Anonymising Commercial Settlement Agreements for Legal Benchmarking – UK GDPR-compliant anonymisation per UK GDPR Art. 5(1)(c)

A commercial settlement agreement names the claimant, respondent, and their legal representatives; may reference individual witnesses or expert witnesses; and records the settlement consideration and agreed confidentiality obligations. anonym.legal pseudonymises the named individuals — preserving the settlement mechanics, payment terms, confidentiality obligations, and any agreed public statements — so the agreement can be used for internal precedent review or benchmarking without disclosing party identities.

When this applies

This task applies when a settlement agreement is added to an internal precedent library, shared with insurance underwriters assessing litigation risk, or benchmarked against market settlements, and those uses require sight of the commercial terms but not the identities of the parties or their representatives.

  1. Upload the settlement agreement.
  2. The engine identifies named parties, their legal representatives, and any named witnesses or experts referenced in recitals or schedules.
  3. Each individual is pseudonymised consistently; settlement consideration, payment timing, and confidentiality provisions are preserved.
  4. Any non-disparagement or agreed public-statement provisions are preserved in clear text.
  5. A mapping table is produced with UK/EU data residency.
  6. Release the pseudonymised version for precedent use; the original is retained under the agreed confidentiality regime.

What you provide

  • Commercial settlement agreement
  • Any deed of release attached to the settlement
  • Agreed joint statement (if annexed)

Limitations & cautions

  • Settlement agreements often contain confidentiality provisions that restrict use of the agreement itself — ensure any use of the pseudonymised version is consistent with those provisions.
  • Where the settlement resolves claims involving special-category data (e.g. health or discrimination claims), additional care is required under UK GDPR Art. 9(2)(f).

FAQ

Does pseudonymisation breach the settlement's own confidentiality clause?

That depends on the specific wording of the confidentiality clause and the use to which the pseudonymised version is put. Obtain legal advice before using the pseudonymised version in any context that could be read as disclosure of the settlement's existence or terms.

Can a pseudonymised settlement agreement be used as a precedent in future negotiations?

Yes. This is a primary use case. The pseudonymised version preserves the commercial structure — consideration, release scope, payment mechanics — making it suitable for internal precedent libraries.

Are legal representatives' names pseudonymised as well as the parties'?

Yes. Named solicitors, barristers, and their firms' contact personnel are pseudonymised if they appear as natural persons in the document.

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.