Pseudonymising Occupation Order Applications – UK GDPR-compliant anonymisation per UK GDPR

Occupation order applications identify both parties by name and address, describe the property subject to the order, and set out the applicant's housing needs and the impact on the respondent and any children. anonym.legal pseudonymises the parties' identifiers and address details while preserving the housing-needs narrative so the application can be reviewed without exposing the applicant's location.

When this applies

This task applies when an occupation order application and supporting evidence are reviewed by a legal-aid supervisor, housing adviser, or welfare specialist, and the reviewer requires sight of the housing-needs analysis and proposed order terms but should not have access to the applicant's address or the property's full location details.

  1. Upload the occupation order application (Form FL401) and any property-related evidence.
  2. The engine identifies the applicant, respondent, children, and property address across the application and supporting documents.
  3. Each natural person receives a consistent pseudonym; the property address is pseudonymised as a unit to protect the applicant's location.
  4. Housing-needs analysis, cohabitation history, and the terms of the proposed order are preserved in clear text.
  5. A reversible mapping table is produced with UK data residency.
  6. Release the pseudonymised documents for review; restore real addresses only for court filing under appropriate safety protocols.

What you provide

  • Form FL401 occupation order application
  • Supporting witness statement describing occupation history
  • Property-related evidence (land registry title if attached)

Limitations & cautions

  • The full property address carries particular sensitivity in domestic abuse contexts — the mapping table containing the real address should be shared only on a strict need-to-know basis.
  • Land Registry title information appended to the application will have the proprietor's name pseudonymised but the title number preserved.
  • anonym.legal does not advise on the merits of occupation order applications or the balance of harm test.

FAQ

Is the property's full address pseudonymised in the application?

Yes. The full property address is pseudonymised as a single unit. A general area descriptor (e.g. 'a property in London') is preserved if present, but the specific street and postcode are replaced with a pseudonym.

Can an occupation order application be pseudonymised alongside a non-molestation order application?

Yes. Upload both applications in the same batch. Individuals named in both applications receive consistent pseudonyms across all documents.

Are Land Registry title numbers treated as personal data?

Title numbers are not personal data under UK GDPR and are preserved. Only the named registered proprietors 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.
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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.