Anonymizing UCC Lien-Search Results for Due-Diligence Packages – CCPA/HIPAA-compliant de-identification per UCC §9-310

A UCC lien-search result produced under UCC §9-310 lists active financing statements by debtor name, secured party, filing date, and collateral description. anonym.legal anonymizes debtor and individual secured-party names — preserving lien-priority data, collateral descriptions, and filing dates — so due-diligence teams can assess the lien landscape without processing unnecessary personal data.

When this applies

This task applies when UCC lien-search results are compiled into a due-diligence report for an acquisition, refinancing, or credit decision, and the advisers receiving the report need lien-priority and collateral information rather than the personal identifiers of individual debtors or guarantors.

  1. Upload the lien-search results export (PDF or spreadsheet) to anonym.legal.
  2. The engine identifies debtor names, addresses, and any individual secured-party names in the search results.
  3. Each named individual is anonymized consistently across all filing entries in the results.
  4. Filing dates, file numbers, collateral descriptions, and secured-party entity names are preserved for priority analysis.
  5. A mapping table is generated with US data residency.
  6. Release the anonymized search results for due-diligence review; restore originals before any lien-priority opinion is issued.

What you provide

  • UCC lien-search results export
  • Filing jurisdiction confirmation (to confirm UCC adoption scope)

Limitations & cautions

  • UCC §9-310 requires filing in the correct jurisdiction based on the debtor's location under UCC §9-307 — the tool does not assess filing sufficiency or jurisdictional correctness.
  • Lien-priority opinions require the original identified search results — anonymized results should not be used as the basis for a formal legal opinion.

FAQ

How does anonym.legal handle search results covering multiple jurisdictions?

Upload all jurisdiction search results in a single batch. Named individuals who appear as debtors in multiple jurisdictions receive consistent pseudonyms across all results, preserving cross-jurisdiction lien analysis.

Are secured-party entity names anonymized?

Secured-party names that identify a legal entity (e.g., a bank or corporation) are not anonymized. Only natural-person names are anonymized. If a secured party is an individual, that name is anonymized consistently.

Can I anonymize a lien search run against an individual debtor?

Yes. Individual debtor names and addresses are anonymized. The filing date, collateral description, and file number are preserved for priority analysis.

Commercial Contracts

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.