Anonymising Sale-of-Business Contracts for Benchmarking – UK GDPR-compliant anonymisation per UK GDPR Art. 5(1)(c)

A sale-of-business contract — whether structured as a share deal, asset deal, or business-and-assets transfer — contains personal data of the vendor, purchaser principals, key employees, and named advisers in recitals, completion mechanics, and restrictive-covenant schedules. anonym.legal pseudonymises those individuals so the agreement can be benchmarked against market precedents or reviewed by sector specialists without personal-data disclosure.

When this applies

This task applies when a completed or near-final sale-of-business contract is shared with sector advisers for benchmarking deal terms, or with management teams evaluating the restrictive covenants and earn-out mechanics, and those reviewers have no need to know the identity of the individual principals.

  1. Upload the sale-of-business contract and any restrictive-covenant or earn-out schedules.
  2. The engine identifies vendor and purchaser principals, named advisers, and any employees referenced in restrictive-covenant provisions.
  3. Each individual is pseudonymised consistently; earn-out targets, performance metrics, and restrictive-covenant geography and duration terms are preserved.
  4. Release the pseudonymised version for benchmarking or review.
  5. Restore originals using the mapping key before any filing or completion formality.

What you provide

  • Sale-of-business contract (all parts)
  • Earn-out schedule (if applicable)
  • Restrictive-covenant schedule naming covenantors

Limitations & cautions

  • The enforceability of restrictive covenants is a legal question requiring specialist advice; the tool pseudonymises the personal data in those provisions but does not assess their legal validity.
  • Earn-out provisions referencing individual performance are pseudonymised at the name level; performance metrics and financial targets are preserved.

FAQ

Can I use this for a franchise sale agreement?

Yes. Franchise sale agreements follow a similar structure to business sale contracts and are supported. Named franchisees and their personal guarantors are detected and pseudonymised.

Does pseudonymisation cover personal guarantees attached to the sale contract?

Yes. Personal guarantees naming individual guarantors are processed in the batch, and the guarantors receive consistent pseudonyms matching their appearances in the main agreement.

How are earn-out provisions handled when they reference named individual performance?

The individual's name is pseudonymised while the performance metric, target figure, and measurement methodology remain in clear text, preserving the commercial substance of the earn-out.

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.