Anonymising Mutual NDAs Before External Review – UK GDPR-compliant anonymisation per UK GDPR Art. 4(1)

A mutual non-disclosure agreement names both counterparties, their authorised signatories, and often project contacts throughout its recitals and schedules. anonym.legal pseudonymises these personal identifiers — keeping confidentiality obligations, carve-outs, and governing-law clauses intact — so the commercial terms can be reviewed, benchmarked, or shared externally without exposing individual identities.

When this applies

This task applies when both parties to an NDA need to circulate the signed or draft agreement to advisers, auditors, or third-party reviewers who require sight of the commercial terms but have no lawful basis to process the named individuals' personal data.

  1. Upload the mutual NDA (PDF, DOCX, or ODT) to anonym.legal; the document structure, clause numbering, and formatting are preserved.
  2. The engine detects personal-data entities across all 285+ supported categories — full names, job titles, email addresses, and postal addresses of signatories and contacts.
  3. Each named individual is assigned a consistent pseudonym (e.g. 'Party A Representative 1') applied uniformly across recitals, signature blocks, and schedules.
  4. Commercial terms — confidentiality scope, duration, permitted-purpose carve-outs, and governing-law clauses — remain in clear text.
  5. A reversible mapping table is generated and stored with EU/UK data residency, allowing full re-identification before filing or execution.
  6. Download the pseudonymised draft for circulation, and use the mapping key to restore original names when the final signed copy is required.

What you provide

  • Signed or draft mutual NDA document
  • List of all named signatories and their roles (to verify entity detection)
  • Any schedule or exhibit appended to the main agreement

Limitations & cautions

  • anonym.legal pseudonymises personal data but does not review the legal sufficiency of the confidentiality obligations — obtain independent legal advice on clause scope.
  • Handwritten or heavily scanned documents may require OCR pre-processing before entity detection achieves full coverage.
  • Re-identification requires secure custody of the mapping key; loss of the key makes reversal impossible.

FAQ

Will pseudonymisation affect the enforceability of the NDA?

The pseudonymised version is a working copy for review purposes only. Before execution or filing, re-identify the document using the mapping key so that the executed version bears the correct legal names. Only the identified version has contractual effect.

Does the engine handle NDAs with multiple signatories on each side?

Yes. Each natural person is tracked as a distinct entity and assigned a unique, consistent pseudonym throughout the document, regardless of how many individuals are listed on either side.

Is the mapping table stored in the UK or EU?

All processing and storage occurs within UK/EU data residency boundaries, in line with UK GDPR requirements for personal data transfers.

Can I redact company names as well as personal names?

By default the engine targets natural-person data. You can manually flag company names as additional entities to pseudonymise if your review scenario requires it.

Commercial Contracts

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.