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The documentS–1Anthropic, PBC26 OCT 2026 · 421 PP.
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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other  laws  and  regulations  not  originally  enacted  to  address  privacy  or  data  protection,  continue  to  evolve  as 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 

87

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  1. Founders’ letterp. 3SEC
  2. Defined termsp. 12SEC
  3. Prospectus summaryp. 16SEC
  4. Risk factorsp. 38SEC
  5. Management’s discussion & analysisp. 144SEC
  6. Businessp. 190SEC
  7. Governancep. 254SEC
  8. Executive compensationp. 275SEC
  9. Related-person transactionsp. 293SEC
  10. Principal & selling stockholdersp. 299SEC
  11. Capital-stock rightsp. 303SEC
  12. Shares eligible for future salep. 318SEC
  13. Underwritingp. 327SEC
  14. Auditor change & expertsp. 345SEC
  15. Financial statements & notesp. 347SEC
  16. Part II & exhibit indexp. 413SEC

How this was made

Read in full.
Kept in context.

A snapshot of the filing dated , rather than a live record of later events.

3primary reviewers
421pages reviewed
43image instances checked

The review

Three primary reviewers read non-overlapping ranges of the complete main filing. All 43 embedded image instances were transcribed and visually reviewed, including the founders’ letter, charts, and customer case studies. Financial tables were also checked visually for dates, units, and column alignment.

A separate reviewer checked the draft’s calculations, accounting interpretations, and customer qualifications. An additional check covered the later merged findings. The result is 62 findings and 21 customer examples.

The boundary

Companion contracts and other exhibits named in the filing’s index are separate documents and were not independently reviewed. Customer outcomes, technical benchmarks, forecasts, and scientific priority claims remain attributed company or customer disclosures.

The numbers

Dollar figures are U.S. dollars. H1 means the six months ended June 30; Q2 means the three months ended June 30. The 2026 interim financial statements are unaudited. Our calculations show their inputs and are labeled separately from reported values.

Blank fields stay undisclosed. Figures with different periods, conditions, or potentially overlapping scopes are kept separate. An earlier tender price is not an IPO price.

What the evidence labels mean
Reported in filing
A company disclosure, with the period and accounting basis retained.
Company estimate / company claim
An estimate or assertion attributed to the company, with its uncertainty preserved.
Our calculation
A derived figure using cited inputs. It is not a separately reported company metric.
Customer example
A selected case study, with its measurement limits. It is not representative ROI.
Proposed / conditional
A status qualifier for an arrangement that is not yet effective or depends on stated conditions.

About updates. This edition is tied to the October 26, 2026 filing. Any later revision should identify its new source date and preserve the basis of earlier claims.

The footnotes are only the beginning.Explore the findings Read the story
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A closer look at the filing

Anthropic · Form S-1PDF 1

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Filed October 26, 2026. PDF is approximately 46 MB and opens only when requested. Section links may precede the exact cited paragraph.