Tomlin Order and settlement agreement: pseudonymise before circulation – UK GDPR-compliant anonymisation

A Tomlin Order stays proceedings on agreed terms scheduled to the order, and the attached schedule frequently contains personal data about the settling parties, named individuals, or third-party beneficiaries; anonym.legal pseudonymises those identifiers in draft orders and settlement agreements so legal teams can circulate working drafts without unnecessary data exposure before the parties execute the final document.

When this applies

Applies when a solicitor is drafting a Tomlin Order schedule or settlement agreement that names individuals — guarantors, beneficiaries, employees, or other third parties — whose personal data should be protected during the drafting stage.

  1. Upload the draft Tomlin Order (or consent order) and attached schedule in DOCX or PDF.
  2. Configure the party-names allow-list to retain named parties' names in clear.
  3. anonym.legal pseudonymises third-party names, account numbers, property addresses, and other personal identifiers in the schedule.
  4. Settlement terms, financial obligations, and procedural provisions are preserved in full.
  5. A reversible mapping is stored with EU data residency.
  6. Re-identify from the mapping key before the order is engrossed and submitted to the court.

What you provide

  • Draft Tomlin Order or consent order body (DOCX or PDF)
  • Draft settlement schedule
  • Party-names allow-list

Limitations & cautions

  • The final Tomlin Order submitted to the court must contain accurate party names and terms — always re-identify completely before submission.
  • anonym.legal does not review the enforceability or legal effect of the settlement terms.

FAQ

What distinguishes a Tomlin Order from a consent order?

A Tomlin Order stays the proceedings with confidential terms in a schedule, which does not become part of the public court record. A consent order disposes of the proceedings on terms that are on the record. Both can be processed through anonym.legal using the same workflow.

Can I pseudonymise the schedule separately from the order body?

Yes — upload the schedule and order body together in one session for consistent pseudonymisation, or upload them separately if that suits your workflow.

Are property addresses and bank account details pseudonymised?

Yes — property addresses, bank account numbers, and sort codes are recognised as personal-data identifiers and pseudonymised by default.

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.