A claim

brought against us that is uninsured or underinsured could result in unanticipated costs. These proceedings

could also result in harm to our reputation and brand, sanctions, consent decrees, injunctions, or other orders

requiring a change in our business practices. Further, under certain circumstances, we have contractual and

other legal obligations to indemnify and to incur legal expenses on behalf of our business and commercial

partners and current and former directors and officers. Any of these consequences could adversely affect our

business, financial condition, and results of operations.

We are subject to anti-corruption and anti-bribery laws, anti-money laundering laws, and

similar laws.

We are required to comply with the United States Foreign Corrupt Practices Act of 1977, the United Kingdom

Bribery Act 2010, and other anti-corruption and anti-bribery laws, anti-money laundering laws, and similar

laws in the United States and non-U.S. countries where we have operations and conduct business. Anti-

corruption and anti-bribery laws, which have been enforced aggressively and are interpreted broadly, prohibit

companies and their employees, agents, intermediaries, and other third parties from, among other things,

promising, authorizing, making, or offering improper payments or other benefits to government officials and

other persons in the public and private sector.

We leverage third parties, including intermediaries and agents, to conduct our business and to sell our models,

platform, and applications, and in connection with lobbying and other activities. We and these third parties

have in the past and may in the future have direct or indirect interactions with officials and employees of

government agencies, including state-owned or state-affiliated entities, and we potentially could be held liable

for the corrupt or other illegal activities of third-party business partners and intermediaries, our employees,

representatives, contractors, partners, agents, and other third parties, even if we do not explicitly authorize

such parties’ activities.

We cannot ensure that our policies and procedures to address compliance with these anti-corruption and anti-

money laundering laws will be effective, or that all of our employees, representatives, contractors, partners,

agents, intermediaries, or other third parties have not taken, or will not take, actions that violate these laws, for

which we may be ultimately held liable.

As we increase our non-U.S. sales and business, our risk of violating these laws may increase. Noncompliance

with applicable anti-corruption and anti-bribery laws, anti-money laundering, and similar laws could subject us

to criminal or civil sanctions, settlements, prosecution, loss of export privileges, suspension or debarment from

U.S. government contracts, other enforcement actions, disgorgement of profits, significant fines, damages,

other civil and criminal penalties or injunctions, whistleblower complaints, adverse media coverage, and other

consequences. Any investigations, actions, or sanctions could adversely affect our reputation, business,

financial condition, and results of operations. Responding to any investigation or action could result in a

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significant diversion of management’s attention and resources and significant defense costs and other

professional fees.

Governmental trade controls, including export and import controls, sanctions, customs

requirements, and related regimes, could subject us to liability or loss of contracting

privileges or limit our ability to compete in certain markets.

Our models, platform, and applications are subject to U.S. export controls, and our current or future models,

platform, and applications may be controlled under the Export Administration Regulations administered by the

U.S. Department of Commerce or, in more limited circumstances, under the International Traffic in Arms

Regulations (the “ITAR”) administered by the U.S. Department of State. Because the capabilities of our AI

models are currently evolving rapidly through ongoing training and frequent model development, and because

the export control treatment of AI technologies under relevant laws is developing, the classification of, and

controls related to, our models, platform, applications, and technologies under these regimes is inherently

uncertain and is likely to change over time. Certain of our models, platform, and applications, and the

underlying technology and source code associated with our models, platform, and applications, may require

authorization for export, re-export, or transfer in-country, and for individuals of certain nationalities to access

such technology or source code, including within the United States.

In particular, our core models, platform, and applications leverage encryption for data protection, and some of

our future models, platform, and applications may be able to produce export-controlled software, which may

subject exports, re-exports, and transfer of such models, platform, and applications to export authorization

requirements.

Our commercially available models, platform, and applications generally can be exported without an export

license. However, some exports may require us to obtain authorization from the cognizant government agency.

In certain contexts, the provision of our models, platform, and applications may constitute export of defense

articles or defense services subject to the ITAR, which can be exported only if we obtain required export licenses

or other government authorizations. Compliance with applicable export controls may delay the introduction or

sale of our models, platform, and applications outside the United States, restrict our customers’ ability to deploy

our models, platform, and applications globally, inhibit our ability to engage in certain research and

development activities, limit the performance of our models, platform, and applications, or prohibit exports to

certain jurisdictions altogether. Such restrictions have already affected our offerings directly. For example, in

June 2026, the U.S. Department of Commerce imposed worldwide export restrictions on our Fable 5 and

Mythos 5 models. To ensure compliance, we disabled Fable 5 and Mythos 5 for all of our customers; access to

our other models was not affected. We re-deployed the Fable 5 and Mythos 5 models after we updated our

safeguards in coordination with the U.S. government and our industry partners and once the U.S. Department

of Commerce lifted its restrictions. Similar export controls could recur, could remain in place longer, or could

extend to additional models or capabilities. In addition, future updates to our safeguards or other remedial

measures may not be sufficient to obtain relief from such restrictions or relief may not be granted on a similar

timeline or at all. The restrictions imposed in June 2026 and potential restrictions in the future may also limit

our ability to recruit talent, to fully utilize our existing workforce, to continue to improve our models, and to

make our products available internationally. Any such restrictions could adversely affect our financial results;

impair the research, compute, and development investment our models represent; and cause us to lose

customers, partners, and market share, including to competitors not subject to similar restrictions.

Further, our activities are subject to economic, financial, and trade sanctions administered by the United States

and other countries. Economic, financial, and trade sanctions restrict or prohibit providing certain services and

engaging in certain transactions or other activities or dealings with individuals, entities, organizations,

governments, territories, and countries targeted by or the subject of these sanctions. These restrictions, as well

as other applicable international trade rules, are subject to change with little to no notice. In addition, U.S. law

increasingly authorizes the U.S. government to restrict or review the use of hardware, software, and services

originating from, or linked to, countries it designates as adversaries, including such technology incorporated

into the supply chains for the data centers and compute infrastructure on which we depend. Such restrictions

could narrow our choice of suppliers, delay our infrastructure projects, or increase our costs, and any

noncompliance could result in penalties, loss of contracting privileges, or reputational harm.

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We take various steps to comply with applicable export controls and sanctions, including: maintaining a global

trade policy and a supported regions policy, implementing IP-based geo-blocking controls that restrict access

from certain jurisdictions to our models, platform, and applications, conducting restricted party screening of

certain customers and vendors, and including sanctions and export compliance provisions in our customer

terms of service and vendor agreements. However, we cannot guarantee the compliance measures and internal

controls we have adopted will prevent violations of applicable export controls and sanctions. Our compliance

measures and internal controls have not always been and may not always be fully effective, and we have in the

past voluntarily disclosed, and may in the future voluntarily disclose, instances of noncompliance to the

relevant authorities. We cannot guarantee that our measures will prevent future violations or keep pace with

the changing substance, application, and interpretation of export controls and sanctions. In addition, third

parties have in the past and may in the future take action to circumvent our compliance measures and controls

in order to gain access to our products and services.

If we misclassify a product or service, export, re-export, transfer, or provide access to a product, or provide

services in violation of applicable export controls or sanctions, or otherwise fail to comply with applicable

export controls or sanctions, we could be subject to criminal or civil sanctions, settlements, prosecution, loss of

export privileges, suspension or debarment from U.S. government contracts, other enforcement actions,

disgorgement of profits, significant fines, damages, other civil and criminal penalties or injunctions,

whistleblower complaints, adverse media coverage, and other consequences. Any investigations, actions, or

sanctions could adversely affect our reputation, business, financial condition, and results of operations.

Responding to any investigation or action could result in a significant diversion of management’s attention and

resources and significant defense costs and other professional fees.

Decreased use of our models, platform, and applications by customers outside the United States or a limitation

on our ability to export, provide access to, or sell our models, platform, and applications to customers and other

parties outside the United States may cause our revenue from such unsupported jurisdictions to decline and

otherwise adversely affect our business and financial condition.

If we or our business partners or counterparties, including licensors and licensees, prime contractors,

subcontractors, sublicensors, vendors, customers, or contractors, violate export controls or sanctions, including

by failing to obtain appropriate import, export, or re-export licenses or permits, or if we fail to secure such

contractual commitments from such parties, we may also be adversely affected through reputational harm as

well as other negative consequences, including government investigations or penalties.

Negative consequences stemming from violations or apparent violations of export controls or sanctions may

include the loss of the right to sell our models, platform, and applications or services to the U.S. government, or

to other U.S. or non-U.S. public bodies, or a reduction in our ability to compete for such sales opportunities

involving government agencies or other public bodies. Further, ensuring that we are complying with applicable

export controls and sanctions regulations may be time-consuming and could result in the delay or loss of sales

opportunities in connection with particular transactions.

Also, in addition to the United States, various countries regulate the import and export of certain encryption

and other technology and have enacted laws that could limit our ability to distribute our models, platform, and

applications or could limit our customers’ abilities to implement our models, platform, and applications in

those countries. For example, following Russia’s invasion of Ukraine, the United States and other countries

imposed financial and trade sanctions and export controls against Russia, Belarus, and certain regions of

Ukraine, and the United States and other countries could impose wider sanctions and export restrictions and

take other actions should the conflict further escalate. Any new export restrictions, new legislation, changes in

sanctions, or shifting approaches in the enforcement or scope of existing regulations, or in the individuals,

entities, governments, territories, countries, or technologies targeted by or subject to such regulations could

result in decreased use of our models, platform, and applications by existing customers outside of the United

States, reduced adoption of our models, platform, and applications by new customers with non-U.S. operations,

limited expansion into new markets, and decreased revenue.

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To continue to grow our business, we will need to continue to expand internationally, and our

non-U.S. operations and sales to customers outside of the United States expose us to risks

inherent in international expansion, sales, and operations.

We are a U.S.-headquartered company with extensive U.S. operations, as well as subsidiaries and operations in

several other countries and regions, including the UK, the EU, Canada, and Asia-Pacific, and we expect that our

future growth will depend in part on expanding our operations, customer base, and market presence in

additional jurisdictions. Operating in non-U.S. markets requires significant resources and management

attention and subjects us to regulatory, economic, and political risks that are different from those in the United

States. As we continue to expand internationally, we have faced and will continue to face risks in doing business

internationally that could adversely affect our business, including:

•the need to localize and adapt our models, platform, and applications for specific countries, including

translation into foreign languages and associated expenses;

•privacy laws, export controls, sanctions, and other national security regulations that impose different

and potentially conflicting obligations with respect to how personal data is processed or require that

customer data be stored in a designated territory;

•laws in certain jurisdictions that may compel our personnel, vendors, or facility operators to provide

governmental authorities with access to our systems, data, or other information, in some cases without

notice to us and with limited means of recourse;

•national security-driven data security regulations. For example, the Department of Justice issued a

final rule, effective in April 2025, that places limitations, and in some cases prohibitions, on certain

transfers of covered data to partners, service providers, and vendors, employees, and investors located

in China or with other specified links to China (and other designated countries). We may be required to

re-examine current contracts or engage in new contract negotiations with third parties that aid in

processing data on our behalf or otherwise have access to covered data. These rules also may broadly

require us to extract promises from other third-party service providers that they will not transfer data

we share with them onward to parties linked to countries of concern;

•import regulations, including U.S. and non-U.S. governments’ restrictive trade policies, customs duties

and other parallel regulations, tariffs and counter-measures;

•AI, data-related, cybersecurity and digital service laws and regulations (such as the EU AI Act, NIS2,

the EU Digital Services Act, the UK Online Safety Act 2023, and the EU Data Act) that are rapidly

evolving, require continuous monitoring to ensure constant compliance maturity level, and often

provide for substantial penalties in the event of a violation;

•difficulties in staffing and managing non-U.S. operations, including the complexity of engaging in

various employer-of-record arrangements that are geographically dispersed, and the risk that these

arrangements, or any failure to establish local employing entities on a timely basis, may not comply

with local employment, labor, or tax laws, exposing us to fines, penalties, reclassification or back-

payment claims;

•difficulties of maintaining our culture across various jurisdictions;

•regulatory and other delays and difficulties in setting up non-U.S. operations, including delays in

forming, registering, and obtaining governmental approvals for local subsidiaries, delays in

establishing local banking, payroll, and benefits arrangements, and difficulties relating to safety of

personnel and information, any of which could delay local hiring efforts;

•the potential need for reviews by the U.S. government or non-U.S. governments of certain transactions

with non-U.S. entities;

•different pricing environments, longer sales cycles, longer accounts receivable payment cycles, and

collections issues;

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•new and different sources of competition;

•weaker protection for, and practical difficulties in enforcing, intellectual property and other legal rights

outside of the United States compared to protections available domestically;

•laws and business practices favoring local competitors;

•compliance challenges related to the complexity of multiple, conflicting, and changing governmental

laws and regulations, including copyright, employment, tax, privacy, and data protection laws and

regulations, export controls, and sanctions;

•parties outside the United States seeking to circumvent sanctions and export controls;

•increased financial accounting and reporting burdens and complexities;

•increased costs in establishing infrastructure across various jurisdictions;

•declines in the values of foreign currencies relative to the U.S. dollar;

•restrictions on the transfer of funds;

•potentially adverse tax consequences;

•the cost of and potential outcomes of any claims or litigation;

•future accounting pronouncements and changes in accounting policies;

•changes in tax laws or tax regulations; and

•regional and local economic and political conditions.

Entry into certain transactions with non-U.S. entities or persons may be subject to government regulations and

review, including review by U.S. or non-U.S. government entities related to contemplated or past foreign direct

investment (“FDI”). In recent years, many countries around the world have adopted FDI regulatory regimes

that seek to scrutinize investments into, and acquisitions of, domestic companies by non-domestic parties,

granting governments broad discretion to review contemplated and past investment and acquisition

transactions. These FDI regimes may restrict our ability to attract investments, invest in or fund partners

outside of the United States that build or operate data centers or supply infrastructure for us, or acquire

promising new technologies, companies, and talent in countries around the world, potentially limiting our

ability to carry out our business strategy.

More broadly, increasing geopolitical tensions, shifting national security priorities, and evolving technology-

focused trade, export control, investment, and data-governance regimes may result in restrictions, heightened

scrutiny, or other limitations on our ability to operate, sell products, partner with customers, or deploy our

models in certain jurisdictions or with certain counterparties. Governments may adopt or expand policies

aimed at protecting domestic technology ecosystems, restricting the cross-border flow of data, or limiting access

to AI systems, which could reduce our addressable market, increase compliance costs, or require operational

changes. In particular, the U.S. government has increasingly scrutinized AI companies’ exposure to Chinese

state actors, and future executive orders, legislation, or regulatory actions could restrict our ability to serve

customers or users connected to China, impose new compliance obligations, lead us to implement anti-abuse

mechanisms or other technical access restrictions, or limit the deployment of our models in ways that reduce

our addressable market. Any escalation of U.S.-China tensions, retaliatory measures by either government, or

failure or perceived failure by us to prevent non-U.S. state-actor access to or misuse of our technology could

subject us to regulatory action, reputational harm, and adverse effects on our business, financial condition, and

results of operations.

As we continue to expand our business globally, our success will depend, in large part, on our ability to

anticipate and effectively manage these risks. These factors and others could adversely affect our ability to

increase non-U.S. revenue and, consequently, could materially impact our business. The expansion of our

existing non-U.S. operations and entry into additional non-U.S. markets will require significant management

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attention and financial resources. Our failure to successfully manage our non-U.S. operations and the

associated risks effectively could limit the future growth of our business.

Increasing scrutiny and changing expectations from global regulations, our investors,

customers, and employees with respect to ESG may result in additional compliance risk and

costs and may impact our reputation and business.

Companies across many industries are facing increasing scrutiny related to their environmental, social, and

governance (“ESG”) practices and reporting, both in the United States and internationally. For example, new

U.S. and non-U.S. laws and regulations relating to ESG matters, including environmental sustainability and

climate change, are under consideration, being adopted, or being rolled back or revised, which may impact our

necessary disclosures and increase compliance costs. Further, there is particular focus on concerns relating to

AI and its impact on society and the environment, including the power-intensive nature of the industry, public

concern regarding high consumption of water, and reliance on critical minerals and rare elements in the

manufacture of chips. Some investors may use these non-financial performance factors to guide their

investment strategies and, in some cases, may choose not to invest in us if they believe our policies and actions

relating to ESG are inadequate.

Our sustainability initiatives, goals, or commitments could be difficult to achieve or costly to implement.

Moreover, compliance with recently adopted and potential upcoming ESG requirements, including California

legislation that requires various climate-related disclosures, the EU’s Corporate Sustainability Reporting

Directive and Corporate Sustainability Due Diligence Directive, and the UK’s Streamlined Energy and Carbon

Reporting framework will require the dedication of significant time and resources. At the same time, anti-ESG

sentiment has gained momentum across the United States, particularly at the federal level, and the federal and

certain state governments have enacted or proposed “anti-ESG” policies or legislation or have issued related

legal opinions. Such policies, legislation, initiatives, and scrutiny could expose any sustainability, employment,

governance, or other corporate practices we adopt to the risk of litigation, antitrust investigations or challenges

by federal or state authorities, and result in injunctions, penalties, and reputational harm.

Additionally, if our competitors’ corporate social responsibility performance is perceived to be better than ours,

potential or current investors may elect to invest with our competitors instead. Our business may face increased

scrutiny related to these activities and our related disclosures, including from the investment community and

the local communities in which we operate, and our failure to achieve progress or manage the dynamic, and at

times conflicting, public sentiment and legal landscape in these areas on a timely basis, or at all, could adversely

affect our reputation, business, and financial condition. Further, we may experience backlash from customers,

government entities, advocacy groups, employees, or other stakeholders who disagree with our actual or

perceived positions, or with our lack of position on social, environmental, governance, political, public policy,

economic, geopolitical, or other sensitive issues. Any perceived lack of transparency about these matters could

adversely affect our brand and reputation, our employees’ engagement and retention, and the willingness of our

customers and partners to do business with us. Both advocates and opponents to ESG-related matters are

increasingly resorting to a range of activism forms, including media campaigns and litigation, to advance their

perspectives. To the extent we are subject to such activism, it may require us to incur costs or otherwise

adversely affect our business, financial condition, or results of operations.

If we or our payment processing partners fail to manage the risks related to our payment

processing activities, we could be subject to fines, regulatory scrutiny, disruptions to our

business, or reputational harm.

A portion of our customers authorize us to bill their credit card accounts through our third-party payment

processing partners for our paid subscriptions. We have experienced, and expect to continue to experience,

fraudulent activity, including the creation of accounts using false identities and the use of stolen or otherwise

unauthorized payment credentials, which has resulted, and may in the future result, in losses, including

payment processing fees, chargeback fees, and fines and penalties imposed by our payment processors or card

networks, for which we may not be reimbursed. We maintain fraud-detection and identity-verification

measures, but these measures have not identified, and may not identify, all such activity. Further, our

customers provide us with credit card billing information online, and we do not verify the physical identity of

cardholders or conduct additional verification beyond what we collect online, which increases our risk of

exposure to fraudulent activity.

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We also incur chargebacks when customers or card issuers claim that a transaction was unauthorized or

otherwise improper. If the volume of chargebacks were to become excessive, we could be subject to higher

processing fees, additional fines, fraud mitigation requirements, or the termination or suspension of our ability

to accept certain payment methods, including credit cards, through one or more payment processors.

In addition, payment processors, card networks, and financial institutions periodically revise their rules,

standards, and practices, including data protection and documentation standards, required to utilize their

services from time to time. Our compliance with these evolving requirements, and the continued compliance of

our third-party payment processing partners, may require additional operational resources and expense.

Failure by us or our payment processing partners to comply with applicable standards could result in fines,

increased scrutiny, disruptions to our business and our ability to process payments for our intelligence service,

or reputational harm.

Risks Related to Tax and Accounting Matters

Changes in tax laws or regulations could be enacted, or existing tax laws or regulations could

be applied to us or our customers in a manner that could increase the costs of our models,

platform, and applications and adversely affect our business.

We operate in multiple jurisdictions and are subject to tax laws and regulations of U.S. federal, state, and local

and non-U.S. governments. Income, sales, use, or other tax laws, statutes, rules, regulations, or ordinances

could be enacted or amended at any time (possibly with retroactive effect) and could be applied solely or

disproportionately to models, platforms, and applications provided over the internet. These enactments or

amendments could reduce our sales activity due to the inherent cost increase the taxes would represent and

ultimately harm our results of operations and cash flows. Further, the application of U.S. federal, state, local,

and non-U.S. tax laws to services provided electronically is unclear and continuously evolving. Existing tax

laws, statutes, rules, regulations, or ordinances could be interpreted or applied adversely to us, possibly with

retroactive effect, which could require us or our customers to pay additional tax amounts, as well as fines or

penalties, and interest for past amounts. If we are unsuccessful in collecting such taxes due from our customers,

we would be held liable for such costs, thereby adversely affecting our results of operations and harming our

business.

As we expand the scale of our non-U.S. business activities, any changes in the U.S. or non-U.S. taxation of such

activities may increase our worldwide effective tax rate and harm our business, financial condition, and results

of operations. We may be subject to taxation in several jurisdictions around the world with increasingly

complex tax laws, the application of which can be uncertain. In addition, our hiring of personnel and

engagement of third-party employer-of-record providers in non-U.S. jurisdictions, as well as our data center

and other infrastructure activities outside the United States, have created, and may in the future create,

permanent establishments or other taxable presence in those jurisdictions, which could subject us to additional

income, withholding, and indirect taxes, as well as interest, penalties, and additional compliance obligations. In

advance of forming and obtaining approvals for local operating entities, we have entered into, and expect to

enter into additional letters of intent, leases, and other agreements relating to our international compute and

infrastructure activities through interim contracting arrangements with existing entities, and we may be unable

to transfer these arrangements to local entities on a timely basis or at all. Any prolonged reliance on these

interim arrangements, or any failure to migrate them to local entities, could increase our exposure to

permanent establishment or other taxable-presence determinations and could result in non-recoverable value-

added or similar indirect taxes, which could be material in certain jurisdictions. Although we have not been

required to pay income taxes, other than in immaterial amounts in certain jurisdictions to date, the amount of

taxes we pay in these jurisdictions could increase substantially as a result of changes in the applicable tax

principles, including increased tax rates, new tax laws, or revised interpretations of existing tax laws and

precedents, which could adversely affect our liquidity and results of operations. For example, a number of

countries and organizations, such as the Organisation for Economic Co-operation and Development (“OECD”),

have proposed changes to existing tax laws or new laws that could impact our tax obligations, including a

framework that imposes a 15% global minimum tax, which has been implemented into the domestic laws of

some jurisdictions in the EU, among other jurisdictions, and is being considered for implementation by other

countries. On January 5, 2026, the OECD announced a “side-by-side” elective safe harbor that exempts electing

U.S.-parented multinational entities from certain provisions of the global minimum tax for fiscal years

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beginning on or after January 1, 2026. In addition, the authorities in these jurisdictions could review our tax

returns and impose additional tax, interest, and penalties, and the authorities could claim that various

withholding requirements apply to us or our subsidiaries or assert that benefits of tax treaties are not available

to us or our subsidiaries, any of which would harm us and our results of operations.

Our business, financial condition, and results of operations may be adversely affected if we

are required to collect sales or other related taxes for subscriptions to our models, platform,

and applications in jurisdictions where we have not historically done so.

We collect sales tax in a number of jurisdictions. Sales, use, value added, digital service, and similar tax laws

and rates vary by jurisdiction. One or more states or countries may seek to impose incremental or new sales,

use, or other tax collection obligations on us. A successful assertion by a state, country, or other jurisdiction that

we should have been or should be collecting additional sales, use, or other taxes could, among other things,

result in substantial tax payments, create significant administrative burdens for us, discourage potential

customers from subscribing to our models, platform, and applications due to the incremental cost of any such

sales or other related taxes, or otherwise harm our business, financial condition, and results of operations.

Further, certain jurisdictions in which we operate have enacted a digital services tax, which is generally a tax on

gross revenue generated from users or customers located in those jurisdictions, and other jurisdictions are

considering enacting similar laws. Any successful action by taxing authorities to compel us to collect and remit

sales, use, value added, digital service, and similar tax laws, either retroactively, prospectively, or both, may

adversely affect our business, financial condition, and results of operations.

Our ability to use our net operating loss carryforwards and certain other tax attributes may

be limited.

We have incurred substantial net operating losses (“NOLs”) during our history. In general, under Sections 382

and 383 of the Internal Revenue Code of 1986, as amended (the “Code”), a corporation that undergoes an

“ownership change” is subject to annual limitations on its ability to utilize its pre-change U.S. federal NOL

carryforwards and certain other tax attributes, including tax credit carryforwards, to offset its future taxable

income or tax liabilities. For these purposes, an ownership change generally occurs if the percentage of a

corporation’s stock (by value) owned by one or more “5-percent shareholders” increases by more than 50

percentage points over a rolling three-year period. We have experienced ownership changes in the past, and we

may experience ownership changes in the future, including as a result of this offering or subsequent shifts in

our stock ownership, some of which may be outside our control. NOLs and other tax attributes of companies we

have acquired are, and of companies we may acquire may be, subject to similar limitations. Similar provisions

of state tax law and the tax laws of non-U.S. jurisdictions may also limit our ability to utilize state and non-U.S.

NOL carryforwards and other tax attributes. In addition, certain states, including California, have suspended or

otherwise limited the use of NOL carryforwards and other tax attributes, which could accelerate or permanently

increase our state income tax liabilities. Separately, under current law, U.S. federal NOLs arising in taxable

years beginning after December 31, 2017 may be used to offset only 80% of taxable income in any year, whether

or not an ownership change occurs. As a result of the foregoing, even if we attain profitability, we may be unable

to use all or a material portion of our NOLs and other tax attributes, which could adversely affect our future

cash flows and results of operations.

Our corporate structure and intercompany arrangements are subject to the tax laws of

multiple jurisdictions, and we could be required to pay additional taxes, which could

adversely affect our business, financial condition, and results of operations.

As we continue to expand our non-U.S. operations, we are, and may increasingly be, required to report taxable

income in various jurisdictions around the world based on our business activities in those jurisdictions. Our

corporate structure and associated transfer pricing policies reflect the functions, risks, and assets of the entities

involved in our intercompany transactions. However, our tax position is subject to various risks, including

increases in tax rates, new or revised tax laws (which may apply retroactively), and new interpretations of

existing tax laws and policies by taxing authorities or courts, any of which could increase our overall tax

obligations.

Our intercompany transactions are subject to complex transfer pricing rules administered by tax authorities in

the jurisdictions in which we operate, many of which apply divergent, and sometimes conflicting, legal

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standards. Tax authorities may take inconsistent positions regarding the application of the arm’s-length

principle, the characterization or valuation of our intellectual property, or the pricing of intercompany services

and other transactions. If a tax authority successfully challenges our transfer pricing or the allocation of income

and expenses among jurisdictions, we could be required to reallocate income or pay additional taxes, interest,

and penalties. If the jurisdiction from which income is reallocated does not agree with the adjustment, we could

also be subject to double taxation. In addition, certain of our cross-border contracting arrangements, including

infrastructure-related agreements entered into by U.S. entities pending the formation of local subsidiaries, may

give rise to non-recoverable value-added or similar indirect taxes or other tax costs, which could be material

depending on the jurisdiction.

Although we believe our tax positions are reasonable, our tax reserves are adequate, and our transfer pricing

practices reflect arm’s-length terms, tax authorities may disagree with our assumptions, judgments, and

estimates. If a tax authority were to prevail in asserting that our intercompany arrangements do not satisfy

applicable transfer pricing requirements, we could be required to pay additional taxes, interest, and penalties

that exceed our reserves. Such an outcome could increase our effective tax rate, reduce our cash flows, and

adversely affect our ability to achieve and sustain profitability.

If our judgments or estimates relating to our critical accounting policies prove to be incorrect,

our results of operations may be adversely affected.

The preparation of financial statements in conformity with GAAP requires management to make judgments in

applying our accounting policies and to make estimates and assumptions that affect the amounts reported on

our consolidated financial statements and accompanying notes. We base our estimates in part on historical

experience, market observable inputs, if available, and various other assumptions that we believe to be

reasonable under the circumstances, as provided in the section titled “Management’s Discussion and Analysis

of Financial Condition and Results of Operations—Critical Accounting Estimates.” Significant accounting

policies, estimates, and assumptions used in preparing our consolidated financial statements include, but are

not limited to, revenue recognition, stock-based compensation, common stock valuations, fair value of

convertible notes, derivative liabilities, and SAFEs, leases, income taxes, and loss contingencies. In addition, we

engage in complex and novel transactions and may be required to consolidate certain assets or entities on our

financial statements, which may involve significant judgment and could result in volatility in our reported

results of operations. Our results of operations may be adversely affected if our assumptions change or if actual

circumstances differ from those in our assumptions, which may cause our results of operations to fall below the

expectations of securities analysts and investors and cause a decline in the market price of our Class A common

stock.

If we fail to maintain an effective system of disclosure controls and internal control over

financial reporting, our ability to produce timely and accurate financial statements or comply

with applicable regulations may be impaired, which may adversely affect our business,

financial condition, and results of operations.

As a public company, we will be subject to the reporting requirements of the Exchange Act, the Sarbanes-Oxley

Act, and the listing standards of the Nasdaq Global Select Market. The Sarbanes-Oxley Act and related

Exchange Act rules require, among other things, that we maintain effective disclosure controls and procedures

and internal control over financial reporting. We are continuing to develop and refine our disclosure controls

and other procedures that are designed to assure that information required to be disclosed by us in the reports

that we will file with the SEC is recorded, processed, summarized, and reported within the time periods

specified in SEC rules and forms and that information required to be disclosed in reports under the Exchange

Act is accumulated and communicated to management, including our principal executive and financial officers,

to allow timely decisions regarding disclosure. We are also continuing to improve our internal control over

financial reporting. We have expended, and anticipate that we will continue to expend, significant resources to

maintain and improve the effectiveness of our disclosure controls and procedures and internal control over

financial reporting.

Our current controls and any new controls that we develop may become inadequate because of changes in the

conditions in our business. Further, weaknesses in our disclosure controls, procedures, or internal control over

financial reporting may be discovered in the future. Any failure to develop or maintain effective controls, or any

difficulties encountered in their implementation or improvement, may adversely affect our results of operations

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or cause us to fail to meet our reporting obligations and may result in a restatement of our financial statements

for prior periods. We also rely on distribution partners and other third-party service providers to process and

store data underlying our financial reporting. Our ability to maintain effective internal controls therefore

depends in part on the design and operating effectiveness of controls maintained by these third parties, and our

ability to audit or remediate deficiencies in such third-party control environments is limited.

Any failure to implement and maintain effective internal control over financial reporting may also adversely

affect the results of periodic management evaluations and annual independent registered public accounting

firm attestation reports regarding the effectiveness of our internal control over financial reporting that we will

eventually be required to include in our periodic reports that will be filed with the SEC. Ineffective disclosure

controls and procedures and internal control over financial reporting may also cause investors to lose

confidence in our reported financial and other information, which would likely adversely affect the market price

of our Class A common stock. In addition, if we are unable to continue to meet these requirements, we may not

be able to remain listed on the Nasdaq Global Select Market. We are not currently required to comply with the

SEC rules that implement Section 404 of the Sarbanes-Oxley Act and are therefore not required to make a

formal assessment of the effectiveness of our internal control over financial reporting for that purpose. As a

public company, we will be required to provide an annual management report on the effectiveness of our

internal control over financial reporting commencing with our second annual report on Form 10-K.

We are exposed to fluctuations in interest rates and currency exchange rates, which could

negatively affect our business, financial condition, and results of operations.

We hold a significant amount of cash, cash equivalents, and investments, a substantial portion of which is

invested in instruments with variable or market-based interest rates. As a result, our investment income is

sensitive to changes in prevailing interest rates. A decline in interest rates could reduce the income we earn on

these investments, which could adversely affect our financial condition and results of operations. In addition,

volatility in interest rates may impact the fair value of our investment portfolio and could affect our overall

financial performance.

Our sales are currently denominated in U.S. dollars, euros, and the pound sterling, and will likely be

denominated in other currencies in the future. Because we report our results of operations and revenue in U.S.

dollars, we are exposed to foreign currency translation risk and may in the future face additional foreign

currency risks. For example, a strengthening of the U.S. dollar compared to these foreign currencies could

increase the real cost of our models, platform, and applications to non-U.S. customers, which could reduce

demand for our models, platform, and applications and adversely affect our results of operations. In addition,

as our non-U.S. operations expand, an increasing portion of our operating expenses may be denominated in

foreign currencies and subject to fluctuations due to changes in foreign currency exchange rates. If we are not

able to effectively manage these risks, including through any hedging activities, our financial condition and

results of operations could be adversely affected.

Risks Related to our Governance Structure

Our capital stock structure features certain provisions that are novel or otherwise not

common among other corporations with multiple-class structures, and may effectively

eliminate the ability of holders of our Class A common stock to influence important decisions,

including a change in control.

We have a novel capital and corporate governance structure that has no direct public company precedent. We

are incorporated as a PBC under Delaware law. As a PBC, we are required to balance the pecuniary interests of

our stockholders, the best interests of those materially affected by our conduct, and the Company Purpose

identified in our amended and restated certificate of incorporation. In addition, the LTBT possesses certain

rights that are designed to help ensure that we are managed in a manner that responsibly balances our goals as

a PBC. Through a special class of common stock, Class T common stock, the LTBT generally has the authority to

elect and remove the Class T directors, who together will constitute a majority of the authorized members of our

board of directors. See the section titled “Our Governance Structure and Its Goals—Long-Term Benefit Trust—

Election and Removal of Directors” for more information. The LTBT is intended to operate as an independent

body of five financially disinterested Trustees, and our Class T common stock has no economic rights. As a

result, the LTBT may have interests that differ from yours, and it may exercise its power in a way with which

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you disagree or in a way that may be adverse to your interests. Immediately prior to the completion of this

offering, we will also issue a single share of Class F common stock, a special class of our common stock, to the

Founder LLC. Our Class F common stock will be entitled to an aggregate number of votes that equals 50.1% of

the total voting power of our outstanding shares of capital stock as of the applicable record date with respect to

matters submitted to stockholders generally, including the election of our directors other than the Class T

directors. Upon the completion of this offering, we will also authorize a special class of our common stock, Class

E common stock, which we will issue to our employees, excluding our co-founders. Our Class E common stock

will be entitled to vote only on certain limited matters and will not have any economic rights. Under this

governance structure, we expect that the LTBT and the Founder LLC will collectively have the ability to elect all

members of our board of directors, and the Founder LLC will have the ability to determine the outcome of all

matters submitted to a vote of our stockholders generally for the foreseeable future. Accordingly, holders of our

Class A common stock generally will not be able to affect the outcome of any matter submitted to a vote of our

stockholders or the election of our directors, regardless of how they vote, unless a majority of the Continuing

Founders (as defined below) cannot agree on how our Class F common stock will be voted (in which case our

Class F common stock will generally be voted proportionately with the votes of our Class A common stock cast

on the matter).

Our governance structure is likely to have the effect of limiting the likelihood of an unsolicited merger proposal,

unsolicited tender offer, or proxy contest for the removal of directors. As a result, our governance structure may

make it more difficult to replace our directors and management and may have the effect of depriving our

stockholders of an opportunity to sell their shares at a premium over prevailing market prices.

We cannot predict whether our structure will result in lower demand for our Class A common stock, increased

volatility, adverse publicity, or other adverse consequences. In particular, the absence of judicial precedent

interpreting this structure increases the risk and unpredictability of governance-related litigation, and courts

may interpret the obligations inherent in our structure in ways that we might not anticipate.

Our capital structure will concentrate voting power with the LTBT and the Founder LLC for

the foreseeable future and will result in the LTBT and the Founder LLC having voting power

that is not derived from or proportionate to economic interests in our company.

Our Class T common stock will generally entitle the LTBT to elect and remove the Class T directors, who

together will constitute a majority of the authorized members of our board of directors. Our Class T common

stock will remain outstanding indefinitely, subject to the right of our board of directors and the Trustees or

specified majorities of our Class A common stock, Class E common stock, and Class F common stock to amend

or terminate the terms of the LTBT or the rights of our Class T common stock or to redeem our Class T common

stock (such time as no share of Class T common stock is outstanding, the “Class T Sunset Time”). The Class T

common stock may also be transferred without restriction upon the receipt of the same approvals required to

amend, terminate, or redeem it. We intentionally structured the Class T common stock in this manner to

preserve long-term flexibility if circumstances change. If the Class T common stock were transferred to a person

or entity that is not affiliated with the LTBT or is not otherwise required to consider the Company Purpose, for

so long as we remain a PBC, all of our directors, regardless of how they are elected, would continue to be

obligated to act in accordance with Delaware law and our certificate of incorporation, bylaws, and other

governing documents as then in effect, including those provisions relating to our public benefit purpose. The

Trust Agreement (as defined below) limits Trustee compensation to a reasonable cash amount fixed annually by

the Trustees. Trustee compensation will not vary with or be conditioned upon the profits or any action or

inaction of our company. The policies of the LTBT prohibit a Trustee from directly purchasing or holding any of

our securities.

Our Class F common stock will entitle the Founder LLC to an aggregate number of votes that equals 50.1% of

the total voting power of our outstanding shares of capital stock as of the applicable record date with respect to

matters submitted to stockholders generally, including the election of our directors other than the Class T

directors. Our Class F common stock will remain outstanding until the earlier of (i) the completion of the Class

F Transition Period (as defined below), which will commence when there have been fewer than three

Continuing Founders (not including any successor member who is a “Non-Qualifying Member” as defined in

the Founder LLC limited liability company agreement) (the “Founder LLC Agreement”) for 90 consecutive

calendar days and (ii) the time when there is no Class F common stock outstanding, including as a result of a

redemption thereof agreed to by a Supermajority (as defined below) of the Continuing Founders or upon the

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dissolution of the Founder LLC (the “Class F Sunset Time”). Upon the completion of this offering, our co-

founders will collectively hold approximately (i)           % of the total voting power of our outstanding capital

stock with respect to matters submitted to stockholders generally, excluding through their interests in the

Founder LLC, and (ii)           % of the total voting power of our outstanding capital stock with respect to matters

submitted to stockholders generally, including through their interests in the Founder LLC.

The voting power of the LTBT and the Founder LLC are not derived from or proportionate to economic

interests in our company and will not be subject to dilution or the loss of rights upon the issuance of additional

shares of Class A common stock (including upon conversion of any Class N common stock) or any other shares

of our capital stock. Moreover, the LTBT, Founder LLC, and our individual co-founders may have interests that

differ from yours and may vote in a way with which you disagree and that may be adverse to your interests. For

example, while the LTBT, Founder LLC, and our co-founders share a long-term commitment to our mission

that may benefit stockholders who share our public benefit goals, the separation between voting power and

economic interests may result in such persons exercising their influence in a manner that prioritizes actions or

outcomes they believe to be consistent with the Company Purpose and the best interests of those materially

affected by our conduct over the pecuniary interests of our other stockholders. This divergence of voting power

from economic interests in our company is likely to persist for the foreseeable future and will not be subject to

dilution based on additional issuances of our capital stock or reduction for sales or dispositions of our capital

stock by our individual co-founders. For additional information about the circumstances in which our Class T

common stock and Class F common stock could be redeemed, see the section titled “Description of Capital

Stock—Common Stock—Redemption.”

Our governance structure and the adoption of our amended and restated certificate of

incorporation may negatively affect the decision by certain institutional investors to

purchase or hold shares of our Class A common stock.

Certain aspects of our governance structure, such as our multi-class capital structure, may limit the ability of

certain institutional investors to invest in us as a result of their investment policies or may make such an

investment less attractive to the portfolio managers of certain institutional investors.

In addition, our multi-class capital structure may make us ineligible for inclusion in indices, and as a result,

mutual funds, exchange-traded funds, and other investment vehicles that attempt to passively track these

indices would not invest in our stock. These policies may depress our valuation compared to those of other

similar companies that are able to be included in such indices.

We are considered a “controlled company” within the meaning of the Nasdaq Global Select

Market corporate governance requirements, and, as a result, we qualify for, and currently

rely on, exemptions from certain corporate governance requirements.

We are considered a “controlled company” within the meaning of the Nasdaq Global Select Market corporate

governance requirements because the LTBT, as the sole holder of our Class T common stock, generally has the

power to elect a majority of the authorized members of our board of directors. As a result, we may elect not to

comply with certain corporate governance requirements, including:

•the requirement that a majority of our board of directors consist of independent directors;

•the requirement that our board of directors have a nominating and corporate governance committee

that is comprised entirely of independent directors with a written charter addressing the committee’s

purpose and responsibilities; and

•the requirement that we have a compensation committee that is comprised entirely of independent

directors with a written charter addressing the committee’s purpose and responsibilities.

If we elect not to comply with certain requirements, you will not have the same protections afforded to

stockholders of companies that are subject to all of the Nasdaq Global Select Market corporate governance

requirements. Although we qualify as a “controlled company,” we do not expect to rely on this exemption except

with respect to our NGC, which will not consist entirely of independent directors. Our board of directors

currently consists of a majority of independent directors and our audit and compensation committees currently

consist entirely of independent directors. In the event that we cease to be a “controlled company” and our Class

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A common stock continues to be listed on the Nasdaq Global Select Market, we will be required to comply with

the provision that our NGC be comprised entirely of independent directors within the applicable transition

period.

We operate as a Delaware public benefit corporation. As a public benefit corporation, we

cannot provide any assurance that we will achieve our Company Purpose.

As a PBC, we are intended to produce a public benefit or benefits and to operate in a responsible and

sustainable manner, balancing our stockholders’ pecuniary interests, the best interests of those materially

affected by our conduct, and the Company Purpose identified in our amended and restated certificate of

incorporation. We cannot assure you that we will achieve our Company Purpose or that the expected positive

impact from being a PBC will be realized, which could adversely affect our reputation, business, financial

condition, and results of operations. As a PBC, we are required, under Section 366 of the Delaware General

Corporation Law (“DGCL”) and pursuant to our amended and restated bylaws, to disclose to stockholders a

report at least biennially on our overall performance in promoting the public benefit identified in our amended

and restated certificate of incorporation and the best interests of those materially affected by our conduct and

on our assessment of our success in achieving our Company Purpose and in promoting those interests. If we are

not timely or are unable to provide this report, or if the report is not viewed favorably by parties doing business

with us, regulators, others reviewing our credentials, or other stakeholders, including holders of our Class A

common stock, our reputation as a PBC may be adversely affected.

Our focus on the long-term best interests of our company as a PBC, and the duty of our

directors to balance the pecuniary interests of our stockholders, the best interests of those

stakeholders materially affected by our conduct, and our Company Purpose, may conflict

with short-, medium-, or long-term financial interests and business performance, which may

negatively impact the value of our Class A common stock.

We have made, and may in the future make, decisions that we believe balance the pecuniary interests of our

stockholders, the best interests of those materially affected by our conduct, and the Company Purpose set forth

in our amended and restated certificate of incorporation, even if such decisions may negatively impact the

short-, medium-, or long-term performance of our business, financial condition, and results of operations or the

short-, medium-, or long-term performance of our Class A common stock. This may impact the value of our

Class A common stock and make owning our Class A common stock less appealing to investors who are focused

on returns. Our decisions and actions in pursuit of long-term success may not result in the long-term benefits

we expect, which could adversely affect our business, financial condition, and results of operations, as well as

the market price of our Class A common stock. Such decisions and actions may include changes to our models,

platform, and applications; limitations on certain uses of our models, platform, and applications; moderating

the pace of the development of our models for safety-related reasons; adjustments to the timing of new

offerings; changes in how we deliver customer support; investments in our relationships with partners and

employees; investments in and introductions of new models, platforms, and applications; investments in social

impact initiatives consistent with our public benefit objectives; and changes in our approach to working with

local or national jurisdictions on laws and regulations governing our business.

Our policies, including those on usage, currently prohibit, or may be revised in the future to prohibit, certain

usage or other actions, which may have adverse commercial consequences to us. For example, our usage policy

prohibits the use of our models, platform, and applications to develop or operate fully autonomous weapons or

to conduct mass surveillance, including mass domestic surveillance, and we have declined to permit such uses

based on our Company Purpose, notwithstanding the revenue those or similar uses could generate. Maintaining

these limitations has had, and may continue to have, adverse commercial and financial consequences. We have

also restricted or delayed the availability of certain capabilities for safety reasons. For example, we initially

released our Mythos model only as a gated research preview through Project Glasswing rather than making it

broadly available to the public. Similarly, we have chosen not to develop certain commercially attractive

offerings, such as image and video generation models, in order to direct our compute toward our research and

safety priorities. Our public advocacy, and the decisions we make to moderate the pace of AI development,

delay or restrict the release of models or features, or forgo commercial opportunities for safety-related reasons,

may not maximize stockholder value, could have a negative impact on the value of our Class A common stock,

and could result in litigation. Each of these decisions reflects our directors’ balancing of the pecuniary interests

of our stockholders, the best interests of those materially affected by our conduct, and the Company Purpose.

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While we believe these decisions are consistent with the Company Purpose, as a result of these decisions, we

may forgo revenue, customers, or growth opportunities that a corporation managed solely to maximize

stockholder value might pursue.

Further, while directors of traditional corporations typically have a fiduciary duty to focus on maximizing

stockholder value, directors of a PBC have a duty to consider not only the stockholders’ financial interests but

also the company’s specific public benefit purpose and the best interests of those stakeholders materially

affected by the company’s actions. Thus, our directors are not merely permitted, but obligated, to consider our

Company Purpose and the interests of other stakeholders. Under Delaware law, directors are shielded from

liability for breach of these obligations if they make informed and disinterested decisions that serve a rational

purpose. In the event of a conflict among the interests of our stockholders, our Company Purpose or the

interests of our other stakeholders, our directors must only make informed and disinterested decisions that

serve a rational purpose; thus, we cannot guarantee that such a conflict would be resolved in favor of our

stockholders’ monetary interests, which could adversely affect our business, financial condition, and results of

operations and cause the market price of our Class A common stock to decline. In addition, there is very limited

judicial precedent interpreting the balancing requirement applicable to PBCs under Delaware law, particularly

for companies with significant scale or visibility, or with a scope of PBC purpose similar to ours. As a result, the

scope of directors’ obligations, the standards by which their decisions may be reviewed, and the nature and

availability of stockholder remedies in connection with alleged failures to responsibly balance these interests

remain uncertain. Future judicial interpretations of these provisions could be more expansive than we currently

anticipate and could result in increased litigation risk, greater scrutiny of board decision-making, or outcomes

that differ from our expectations.

Additionally, as a PBC, we are less vulnerable to an unsolicited takeover effort than a traditional company

would be and, therefore, your ability to realize your investment through an acquisition may be limited. We may

also not be an attractive target for activists or hedge fund investors because new directors must consider and

give appropriate weight to the pecuniary interests of our stockholders, the best interests of those materially

affected by our conduct, and our Company Purpose, and stockholders may be able to enforce this obligation

through litigation. Further, by requiring that our board of directors consider additional stakeholders and our

Company Purpose, and not just maximizing stockholder value, Delaware law could make it easier for our board

of directors to reject a hostile bid, even where the acceptance of such a bid would provide the greatest short-

term financial yield to investors.

In addition, we intend to direct a meaningful portion of our resources toward our public benefit initiatives,

which may include contributions to nonprofit organizations, research institutions, underserved communities,

and other third parties that may not otherwise have access to frontier AI capabilities. These initiatives, which

include the Initial Public Benefit Issuance and the future Public Benefit Issuances, have been, and may continue

to be, substantial in scale, and we expect to significantly grow these efforts over time. The benefits of such

expenditures may be difficult or impossible to measure in financial terms and may not result in any direct or

measurable benefit to our business or our stockholders. The amount of resources directed toward these

initiatives may, in any given period, reduce our revenue, increase our expenses, and could otherwise affect our

results of operations.

As a Delaware public benefit corporation, we may be subject to increased litigation

concerning our board of directors’ obligation to balance our stockholders’ pecuniary

interests, the best interests of those materially affected by our conduct and our Company

Purpose, the occurrence of which may have an adverse impact on our business, financial

condition, and results of operations.

Section 367 of the DGCL provides that stockholders of a Delaware PBC with shares listed on a national

securities exchange may only file an action to enforce the statutory balancing requirement imposed on the

board of directors by the DGCL if they, individually or collectively, own the lesser of at least two percent of the

corporation’s outstanding shares or shares of the corporation with a market value of at least $2,000,000 as of

the date the action is instituted and, in the case of a derivative action, such stockholders satisfy any other

conditions applicable to filing a derivative action. This potential liability for enforcement of the statutory

balancing requirement does not exist for traditional corporations. Therefore, we may be subject to the

possibility of increased litigation, which would require the attention of our management, and, as a result, may

adversely affect our management’s ability to effectively execute our strategy. There is limited judicial precedent

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for this type of balancing litigation, which may create uncertainty around the scope of our directors’ obligations

or the remedies available to stockholders. Additionally, any such litigation may be costly, which may adversely

affect our business, financial condition, and results of operations.

Our amended and restated bylaws will designate a state or federal court located within the

State of Delaware as the exclusive forum for substantially all disputes between us and our

stockholders, and also provide that the federal district courts will be the exclusive forum for

resolving any complaint asserting a cause of action arising under the Securities Act of 1933, as

amended, each of which may limit our stockholders’ ability to choose the judicial forum for

disputes with us or our directors, officers, stockholders, or employees.

Our amended and restated bylaws, which will become effective immediately prior to the completion of this

offering, will provide that, unless we consent in writing to the selection of an alternative forum, the Court of

Chancery of the State of Delaware (or, if the Court of Chancery of the State of Delaware does not have

jurisdiction, another State court in Delaware or the federal district court for the District of Delaware) will, to the

fullest extent permitted by law, be the sole and exclusive forum for (i) any derivative action or proceeding

brought on our behalf, (ii) any action asserting a claim of breach of a fiduciary duty owed by any of our current

or former directors, stockholders, or officers or other employees to us or our stockholders, (iii) any action

arising pursuant to any provision of the DGCL, or as to which the DGCL confers jurisdiction upon the Court of

Chancery of the State of Delaware, (iv) any action arising pursuant to or to interpret, apply, enforce or

determine the validity of our amended and restated certificate of incorporation, or our amended and restated

bylaws, or (v) any action asserting a claim governed by the internal affairs doctrine, except for, in all cases, any

claim as to which such court determines that there is an indispensable party not subject to the jurisdiction of

such court (and the indispensable party does not consent to the personal jurisdiction of such court within 10

days following such determination).

Section 22 of the Securities Act of 1933, as amended (the “Securities Act”), establishes concurrent jurisdiction

for federal and state courts over Securities Act claims. Accordingly, both state and federal courts have

jurisdiction to hear such claims. To prevent having to litigate claims in multiple jurisdictions and the threat of

inconsistent or contrary rulings by different courts, among other considerations, our amended and restated

bylaws will also provide that, unless we consent in writing to the selection of an alternative forum, the federal

district courts of the United States will, to the fullest extent permitted by applicable law, be the sole and

exclusive forum for resolving any complaint asserting a cause or causes of action arising under the Securities

Act against any person in connection with any offering of our securities, including, without limitation, any

auditor, underwriter, expert, control person, or other defendant. Unless we consent in writing to the selection of

an alternative forum, the United States District Court for the District of Delaware will, to the fullest extent

permitted by applicable law, be the sole and exclusive forum for the resolution of any derivative action or

proceeding brought to enforce any duty or liability created by the Exchange Act or the rules or regulations

thereunder. All other claims arising under the Exchange Act may be brought in any federal court of competent

jurisdiction.

Any person or entity purchasing, holding, or otherwise acquiring any interest in any of our securities shall be

deemed to have notice of and consented to the foregoing bylaw provisions. Although we believe these exclusive

forum provisions benefit us by providing increased consistency in the application of Delaware law and federal

securities laws in the types of lawsuits to which each applies, the exclusive forum provisions may limit a

stockholder’s ability to bring a claim in a judicial forum of its choosing for disputes with us or our current or

former directors, officers, stockholders, or other employees, which may discourage lawsuits with respect to such

claims against us and our current and former directors, officers, stockholders, or other employees. Our

stockholders will not be deemed to have waived our compliance with the federal securities laws and the rules

and regulations thereunder as a result of our exclusive forum provisions.

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Provisions in our amended and restated certificate of incorporation and amended and

restated bylaws could make a merger, tender offer, proxy contest, or other significant

corporate transaction difficult, potentially depressing the market price of our Class A

common stock.

Our amended and restated certificate of incorporation and amended and restated bylaws, which will become

effective immediately prior to the completion of this offering, will contain a number of provisions that may

make the acquisition of our company more difficult. Such provisions will include:

•a multi-class common stock structure, which will provide the LTBT and the Founder LLC with the

ability to elect all members of our board of directors, and will provide the Founder LLC with the ability

to determine the outcome of all matters submitted to a vote of our stockholders generally (including

the approval of any merger, sale of our company, and other significant corporate transaction requiring

stockholder approval) for the foreseeable future;

•prior to the Class F Sunset Time, vacant or newly created directorships for any directors who are not

Class T directors can be filled by our board of directors in accordance with a notice from the Founder

LLC or by the holders of our Class A common stock and Class F common stock, voting together or

acting by written consent;

•prior to the Class T Sunset Time, the number of directors constituting our board of directors will be

permitted to be set only with the approval of 80% of the authorized members of our board of directors

(rounded up or down to the nearest whole number (any exact 0.5 rounding up));

•a special meeting of our stockholders may only be called by (i) our board of directors acting pursuant to

a resolution adopted by a majority of the authorized members of our board of directors; (ii) the

Chairperson of our board of directors; (iii) our Chief Executive Officer; (iv) our President; (v) following

the Class F Sunset Time, a majority of the directors who are not Class T directors; (vi) prior to the Class

F Sunset Time and only with respect to a special meeting at which holders of our Class E common stock

will be asked to vote on a proposal, the secretary of the company; or (vii) prior to the Class F Sunset

Time, the Founder LLC as the holder of our Class F common stock;

•prior to the Class F Sunset Time and the Class T Sunset Time, stockholders may act by written consent

only with respect to (i) any action to nominate, elect, or remove directors or appoint a director to fill

any vacancy or newly created directorship; (ii) any action to satisfy certain redemption and protective

provisions in our amended and restated certificate of incorporation related to our Class F common

stock, Class T common stock, and Class E common stock; and (iii) any matter in which stockholders

vote together as a single class if such matter is first approved or requested by our board of directors,

and following both the Class F Sunset Time and the Class T Sunset Time, any action required or

permitted to be taken by our stockholders must be effected at a duly called annual or special meeting of

stockholders and may not be effected by any written consent of our stockholders; notwithstanding the

foregoing, any action required or permitted to be taken by the holders of our Class E common stock

must be effected at a duly called annual or special meeting of stockholders and may not be effected by

any consent in writing by such stockholders;

•advance notice procedures required for Class A stockholders to nominate candidates for election as

directors or to bring matters before an annual meeting of stockholders;

•following the Class F Sunset Time, our board of directors will shift to having a classified board of

directors consisting of three classes of directors with staggered three-year terms;

•following the Class F Sunset Time, 66 2/3% of the voting power of our Class A common stock will be

required to amend certain provisions in our amended and restated certificate of incorporation and our

amended and restated bylaws;

•not providing for cumulative voting; and

•authorizing undesignated preferred stock, the issuance and terms of which may be established by 80%

of the authorized members of our board of directors (rounded up or down to the nearest whole number

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(any exact 0.5 rounding up)) and, prior to the Class F Sunset Time, only with the consent of the

Founder LLC as the holder of our Class F common stock.

These provisions, alone or together, could discourage, delay or prevent a transaction involving a change in

control of our company. These provisions could also discourage proxy contests and make it more difficult for

stockholders to elect directors of their choosing and to cause us to take other corporate actions they desire, any

of which, under certain circumstances, could limit the opportunity for our stockholders to receive a premium

for their shares of our Class A common stock, and could also affect the price that some investors are willing to

pay for our Class A common stock.

Risks Related to Ownership of our Class A Common Stock

There has been no prior public trading market for our Class A common stock, and an active

trading market may not develop or be sustained following this offering.

We have applied to list our Class A common stock on the Nasdaq Global Select Market under the symbol “ANT.”

However, prior to this offering, there has been no public trading market for our Class A common stock. We

cannot assure you that an active trading market for our Class A common stock will develop on such exchange or

elsewhere or, if developed, that any market will be sustained. The initial public offering price of our Class A

common stock will be determined through negotiation among us, the selling stockholders, and the

underwriters. This price will not necessarily reflect the price at which investors in the market will be willing to

buy and sell shares of our Class A common stock following this offering.

The market price of our Class A common stock may be volatile, and you may lose all or part of

your investment.

We cannot predict the prices at which our Class A common stock will trade. The initial public offering price of

our Class A common stock will be determined by negotiations among us, the selling stockholders, and the

underwriters. This price will not necessarily reflect the price at which investors in the market will be willing to

buy and sell shares of our Class A common stock following this offering. The market price of our Class A

common stock following this offering may fluctuate substantially, depending on a number of factors, many of

which are beyond our control and may not be related to our operating performance. These fluctuations may

cause you to lose all or part of your investment in our Class A common stock. Factors that may cause

fluctuations in the market price of our Class A common stock include the following:

•price and volume fluctuations in the overall stock market from time to time, including fluctuations due

to general economic uncertainty or negative market sentiment;

•volatility in the market and trading volumes of technology stocks;

•supply chain constraints, particularly those impacting compute, and new and evolving trade

regulations and tariffs, and counter-measures;

•changes in the operating performance and stock market valuations of other technology companies

generally, or those in our industry in particular;

•sales of shares of our Class A common stock by us or our stockholders, as well as the anticipation of

lock-up releases;

•rumors and market speculation involving us or other companies in our industry or related industries;

•failure of securities analysts to maintain coverage of us, changes in financial estimates by securities

analysts who follow our company, or our failure to meet these estimates or the expectations of

investors;

•actual or perceived significant data breaches involving our business;

•the financial or non-financial projections we may provide to the public, any changes in those

projections, or our failure to meet those projections;

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•third-party data published about us or other companies in our industry, whether or not such data is

accurate;

•announcements by us or our competitors of new models, platforms, or applications;

•the public’s reaction to our press releases, other public announcements, and filings with the SEC;

•fluctuations in the trading volume of shares of our Class A common stock or the size of our public float;

•short selling of our Class A common stock or related derivative securities;

•actual or anticipated changes or fluctuations in our results of operations;

•actual or anticipated developments in our business, our competitors’ businesses, or the competitive

landscape generally;

•changes in the anticipated future size or growth rate of our addressable markets;

•our issuance of shares of our Class A common stock, including as a result of the conversion of our Class

N common stock in connection with certain transfers;

•litigation or regulatory action involving us, our industry, or both, or investigations by regulators into

our operations or those of our competitors;

•developments or disputes concerning our intellectual property or other proprietary rights;

•announced or completed acquisitions of businesses or technologies, or similar strategic transactions,

by us or our competitors;

•new laws or regulations or new interpretations of existing laws or regulations applicable to our

business;

•regulatory enforcement actions or other governmental efforts affecting our models, platform, and

applications;

•changes in accounting standards, policies, guidelines, interpretations, or principles;

•major catastrophic events such as war, incidents of terrorism, pandemics, or responses to such events;

•any additions or departures of founders, board members, management, or key personnel; and

•general economic conditions and slow or negative growth of our markets.

In addition, if the market for technology stocks or the stock market in general experiences a loss of investor

confidence, the market price of our Class A common stock may decline for reasons unrelated to our business,

financial condition, or results of operations. The market price of our Class A common stock may also decline in

reaction to events that affect other companies in our industry even if these events do not directly affect us.

Accordingly, we cannot assure you of the liquidity of any trading market, your ability to sell your shares of our

Class A common stock when desired, or the prices that you may obtain for your shares of our Class A common

stock.

In the past, stockholders have initiated securities class action lawsuits against companies following periods of

stock price volatility. If the market price of our Class A common stock is volatile, we may become the target of

securities litigation. Such litigation may subject us to substantial costs, divert resources and management’s

attention, and adversely affect our business, financial condition, and results of operations.

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The issuance of additional stock in connection with financings, acquisitions, investments, our

equity incentive plans, the conversion of our outstanding convertible promissory notes, the

conversion of our outstanding Class N common stock, our public benefit initiatives, or

otherwise will dilute the interests of the holders of our Class A common stock.

Our amended and restated certificate of incorporation that will become effective immediately prior to the

completion of this offering authorizes us to issue up to an aggregate of 300,000,000,000 shares of Class A

common stock, 100,000,000,000 shares of Class N common stock, one share of Class T common stock, one

share of Class F common stock, 30,000,000,000 shares of Class E common stock, and 30,000,000,000 shares

of preferred stock, with such rights, powers, and preferences as may be determined by our board of directors

(subject to limitations in our amended and restated certificate of incorporation, which will become effective

immediately prior to the completion of this offering, or prescribed by Delaware law). Subject to compliance with

applicable rules and regulations, we may issue shares of our capital stock or securities convertible into shares of

our capital stock from time to time in connection with a financing, an acquisition, an investment, our equity

incentive plans, the conversion of our outstanding convertible promissory notes, the conversion of our Class N

common stock, our public benefit initiatives, which may include issuances of equity to third parties such as

nonprofit organizations, research institutions, or other recipients, or otherwise, including the Public Benefit

Issuances. Any such issuances may result in substantial dilution to the holders of our Class A common stock

and cause the market price of our Class A common stock to decline. For a discussion of the dilutive impact of

our Class N common stock on the holders of our Class A common stock, see the risk factor titled “A substantial

number of shares of our Class N common stock will be outstanding upon the completion of this offering, which

will dilute the voting power of the holders of our Class A common stock upon conversion.”

In addition, registration rights agreements entered into with counterparties to certain of our NPAs provide such

counterparties with rights to cause us to register for resale after this offering (i) shares of our common stock

underlying such notes, (ii) shares of Class A common stock issuable upon conversion of Class N common stock

issued upon conversion of the notes, and (iii) shares of our common stock issued in connection with certain

contractual rights to private placements concurrent with this offering. The exercise of such registration rights

could facilitate sales of large blocks of our Class A common stock into the public market, which could depress

the market price of our Class A common stock or increase its volatility.

A substantial number of shares of our Class N common stock will be outstanding upon the

completion of this offering, which will dilute the voting power of the holders of our Class A

common stock upon conversion.

Immediately prior to the completion of this offering, after giving effect to the Preferred Stock Conversion and

the Convertible Notes Conversion, we will have            shares of Class N common stock outstanding,

representing approximately           % of our outstanding capital stock prior to this offering and approximately

          % of our outstanding capital stock following the completion of this offering (in each case, excluding our

Class T common stock, Class F common stock, and Class E common stock). After giving effect to the Preferred

Stock Conversion and the Convertible Notes Conversion, Amazon and Google will each hold greater than five

percent of our outstanding capital stock. Although our Class N common stock is non-voting, their holdings

represent a significant economic interest in our company, and because our Class N common stock converts into

Class A common stock upon transfer to an unaffiliated third party, these shares could also become significant to

the voting power of our Class A common stock following any such transfer. Immediately prior to the completion

of this offering, after giving effect to the Preferred Stock Conversion and the Convertible Notes Conversion, and

immediately following the offering, Amazon will hold            shares of our Class N common stock and Google

will hold            shares of our Class N common stock. An aggregate of an additional           shares of Class N

common stock will be issuable after this offering upon conversion of remaining outstanding convertible

promissory notes, all of which are held by Amazon, that could not convert immediately prior to the completion

of this offering without exceeding the applicable ownership cap. Additional shares of Class N common stock

may also be issued following this offering pursuant to the Public Benefit Issuances, future drawdowns and

related issuances or conversions under our note purchase agreements, and certain contractual rights. See the

sections titled “Shares Eligible for Future Sale—Class N Common Stock,” “Management’s Discussion and

Analysis of Financial Condition and Results of Operations—Liquidity and Capital Resources—Convertible

Notes,” and “Business—Our Commitment to Public Benefit.”

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Although our Class N common stock is not entitled to vote, it is entitled to economic rights equivalent to those

of our Class A common stock, including the right to participate ratably with our Class A common stock in any

dividends we may declare and in distributions upon a liquidation, dissolution, or winding-up. As a result, the

shares of Class N common stock issued in connection with the completion of this offering as a result of the

Preferred Stock Conversion and Convertible Notes Conversion will dilute the economic interests, including any

dividends and any proceeds available for distribution to stockholders, of the holders of our Class A common

stock, and such shares are included together with our Class A common stock in determining net tangible book

value per share. See the section titled “Dilution.”

The shares of Class N common stock will automatically convert into an equal number of shares of Class A

common stock upon a transfer effected through: (i) a registered offering or an open market sale of such shares

or (ii) a transfer to an unaffiliated third party, subject to certain limitations described in the section titled

“Description of Capital Stock.” While held as Class N common stock, these shares are non-voting and therefore

do not impact the voting power of the holders of our Class A common stock. Upon the conversion of shares of

Class N common stock into Class A common stock, however, the resulting shares of Class A common stock will

be entitled to one vote per share and the issuance of such shares will dilute the voting power of the existing

holders of our Class A common stock. Any shares of Class N common stock that we issue in the future would

have the same effect, diluting the economic interests of the holders of our Class A common stock while

outstanding, as well as diluting their voting power upon conversion into Class A common stock.

Future issuances of our Class A common stock and Class N common stock will not dilute the

voting power of our Class F common stock.

Future issuances of our Class A common stock, including upon conversion of our Class N common stock, and

our Class N common stock will not dilute the voting power of our Class F common stock because our Class F

common stock is entitled to a fixed 50.1% of the total voting power of our outstanding shares of capital stock as

of the applicable record date with respect to matters submitted to stockholders generally. For example, if we

were to issue 1,000,000 additional shares of Class A common stock, our Class F common stock would

automatically be entitled to an incremental number of votes sufficient to cause the aggregate voting power of

our Class F common stock to equal 50.1% of the total voting power of our outstanding shares of capital stock as

of the applicable record date with respect to matters submitted to stockholders generally, or approximately

1,004,008 additional votes. Any future issuances of additional shares of Class A common stock, including upon

conversion of our Class N common stock, and Class N common stock will not be subject to approval by our

stockholders except as required by the listing standards of the Nasdaq Global Select Market.

Future sales of our Class A common stock in the public market could cause the market price of

our Class A common stock to decline.

The market price of our Class A common stock may decline due to sales of a large number of shares of our Class

A common stock in the market after this offering. The potential for such sales to occur may also depress the

market price of our Class A common stock. Following the completion of this offering, based on            shares of

our Class A common stock outstanding and            shares of Class N common stock outstanding as of September

30, 2026 (after giving effect to the Preferred Stock Conversion, Convertible Notes Conversion, Initial Public

Benefit Issuance, and RSU Settlement), we will have a total of            shares of Class A common stock

outstanding and            shares of Class N common stock outstanding. Our directors, executive officers, and the

holders of substantially all of our capital stock and securities convertible into or exchangeable for our capital

stock have entered into market standoff agreements with us or have entered or will enter into lock-up

agreements with Goldman Sachs & Co. LLC and Morgan Stanley & Co. LLC, on behalf of the underwriters,

under which they have agreed, subject to specific exceptions including specified early expiration provisions, to

certain restrictions on their ability to transfer any shares of our Class A common stock or Class N common stock

or securities directly or indirectly convertible into or exchangeable or exercisable for our Class A common stock

or Class N common stock during the period ending (i) in the case of our co-founders and certain of our

stockholders holding more than 0.5% of our fully diluted shares prior to this offering, on the earlier of (A) 6:00

AM Eastern Time on the second full trading day immediately following the public release of our quarterly

financial results for the fiscal quarter ending September 30, 2027 and (B) immediately after the close of the

trading day on the 365th day after the date of this prospectus, and (ii) in the case of all other such holders, on

the earlier of (A) 6:00 AM Eastern Time on the second full trading day immediately following the public release

of our quarterly financial results for the fiscal quarter ending March 31, 2027 and (B) immediately after the

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close of the trading day on the 180th day after the date of this prospectus. Goldman Sachs & Co. LLC and

Morgan Stanley & Co. LLC may release stockholders from the lock-up agreements, and we may, generally only

with their consent, release stockholders from the market standoff agreements, in each case prior to the end of

the applicable period. See the sections titled “Underwriting” and “Shares Eligible for Future Sale—Lock-Up and

Market Standoff Agreements” for further information about these agreements, including the specified early

expiration provisions.

As a result of these agreements and the provisions of our amended and restated investors’ rights agreement,

dated as of May 28, 2026 (our “IRA”), as described further in the section titled “Description of Capital Stock—

Registration Rights,” and subject to the provisions of Rule 144 or Rule 701 of the Securities Act, additional

shares of our Class A common stock (including shares issuable upon conversion of our Class N common stock)

will become available for sale in the public market at various times after the date of this offering, beginning on

the first trading day following the date of this prospectus. See the section titled “Shares Eligible for Future Sale”

for additional information.

Upon completion of this offering, stockholders owning an aggregate of up to            shares of our Class A

common stock (including those issuable upon conversion of our Class N common stock) will be entitled, under

our IRA, to demand registration rights. In addition, we intend to file a registration statement to register shares

reserved for future issuance under our equity compensation plans. Upon effectiveness of that registration

statement, subject to the satisfaction of applicable exercise periods and the expiration or waiver of the market

standoff agreements and lock-up agreements referred to above, the shares issued upon exercise of outstanding

stock options or settlement of RSUs will be available for immediate resale in the United States in the open

market.

In addition, our co-founders have each pledged to dedicate 80% of their personal equity in Anthropic to

philanthropic causes. These commitments are voluntary, revocable expressions of each co-founder’s

philanthropic intent and do not constitute legally binding obligations. The timing, amount, recipients,

structure, and manner of any donations in furtherance of this pledge are uncertain and will depend on a variety

of factors, including each co-founder’s individual circumstances, tax and estate planning considerations,

applicable transfer restrictions, market conditions, and philanthropic priorities at the relevant time. The co-

founders may satisfy this pledge over time through a variety of means, including donations to donor-advised

funds, charitable organizations, private foundations, or other philanthropic vehicles, certain of which have

entered into irrevocable proxy agreements with us, as described under the section titled “Certain Relationships

and Related Person Transactions—Irrevocable Proxy Agreements.” Donations of shares of our Class A common

stock in furtherance of this pledge and any subsequent sales by recipients could, subject to the lock-up and

market standoff agreements described above and applicable securities laws, result in the sale of a significant

number of shares in the public market. Because the timing and amount of any such donations and sales cannot

be predicted, any such sales, or the perception that such sales could occur, could depress the market price of our

Class A common stock. These pledges relate to the co-founders’ personal economic interests in shares of our

Class A common stock and do not apply to our Class F common stock or alter the Founder LLC voting structure

described under the section titled “Our Governance Structure and Its Goals—Founder Voting Structure.” As

such, as our co-founders make donations in furtherance of this pledge, their personal economic interests in us

will decrease while their voting control through the Founder LLC will remain unchanged for so long as each co-

founder continues to satisfy the minimum retained ownership condition for continued membership in the

Founder LLC described in the section titled “Description of Capital Stock—Founder LLC Agreement,” which

may reduce the alignment between the interests of our co-founders and those of our other stockholders, or

cause those interests to diverge.

Sales of our Class A common stock by stockholders as lock-up restrictions end or pursuant to registration rights

may make it more difficult for us to sell equity securities in the future at a time and at a price that we deem

appropriate. These sales may also cause the market price of our Class A common stock to fall and make it more

difficult for you to sell shares of our Class A common stock.

Because we do not anticipate paying any cash dividends on our capital stock in the

foreseeable future, capital appreciation, if any, will be your sole source of gain.

We do not anticipate paying cash dividends in the foreseeable future. We currently intend to retain future

earnings, if any, to fund the development and growth of our business. In addition, the A&R Credit Agreement

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contains, and any future credit facility or financing we obtain may contain, terms limiting the amount of cash

dividends that may be declared or paid on our capital stock. Any future determination to pay cash dividends

will be at the discretion of our board of directors and will be dependent upon our financial condition, results of

operations, capital requirements, and applicable contractual restrictions. As a result, stockholders should rely

on sales of their Class A common stock or Class N common stock after price appreciation, if any, as the only way

to realize any future gains on their investment.

If securities or industry analysts do not publish research or publish inaccurate or unfavorable

research about us, our business or our market, or if they change their recommendation

regarding our Class A common stock adversely, the market price and trading volume of our

Class A common stock could decline.

The market price and trading volume for our Class A common stock will depend in part on the research and

reports that securities or industry analysts publish about us, our business, our market, or our competitors. The

analysts’ estimates are based upon their own opinions and are often different from our estimates or

expectations. If any of the analysts who cover us change their recommendation regarding our Class A common

stock adversely, provide more favorable relative recommendations about our competitors or publish inaccurate

or unfavorable research about our business, the price of our securities would likely decline. If few securities

analysts commence coverage of us, or if one or more of these analysts cease coverage of us or fail to publish

reports on us regularly, we could lose visibility in the financial markets and demand for our securities could

decrease, which could cause the price and trading volume of our Class A common stock to decline.

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Special Note Regarding Forward-looking

Statements

This prospectus contains forward-looking statements within the meaning of the federal securities laws, which

statements involve substantial risks and uncertainties. All statements contained in this prospectus other than

statements of historical fact, including statements regarding our future results of operations, financial position,

market size and opportunity, our business strategy and plans, the factors affecting our performance, and our

objectives for future operations, are forward-looking statements. In some cases, you can identify forward-

looking statements because they contain words such as “may,” “will,” “shall,” “should,” “expect,” “plan,”

“anticipate,” “could,” “intend,” “target,” “project,” “contemplate,” “believe,” “estimate,” “predict,” “potential,”

“goal,” “objective,” “seek,” “forecast,” or “continue,” or the negative of any of these words or other similar terms

or expressions that concern our expectations, strategy, plans, or intentions. Forward-looking statements

contained in this prospectus include, but are not limited to, statements about:

•our future financial performance, including our expectations regarding our revenue, compute and

infrastructure expenses, and operating expenses, and our ability to achieve and maintain future

profitability;

•the sufficiency of our cash, cash equivalents, and investments and amounts available under our credit

facility to meet our working capital and liquidity needs;

•the amount, nature, and timing of our capital expenditures and other compute and infrastructure

commitments, our ability to fund such commitments and achieve expected returns, and our ability to

convert compute investments into revenue-generating customer workloads on anticipated timelines;

•our ability to successfully execute our business and growth strategy, including scaling our operations

and managing costs, timelines, and operational complexity, and pursuing our public benefit initiatives

consistent with our public benefit purpose;

•our expectations and management of future growth;

•our ability to raise additional capital through future debt or equity financing on acceptable terms, and

the potential dilutive or restrictive effects of any such financing on our stockholders and operations;

•our expectations concerning relationships with third parties and access to compute and infrastructure,

including potential conflicts of interest with cloud service providers and chip partners that develop

competing AI offerings;

•the demand for our offerings and the pricing thereof, including potential changes to our pricing

structure;

•our ability to attract and retain customers and our expectations regarding revenue concentration

among a limited number of customers and distribution channels;

•our ability to attract, develop, and retain highly skilled personnel, and to maintain our culture, talent

density, and mission alignment as we grow;

•our ability to develop new models, platforms, and applications and bring them to market in a timely

manner and make enhancements to our current models, platform, and applications, and to remain at

the frontier of AI;

•our plans and commitments with respect to AI safety, responsible deployment, and safety-related

access restrictions on frontier models, and the commercial and operational implications of those

commitments;

•our ability to maintain the availability and operability of our models, platform, and applications;

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•our ability to compete with existing and new competitors in existing and new markets and offerings;

•our expectations regarding new and evolving markets, including our ability to expand our operations,

customer base, and revenue internationally and to adapt our models, platform, and applications to

local language, regulatory, and market requirements in new jurisdictions;

•our ability to identify, execute, and integrate beneficial acquisitions, investments, and strategic

partnerships;

•our ability to manage risk associated with our business, including risks arising from our public benefit

corporation status and the role of the LTBT in our governance;

•our ability to protect our models, platform, applications, and systems against cybersecurity threats,

including nation-state and other sophisticated threat actors;

•our expectations regarding the effects of existing and developing laws and regulations, including with

respect to AI, copyright, privacy and data protection, and export controls, economic sanctions, and

other trade controls;

•our ability to maintain, protect, and enhance our intellectual property;

•our ability to develop and protect our brand, including the impact of safety, security, or misuse

incidents and of our public positions on AI policy and regulation;

•the increased expenses associated with being a public company;

•the outcome of pending or future litigation, regulatory proceedings, and governmental enforcement

actions, and their potential effects on our business, financial condition, and results of operations;

•our dividend policy, including our current intention not to pay cash dividends and to retain future

earnings for use in our business;

•the development and maintenance of an active trading market for our Class A common stock and the

potential volatility of our stock price following this offering; and

•our anticipated uses of net proceeds from this offering.

We caution you that the foregoing list may not contain all of the forward-looking statements made in this

prospectus.

We have based the forward-looking statements contained in this prospectus primarily on our current

expectations, estimates, forecasts, and projections about future events and trends that we believe may affect our

business, financial condition, results of operations, and prospects. The outcome of the events described in these

forward-looking statements is subject to risks, uncertainties and other factors, including those described in the

section titled “Risk Factors” and elsewhere in this prospectus. Moreover, we operate in a very competitive and

rapidly changing environment. New risks and uncertainties emerge from time to time and it is not possible for

us to predict all risks and uncertainties that could have an impact on the forward-looking statements contained

in this prospectus. Although we believe that we have a reasonable basis for each forward-looking statement

contained in this prospectus, we cannot assure you that the future results, events, and circumstances reflected

in the forward-looking statements will be achieved or occur at all, and actual future results, events, and

circumstances could differ materially from those described in the forward-looking statements. Accordingly, you

should not place undue reliance upon forward-looking statements as predictions of future events.

The forward-looking statements made in this prospectus relate only to our expectations as of the date on which

the statements are made. We undertake no obligation to update any forward-looking statements made in this

prospectus to reflect events or circumstances after the date of this prospectus or to reflect new information or

the occurrence of unanticipated events, except as required by law.

In addition, statements that “we believe” and similar statements reflect our beliefs and opinions on the relevant

subject. These statements are based upon information available to us as of the date of this prospectus, and while

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we believe such information forms a reasonable basis for such statements, such information may be limited or

incomplete, and our statements should not be read to indicate that we have conducted an exhaustive inquiry

into, or review of, all potentially available relevant information. These statements are inherently uncertain, and

investors are cautioned not to unduly rely upon these statements.

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Industry, Market, and Other Data

Unless otherwise indicated, data, estimates, and other information contained in this prospectus concerning our

industry and the market in which we operate, including our general expectations, market position, market

opportunity, and market size, are based on industry publications and reports generated by third-party

providers, other publicly available studies, and our internal sources and estimates. This information involves a

number of assumptions and limitations, and you are cautioned not to give undue weight to such estimates.

Although we are responsible for all of the disclosure contained in this prospectus and we believe the

information from the industry publications and other third-party sources included in this prospectus is reliable,

we have not independently verified the accuracy or completeness of the data contained in such sources.

Forecasts and other forward-looking information with respect to market and industry data and other data are

subject to the same qualifications and additional uncertainties regarding the other forward-looking statements

in this prospectus. See the section titled “Special Note Regarding Forward-looking Statements” for more

information. The content of, or accessibility through, the below sources, except to the extent specifically set

forth in this prospectus, does not constitute a portion of this prospectus and is not incorporated herein and any

websites are inactive textual references only.

The sources of the statistical data, estimates, and market and industry data contained in this prospectus are

identified by superscript notations and are provided below:

•IDC, The Economic Impact of AI: 2026 Edition, doc # US54452226, April 2026.

•IDC, Worldwide Black Book: Live Edition V2 2026 Forecast, July 2026.

•IDC, Worldwide Developer Population Growth Forecast, 2025–2029, doc # US53789825, September

2025.

•IQVIA Institute for Human Data Science, Global Medicine Use Trends 2026, February 2026.

•U.S. Bureau of Labor Statistics, Occupational Employment and Wage Statistics, May 2025.

•World Bank Group, GDP (current US$), 2025.

The industry in which we operate is subject to a high degree of uncertainty and risk due to a variety of factors,

including those described in the section titled “Risk Factors” and elsewhere in this prospectus. These and other

factors could cause results to differ materially from those expressed in the reports and estimates made by the

aforementioned third parties and by us.

Certain estimates in this prospectus regarding global knowledge workers’ wages, which we refer to as the

annual economic value represented by global knowledge workers, are our own, derived from third-party data.

Based on wage data for U.S. workers by occupation classification from the U.S. Bureau of Labor Statistics in

2025, we calculate the total salary for the subset of workers that we believe to represent knowledge workers.

Based on International Labor Organization data for global labor income as a percentage of global GDP, and

based on 2025 global GDP, we estimate a 2025 global wages figure. We calculate the ratio of total U.S. wages in

2025 to the 2025 global wages figure, and apply that ratio to the total U.S. knowledge workers’ wages figure to

arrive at an estimate of global knowledge workers’ wages.

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Use of Proceeds

We estimate that the net proceeds to us from the sale of shares of our Class A common stock in this offering will

be approximately $          , based upon the assumed initial public offering price of $           per share, which is the

midpoint of the estimated offering price range set forth on the cover page of this prospectus, and after

deducting estimated underwriting discounts and commissions and estimated offering expenses payable by us,

or approximately $           if the underwriters’ option to purchase additional shares of our Class A common stock

from us is exercised in full. We will not receive any proceeds from the sale of shares of Class A common stock by

the selling stockholders.

Each $1.00 increase or decrease in the assumed initial public offering price of $           per share, which is the

midpoint of the estimated offering price range set forth on the cover page of this prospectus, would increase or

decrease, as applicable, the net proceeds that we receive from this offering by approximately $          , assuming

that the number of shares offered by us, as set forth on the cover page of this prospectus, remains the same and

after deducting the estimated underwriting discounts and commissions and estimated offering expenses

payable by us. Similarly, each increase or decrease of 1.0 million in the number of shares of our Class A

common stock offered by us would increase or decrease, as applicable, the net proceeds that we receive from

this offering by approximately $          , assuming the assumed initial public offering price remains the same and

after deducting the estimated underwriting discounts and commissions and estimated offering expenses

payable by us.

The principal purposes of this offering are to increase our capitalization and financial flexibility, create a public

market for our Class A common stock, facilitate an orderly distribution of shares for the selling stockholders,

and enable access to the public equity markets for us and our stockholders.

We intend to use the net proceeds from this offering for general corporate purposes, including working capital,

operating expenses, and capital expenditures, including investments in compute and infrastructure, as well as

hiring and retention of highly skilled personnel. Additionally, we may use a portion of the net proceeds we

receive from this offering to acquire or invest in businesses, products, services, or technologies. However, we do

not have agreements or commitments for any material acquisitions or investments at this time.

We also intend to use a portion of the net proceeds we receive from this offering to satisfy our anticipated tax

withholding and remittance obligations of $           related to the RSU Settlement. This amount is based upon the

assumed initial public offering price of $           per share, which is the midpoint of the estimated offering price

range set forth on the cover page of this prospectus, and an assumed           % tax withholding rate. Each $1.00

increase or decrease in the assumed initial public offering price of $           per share, which is the midpoint of

the estimated offering price range set forth on the cover page of this prospectus, would increase or decrease, as

applicable, the amount we would be required to pay to satisfy our tax withholding and remittance obligations

related to the RSU Settlement by $          .

We cannot further specify with certainty the particular uses of the net proceeds that we will receive from this

offering. Accordingly, we will have broad discretion in using these proceeds. Pending the use of proceeds from

this offering as described above, we may invest the net proceeds that we receive in this offering in short-term,

investment grade, interest-bearing instruments.

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Dividend Policy

We have never declared or paid any cash dividends on our capital stock. We currently intend to retain all

available funds and any future earnings to finance the operation and expansion of our business and do not

expect to pay any dividends in the foreseeable future. Any future determination to declare cash dividends will

be made at the discretion of our board of directors, subject to applicable laws, and will depend on a number of

factors, including our financial condition, results of operations, capital requirements, contractual restrictions,

general business conditions, and other factors that our board of directors may deem relevant. In addition, the

terms of the A&R Credit Agreement place certain limitations on the amount of cash dividends we can pay, even

if no amounts are currently outstanding under the credit facility.

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Capitalization

The following table sets forth our cash, cash equivalents, and short-term investments, as well as our

capitalization, as of September 30, 2026 as follows:

•on an actual basis;

•on a pro forma basis, giving effect to (i) the Preferred Stock Conversion, as if such conversion had

occurred on September 30, 2026, (ii) the Convertible Notes Conversion, as if such conversion had

occurred on September 30, 2026, (iii) the Class F Stock Issuance, as if it had occurred on September

30, 2026, (iv) an increase to additional paid-in capital and accumulated deficit related to stock-based

compensation of $           related to RSUs subject to the RSU Settlement, and (v) the filing and

effectiveness of our amended and restated certificate of incorporation in Delaware that will become

effective immediately prior to the completion of this offering; and

•on a pro forma as adjusted basis, giving effect to (i) the pro forma adjustments set forth above, (ii) the

sale and issuance by us of            shares of our Class A common stock in this offering, based upon the

assumed initial public offering price of $           per share, which is the midpoint of the estimated

offering price range set forth on the cover page of this prospectus, and after deducting estimated

underwriting discounts and commissions and estimated offering expenses payable by us, and (iii) the

use of net proceeds from this offering, together with existing cash and cash equivalents, if necessary, to

satisfy the estimated tax withholding and remittance obligations related to the RSU Settlement. We will

not receive any proceeds from the sale of shares of our Class A common stock by any of the selling

stockholders.

The pro forma as adjusted information set forth in the table below is illustrative only and will be adjusted based

on the actual initial public offering price and other terms of this offering determined at pricing. You should read

this table together with our consolidated financial statements and related notes, and the section titled

“Management’s Discussion and Analysis of Financial Condition and Results of Operations” that are included

elsewhere in this prospectus.

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