By George Curta · Last updated 2026-06-30
PII Anonymization API for Developers
An anonymization API is a developer endpoint that strips PII from text inside your own pipelines. Ship privacy-first applications with anonym.legal's REST endpoints for CI/CD integration, MCP Server for AI tools, and consistent anonymization across 48 languages.
Utfordringen
Utviklingsteam møter konstant spenning mellom realistiske testdata og databeskyttelse:
- •Produksjonsdata inneholder sensitive personopplysninger som ikke kan brukes direkte
- •Syntetiske data mangler ofte realismen som trengs for meningsfull testing
- •Manuell anonymisering er tidkrevende og feilutsatt
- •Ulike miljøer trenger konsistente, reproduserbare data
# Anonymize test data in CI/CD pipeline
curl -X POST https://anonym.legal/api/presidio/anonymize \
-H "Authorization: Bearer $API_TOKEN" \
-H "Content-Type: application/json" \
-d '{"text": "Contact john@company.com", "anonymizers": {"DEFAULT": {"type": "replace"}}}'Løsningen
Integrer anonymisering av personopplysninger direkte i utviklingsarbeidsflyten din med vår RESTful API.
REST API
Enkelt JSON API for integrasjon i alle teknologistabler. Analyser og anonymiser i en enkelt forespørsel.
CI/CD-klar
Automatiser generering av testdata i pipelinen. Konsistente resultater hver gang.
Reproduserbar
Samme inndata, samme utdata. Deterministiske resultater for pålitelig testing.
Rask
Behandle tusenvis av poster per minutt. Ingen GPU nødvendig.
API Endpoints
Simple REST API with bearer token authentication. Integrate in minutes.
| Endpoint | Method | Description |
|---|---|---|
| /api/presidio/analyze | POST | Detect PII entities in text |
| /api/presidio/anonymize | POST | Anonymize detected entities |
| /api/image | POST | Redact PII from images |
| /api/structured | POST | Process CSV/Excel files |
| /api/presidio/entities | GET | List supported entity types |
Integration Options
REST API
Standard REST endpoints with JSON payloads. Works with any language or framework.
- Bearer token authentication
- Batch processing support
- Webhook callbacks (Pro+)
MCP Server
Model Context Protocol integration for AI tools like Claude Desktop and VS Code.
- analyze, anonymize, deanonymize tools
- estimate_cost for pricing transparency
- Multi-language support in tool calls
Built for developers
Begynn å bygge i dag
200 gratis tokens per måned. Full dokumentasjon tilgjengelig.
Limitations / Important note
- Rate limits and endpoint availability depend on your plan; build in retry/backoff handling.
- Detection results are probabilistic; validate before automated downstream use. This is not legal advice.
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.
Related reading
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 company HQ is in Saarbrücken, Germany. Our servers run in Hetzner's Falkenstein datacenter.
Hetzner holds 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
- Open the web app and try a sample file.
- Learn how credits get counted.
- See current plans and limits.
- Meet the team behind the product.
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.