Anonymising Joint Venture and Collaboration Agreements – UK GDPR-compliant anonymisation per Contracts (Rights of Third Parties) Act 1999

Joint venture and collaboration agreements identify the named authorised representatives and nominees of each venture party, their addresses, and often their individual contributions and profit-share entitlements. anonym.legal pseudonymises these individuals — preserving governance structure, profit-share mechanics, and any third-party rights expressly conferred under the Contracts (Rights of Third Parties) Act 1999 — so the commercial framework can be shared with financing parties or regulatory advisers without personal-data disclosure.

When this applies

This task applies when a joint venture or collaboration agreement is shared with debt or equity financiers, regulatory bodies, or sector consultants who require sight of the governance and commercial terms but have no legitimate need to process the named individuals' personal data.

  1. Upload the JV or collaboration agreement and any side letters naming individual nominees or representatives.
  2. The engine identifies all named natural persons: venture-party nominees, authorised representatives, board appointees, and any named profit-share beneficiaries.
  3. Each individual is pseudonymised consistently across the agreement and side letters.
  4. Governance provisions — board composition rules, deadlock mechanisms, exit triggers — profit-share calculations, and any expressly conferred third-party rights under the 1999 Act remain in clear text.
  5. A mapping table is produced with UK/EU data residency.
  6. Release the pseudonymised version for financing or regulatory review; restore originals before execution.

What you provide

  • Joint venture or collaboration agreement
  • Side letters naming individual nominees or representatives
  • Shareholder or members' agreement if the JV is incorporated

Limitations & cautions

  • Whether third-party rights under the Contracts (Rights of Third Parties) Act 1999 are adequately preserved requires legal review — the tool pseudonymises personal data in those provisions but does not alter their legal effect.
  • Deadlock mechanisms referencing named casting-vote holders are pseudonymised; verify consistency in the pseudonymised version before sharing with financiers.

FAQ

Are third-party rights under the 1999 Act affected by pseudonymisation?

The substantive right-conferral language is preserved. If the right is conferred on a named individual, that name is pseudonymised in the review copy. The executed version must re-identify all named beneficiaries to ensure the right is enforceable.

Can I pseudonymise an unincorporated JV agreement and an incorporated JV shareholders' agreement in the same batch?

Yes. Upload all related documents together; the engine tracks individuals across both and applies consistent pseudonyms.

How does the tool handle nominee shareholder arrangements disclosed in the JV agreement?

Named nominees and the beneficial owners they act for are each pseudonymised individually, with distinct pseudonyms, so the nominee / beneficial-owner relationship structure is preserved.

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.