Pseudonymising Children Proceedings Court Bundles – UK GDPR-compliant anonymisation per Family Procedure Rules 2010

Children proceedings court bundles aggregate statements, expert evidence, and correspondence that identify the child, both parents, extended family, and professional witnesses throughout. anonym.legal pseudonymises those personal identifiers across the entire bundle while preserving the chronology, welfare analysis, and procedural record so reviewing experts can assess the case without direct access to the parties' personal data.

When this applies

This task applies when a consolidated court bundle is shared with a jointly-instructed expert, a reviewing independent social worker, or a legal-aid supervisor for quality review, and the recipient requires the substantive case content but not the personal data of the individuals named.

  1. Upload the full court bundle (or individual sections) to anonym.legal in a batch.
  2. The engine builds a unified entity registry across all documents in the bundle, assigning consistent pseudonyms to every named individual regardless of where they appear.
  3. The child, parents, extended family members, social workers, CAFCASS officers, teachers, and medical professionals each receive a unique, consistent pseudonym.
  4. Welfare analysis, chronology entries, order texts, and expert conclusions remain in clear text.
  5. A master mapping table for the bundle is produced with UK data residency.
  6. Release the pseudonymised bundle for expert or reviewer use; restore originals for court use.

What you provide

  • Indexed court bundle (PDF, DOCX, or multi-file batch)
  • Bundle index or schedule (to preserve document references)
  • Expert instruction letter if it names parties

Limitations & cautions

  • Bundles containing colour-coded annotations or hand-written marginal notes may require OCR pre-processing and a manual review of annotation coverage.
  • The tool pseudonymises personal data in bundle documents but does not review the sufficiency or accuracy of the evidence — obtain specialist advice.
  • Re-identification must occur before the bundle is filed or used at a final hearing.

FAQ

How does the engine handle witness statements that quote other named individuals?

Quoted names within statements are detected and pseudonymised consistently with those individuals' appearances elsewhere in the bundle, so internal cross-references remain coherent.

Can I process a bundle that includes documents in different formats (PDF and DOCX)?

Yes. anonym.legal accepts PDF, DOCX, and TXT within the same batch. Mixed-format bundles are processed in a unified pass.

Will pagination and page references within the bundle be preserved?

Pagination is preserved in the pseudonymised output. Internal cross-references that cite page numbers are unaffected; cross-references that name individuals are pseudonymised.

Family Law

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.