Expert Report under CPR Part 35: redact non-party personal data – UK GDPR-compliant anonymisation per CPR Part 35

Expert reports served under CPR Part 35 often reference medical records, financial data, or witness accounts that contain personal data about individuals who are not parties; anonym.legal pseudonymises those references across the report and any appendices, enabling the instructing solicitor to share draft reports internally without exposing third-party data unnecessarily before the report is finalised.

When this applies

Applies when an instructing solicitor or expert is preparing a CPR Part 35 report that cites or incorporates third-party personal data, particularly in medical negligence, personal injury, or financial-dispute matters.

  1. Upload the draft expert report and any appendices or supporting data schedules.
  2. anonym.legal identifies personal identifiers — patient names, medical-record numbers, account numbers, addresses — across all documents.
  3. Each individual is pseudonymised consistently across the report and all appendices.
  4. Technical and expert opinion, methodology, and conclusions are preserved in full.
  5. A reversible mapping is stored in an encrypted table with EU data residency.
  6. The solicitor re-identifies from the mapping key when producing the final version for exchange or filing.

What you provide

  • Draft expert report (DOCX or PDF)
  • Appendices, data schedules, or source documents annexed to the report
  • Party-names allow-list

Limitations & cautions

  • The expert's own name and professional qualifications must appear in clear in the served version — do not pseudonymise the expert's identity.
  • anonym.legal does not verify compliance with the CPR Part 35 declaration (see PD 35 paragraph 3.2) or the overriding duty to the court.
  • Medical imaging or scanned records with embedded patient metadata require manual redaction before upload.

FAQ

Can anonym.legal process reports from multiple experts in the same matter?

Yes, upload reports from all experts in a single session to ensure consistent pseudonyms across all materials.

Does the engine handle statistical or aggregated data?

Aggregated data without individual identifiers is preserved as-is. The engine targets personal-identifier fields only.

What if the report contains direct quotations from a witness?

Quotations are treated as running text; if they contain personal identifiers, those identifiers are pseudonymised while the quoted content is otherwise preserved.

Civil Litigation

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.