Redacted exhibits under CPR Part 31: pseudonymise non-party data in disclosed exhibits – UK GDPR-compliant anonymisation per CPR Part 31

Redacted exhibits are documents disclosed under CPR Part 31 — such as invoices, correspondence, and records — from which non-party personal data has been pseudonymised before production; anonym.legal applies consistent pseudonymisation across all exhibit documents — according to HMCTS Civil Justice Statistics, over 1.4 million claims were issued in 2023, generating millions of exhibits containing third-party personal data.

When this applies

Applies when a solicitor is preparing exhibits for disclosure under CPR Part 31 and the exhibits contain personal data about individuals who are not parties — for example, customer records in a commercial dispute above the £25,000 multi-track threshold or HR records in an employment claim. Data shows that large commercial disclosures can contain over 20,000 documents with third-party identifiers.

  1. Upload the exhibit documents — invoices, emails, records — in PDF or DOCX format.
  2. Configure the party-names allow-list for the case parties.
  3. anonym.legal identifies and pseudonymises non-party names, addresses, account references, and other personal identifiers across all exhibits.
  4. Substantive content — dates, amounts, subject matter — is preserved so the evidential value of the exhibit is maintained.
  5. A reversible mapping is stored with EU data residency.
  6. Consider whether your disclosure statement should note that exhibits have been prepared with third-party data pseudonymised in accordance with UK GDPR data-minimisation principles.

What you provide

  • Exhibit documents (PDF or DOCX)
  • Party-names allow-list

Limitations & cautions

  • Decisions on which documents are disclosable and whether any redaction is permissible under CPR Part 31 must be made by a qualified solicitor.
  • Irrelevant redaction of substantive content may constitute a breach of disclosure obligations — only personal-identifier data should be pseudonymised, not substantive evidence.
  • Misuse of non-party personal data in disclosed exhibits can attract UK GDPR fines of up to £17.5 million or 4% of global turnover under DPA 2018 s.157; the ICO fined British Airways £20 million in 2020 for inadequate data protections.

FAQ

Is pseudonymising non-party personal data in disclosed exhibits permissible under CPR Part 31?

Proportionate pseudonymisation of non-party personal data is consistent with data-minimisation principles under UK GDPR Article 5. Whether it is permissible in any given case should be confirmed with the court or agreed with the other side. According to the ICO Code of Practice on Anonymisation (2021), pseudonymisation is a recognised privacy-enhancement technique.

Can I pseudonymise personal data that is also part of the substantive evidence?

If the identity of a non-party is itself material to the issues in dispute, pseudonymisation may not be appropriate for that individual. Use the party-names allow-list or manually exclude individuals whose identities are evidentially material.

What if the exhibit is a spreadsheet with thousands of rows of third-party data?

anonym.legal processes large spreadsheets at row level, identifying personal-identifier columns and pseudonymising all relevant cells consistently across the dataset. Data shows that commercial disclosure datasets can contain over 50,000 rows of customer records requiring pseudonymisation.

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 company HQ is in Saarbrücken, Germany. Our servers run in Hetzner's Falkenstein datacenter.

Hetzner holds 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.