Pseudonymising Software Licence Agreements for Legal Review – UK GDPR-compliant anonymisation per UK GDPR Art. 4(1)

A software licence agreement identifies the licensee's authorised users, technical contacts, and payment administrators, often in an exhibit or order form appended to the core licence grant. anonym.legal pseudonymises these individuals while preserving the grant scope, restrictions, royalty provisions, and support entitlements so that external IP counsel can advise on the licence terms without unnecessary access to personal data.

When this applies

This task applies when a software licence agreement is referred to external intellectual-property counsel or technology lawyers for review of licence scope, audit rights, or source-code escrow provisions, and the named users or contacts are not relevant to that legal analysis.

  1. Upload the software licence agreement and any attached user-list or order-form exhibits.
  2. The engine identifies named licensees, authorised users, technical contacts, and billing administrators across all documents.
  3. Each individual is pseudonymised consistently; role-based references (e.g. 'the Licensee's IT Manager') that appear alongside a name are also captured.
  4. The licence grant, restrictions, support tiers, audit rights, and IP ownership provisions remain in clear text.
  5. A mapping table is stored with UK/EU data residency.
  6. Release the pseudonymised documents for review; restore originals before execution.

What you provide

  • Software Licence Agreement
  • User-list or authorised-user exhibit
  • Order form naming billing and technical contacts

Limitations & cautions

  • The engine does not assess whether the licence grant is sufficiently broad for the intended use case — obtain specialist IP advice.
  • Named third-party software components listed in a schedule are not pseudonymised (they are not personal data); only natural-person identifiers are targeted.

FAQ

What if the licence agreement names both individual users and team accounts?

Individual natural persons are pseudonymised. Generic team accounts (e.g. 'dev-team@company.com') that do not identify a specific individual fall outside the UK GDPR definition of personal data and are not altered unless you flag them manually.

Can I use the pseudonymised licence in an M&A due-diligence data room?

Yes. This task pairs well with the M&A due-diligence workflow — pseudonymise the licence here and include it in the data room via the data-room-anonymisation workflow, which handles batch processing and access-control logging.

Does the tool handle multi-jurisdiction licence agreements?

Yes. The engine detects personal data irrespective of the governing law clause, though the pseudonymisation standard applied is UK GDPR. Confirm with your legal adviser that this standard is adequate for any non-UK governing-law provisions.

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.