Anonymize 10-K annual report drafts for external review and benchmarking – CCPA/HIPAA-compliant de-identification per 15 USC §78m

Annual reports on Form 10-K filed under Securities Exchange Act §78m disclose executive names, compensation figures, related-party transactions, and legal proceedings that identify individuals and counterparties. anonym.legal pseudonymizes these personal data fields in draft 10-Ks so they can be shared with external counsel, auditors, or peer-benchmarking advisers without exposing sensitive individual data.

When this applies

Use this workflow when draft 10-K sections — MD&A, executive-compensation tables, or legal-proceedings disclosures — must be circulated to outside counsel, disclosure-review committees, or benchmarking vendors where the specific individual identities are not required.

  1. Upload the draft 10-K or individual sections (e.g., Part II, Items 6-9A) to anonym.legal in PDF or DOCX format.
  2. The engine identifies named executives, directors, related-party counterparties, named litigation plaintiffs, and individual compensation figures linked to named persons.
  3. Each individual is assigned a consistent pseudonym across all sections of the report, preserving cross-references between the proxy-statement-incorporated executive-compensation table and the Reg S-K §229.404 related-party section.
  4. Financial statement line items, segment data, and MD&A narrative not linked to named individuals are retained as non-personal structural content.
  5. Legal-proceedings descriptions in Item 3 (Reg S-K §229.103) are pseudonymized at the plaintiff and counterparty level while preserving case status, forum, and claimed damages for disclosure review.
  6. The reversible mapping is stored encrypted with US data residency.
  7. The pseudonymized draft is exported for review; re-identification is available before filing.

What you provide

  • Draft 10-K in PDF or DOCX format, or individual sections extracted from the EDGAR filing system
  • Instruction on which named individuals should be pseudonymized (all named persons, or a defined subset)
  • Prior-year 10-K if cross-year consistency of pseudonyms is required

Limitations & cautions

  • anonym.legal does not assess the completeness or accuracy of disclosures required by Reg S-K or Exchange Act §78m; disclosure adequacy requires attorney and auditor review.
  • Incorporation-by-reference structure (e.g., proxy statement incorporated into Part III) means cross-referenced documents must also be uploaded for consistent pseudonymization.
  • Highly specific factual descriptions — such as a uniquely structured deal with a named counterparty — may retain indirect identifiability after pseudonymization of direct name references.
  • The tool does not prepare or file EDGAR submissions; it processes draft documents only.

FAQ

Can this workflow pseudonymize the executive compensation tables in Item 11?

Yes. Compensation tables linked to named executives — including the Summary Compensation Table, Grants of Plan-Based Awards Table, and Outstanding Equity Awards table — are processed with each named executive pseudonymized consistently throughout all tables.

Will financial statement figures be altered by pseudonymization?

No. Consolidated financial statement figures, segment revenues, and aggregate compensation totals are non-personal structural content and are preserved in plain text. Only figures linked by name to a specific individual (e.g., a named CEO's total compensation row) are treated as personal data.

Can I use pseudonymized drafts for peer-benchmarking with a compensation consultant?

Yes. Pseudonymizing the draft executive-compensation sections allows a compensation consultant to benchmark pay structures against market data without learning the identities of the specific executives whose compensation is being reviewed.

Does the tool handle multi-part 10-K filings with exhibits?

Yes. You can upload the main body and all exhibits as a batch. The engine assigns consistent pseudonyms across the main document and attached exhibits, including any Reg S-K §229.601 exhibit list.

Securities & Corporate Disclosure

About this page

We update this page when our platform or the law changes.

Read our founder note for how we work.

Each change shows up in the timestamp at the top.

We follow these rules

  • GDPR (EU 2016/679).
  • ISO/IEC 27001:2022.
  • NIS2 (EU 2022/2555).
  • HIPAA safe harbor under 45 CFR § 164.514(b)(2).

Our promise

We do not sell your data.

We do not train models on your text.

We store your files in Germany.

You can delete your account at any time.

You own your work.

Where we run

Our servers live in Falkenstein, Germany.

We use Hetzner. They hold ISO 27001 certification.

All data stays in the EU.

Backups run every day.

Need help?

Email support@anonym.legal.

We reply within one business day.

How we test

We run a full check suite on every release.

Each surface gets its own sweep script and report.

Human reviewers spot-check the output each week.

We track recall and precision on a labelled set.

Bad runs block the deploy.

What we never do

  • We never sell your information to third parties.
  • We never train models on what you upload.
  • We never keep your work after you delete it.
  • We never share keys with any outside firm.
  • We never run ads inside the product.

Plans in plain words

We sell credits, not seats.

One credit covers one short job.

Long jobs use a few credits each.

You can top up at any time.

Unused credits roll over each month.

Read the plans page for current rates.

Who built this

A small team of engineers and lawyers built this.

We ship from Europe and work in the open.

Our founder note spells out why we started.

Where to start

How the parts fit

A browser add-on cleans text inside Chrome.

A Word plug-in handles drafts in Office.

A small desktop tool works on whole folders.

An agent protocol link feeds large models safely.

All four share one core engine and one rule set.

Words from our team

We started this work after a lunch about cookies.

One friend kept getting odd ads on her phone.

We asked why a court file leaked through a draft.

We sketched the first build on a napkin that week.

By month three we had a tiny demo for a friend.

She used it on her first case the next day.

Common questions we hear

Can the tool read scanned PDFs? Yes, with OCR.

Does it work on long files? Yes, in small chunks.

Can I roll my own rule set? Yes, save it as a preset.

Does it run offline? The desktop build runs offline.

Do you keep my files? No, the cloud build wipes after each run.

Will it learn from my work? No, we never train on inputs.

A short tour of the workflow

Upload a file or paste a snippet of prose.

Pick the entities you want gone from the draft.

Choose a method: replace, mask, hash, encrypt, or redact.

Press run and watch the side panel show each hit.

Skim the result and tweak any rule that misfired.

Save the cleaned file or send it to a teammate.