Anonymize professional employment applications for ethics research – CCPA/HIPAA-compliant de-identification per 11 USC §327

A trustee or debtor in possession must obtain court approval to employ professionals under 11 USC §327 by filing an application disclosing the professional's connections to parties in interest and proposed compensation terms. These applications name the applicant firm, individual professionals, and all parties screened for conflicts. anonym.legal pseudonymizes these identifiers for ethics-education and conflicts-screening research.

When this applies

Apply this workflow when professional employment applications and supporting affidavits must be shared with law-school ethics courses, bar-association CLE programs, or academic researchers studying bankruptcy professional-compensation practices.

  1. Upload the professional employment application and supporting affidavit of disinterestedness to anonym.legal.
  2. The engine identifies the applicant firm name, individual professional names, debtor name, and all conflict-check parties named in the affidavit.
  3. Each named party receives a consistent pseudonym applied throughout the application and affidavit.
  4. The category of professional service — financial adviser, investment banker, claims agent, counsel — and the fee structure are preserved as structural content.
  5. The encrypted mapping is stored for authorized re-identification.
  6. The pseudonymized application is exported for use in ethics-education materials or professional-compensation research.
  7. Batch processing supports a library of applications from one case or across multiple cases for comparative compensation analysis.

What you provide

  • Professional employment application and affidavit of disinterestedness in PDF or DOCX
  • Any supplemental declarations disclosing connections discovered after initial filing
  • Instruction on whether the fee arrangement structure should be retained or also pseudonymized

Limitations & cautions

  • anonym.legal does not assess whether the disclosed connections constitute disqualifying interests under 11 USC §327(a); that is a legal determination for the court.
  • Bar number and state-admission details for individual attorneys are pseudonymized but the jurisdiction of admission is retained as a structural professional credential.
  • Compensation structures referencing publicly available market rates may allow indirect identification of well-known restructuring firms.
  • The tool does not verify conflicts database completeness; it pseudonymizes only the connections that are actually disclosed in the application.

FAQ

Are all parties named in the conflicts check pseudonymized?

Yes. All parties listed in the conflicts-screening exhibit — creditors, equity holders, and professionals — receive pseudonyms consistent with their treatment across all other documents in the case.

Is the proposed fee structure — hourly rates, monthly caps — retained in the pseudonymized output?

Yes. Fee structures and compensation terms are non-personal commercial data preserved verbatim. Only the professional's name and firm are pseudonymized.

Can this workflow cover applications to employ investment bankers and financial advisers as well as counsel?

Yes. The pseudonymization logic applies equally to all categories of professionals employed under 11 USC §327, including financial advisers, investment bankers, and claims and noticing agents.

How are supplemental disclosures filed after the initial application handled?

Supplemental declarations can be processed as part of the same batch, and the engine applies the same pseudonyms to parties already identified in the initial application.

Bankruptcy & Insolvency

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.
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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.