Utambuzi wa PII na Kuanonymize kwa Kiwango cha Biashara
Regex patterns for structured data, proven ML models for names. Transparent, auditable results on Hetzner's ISO 27001-certified servers in Germany.
Kwa Nini Uchague anonym.legal
Deterministic Pattern Detection
Regex patterns for structured data (emails, SSNs, credit cards) give 100% reproducible results. ML-based NER for names and organizations provides high consistency. Fully auditable for compliance.
Jifunze kuhusu teknolojia yetu →Hetzner Germany, ISO 27001 Certified
Usindikaji wote unafanyika katika vituo vya data vya Hetzner vilivyothibitishwa na ISO 27001 nchini Ujerumani. Data yako inabaki ndani ya EU bila matatizo ya mamlaka yasiyotarajiwa.
Tazama maelezo ya usalama →Bei za Kulingana na Token ambazo Unaweza Kuelewa
Lipa kwa kile unachotumia kwa mfumo wetu wa wazi wa token. Kiwango cha bure kinajumuisha token 200 (~15-18 kurasa/ mwezi). Hakuna ada zilizofichwa, hakuna mshangao.
Tazama bei →Ushirikiano wa AI na Ulinzi wa Faragha
Unganisha zana zako za AI kama Cursor na Claude Desktop huku ukihifadhi data zako nyeti salama kwa kuanonymize PII kiotomatiki.
Your AI Tool
(Cursor, Claude)
MCP Server
(Anonymizes PII)
AI Processes
(Safe data only)
Restore Values
(Optional)
MCP Server inafanya kazi kama kinga ya faragha kati ya zana zako za AI na data nyeti. Inatambua kiotomatiki na kuanonymize PII kabla ya kutumwa kwa AI, kisha inarudisha thamani za asili katika majibu—hakikisha AI haioni data yako halisi.
Ushirikiano wa Zana za AI Bila Mshindo
Inafanya kazi na Cursor, Claude Desktop, na zana nyingine zinazofaa za MCP
Muundo wa Kwanza wa Faragha
AI inashughulikia data zilizokuanonymize tu—PII ya asili haitoki kwenye udhibiti wako
Kuanonymize Kunayoweza Kurudiwa
Tokenization inakuruhusu kurudisha thamani za asili unapohitaji
Bei za Token Zilezile
Inatumia salio lako la token lililopo—hakuna gharama za ziada
Zana za AI Zinazoungwa Mkono:
Inapatikana kwenye mipango ya Pro na Biashara. Pandisha ili kufungua.
Sindikiza Hati kwa Usalama
Faragha ya juu na usimamizi salama wa faili. Hati zinabaki kwenye kifaa chako — maandiko pekee yanayochukuliwa yanatumwa kwa uchambuzi.
Drag & Drop
(Your files)
Local Processing
(On your device)
Analyze & Anonymize
(Text only)
Save Result
(Stay local)
Programu ya Desktop inasindika hati zote kwenye kifaa chako. Faili zinapitiwa kwa ndani, maandiko pekee yanatumwa kwa uchambuzi, na hati zako zinabaki kuwa za faragha.
Usimamizi Salama wa Faili
Hati zinabaki kwenye kompyuta yako — maandiko pekee yanatumwa kwa API yetu salama
Hifadhi ya Mitaa Iliyojificha
Historia, mipangilio, na funguo za ushirikishaji zinahifadhiwa kwenye vault yako ya ndani iliyo na ushirikishaji
Kiolesura cha Drag & Drop
Mchakato rahisi, wa kueleweka—vuta faili na pata matokeo mara moja
Format Nyingi
PDF, DOCX, TXT, na zaidi—sindikiza aina yoyote ya hati
Inapatikana kwa:
Tambua majina, barua pepe, nambari za simu, kadi za mkopo, SSNs, IBANs, anwani za IP, na zaidi katika makundi mbalimbali.
Msaada kamili kwa lugha 48 ikiwa ni pamoja na Kiingereza, Kijerumani, Kihispania, Kifaransa, na nyingine 43 zikiwa na msaada wa RTL kwa Kiarabu, Kihebra, Kifarsi, na Kihindi. Inasimamiwa na spaCy, Stanza, na XLM-RoBERTa NLP engines.
Badilisha, Ficha, Hash (SHA-256), Encrypt (AES-256-GCM), au Ficha—chagua mbinu ya ulinzi inayofaa kwa matumizi yako.
Uaminifu wa kiwango cha biashara na ufuatiliaji, nakala za kiotomatiki, na taratibu za majibu ya matukio.
Miongozo ya Uzingatiaji na Usalama Bila Malipo
Pakua rasilimali za kitaalamu zinazosaidia shirika lenu kulinda data nyeti na kutimiza mahitaji ya uzingatiaji.
Orodha ya Ukaguzi ya Uzingatiaji wa GDPR
Mfumo wa ukaguzi wa pointi 50
14 pages • PDF
Mwongozo wa Kuzuia Uvujaji wa Data kwa AI
Linda data dhidi ya zana za GenAI
18 pages • PDF
Mwongozo wa Uzingatiaji wa HIPAA
Inajumuisha vitambulisho vyote 18 vya PHI
22 pages • PDF
Utafiti wa Kesi wa Kuficha Utambulisho wa PII
Uchambuzi wa usanifu mseto
11 pages • PDF
Tazama jinsi inavyofanya kazi
Tazama jinsi anonym.legal inalinda data nyeti kwa wakati halisi katika zana unazopenda.
Latest Insights
Research, guides, and analysis on data privacy
Japan My Number: Verhoeff & APPI
63% of generic tools fail My Number detection in Japanese documents. My Number uses Verhoeff algorithm — the most complex national ID checksum in Asia.
HDPA Greece: AFM & AMKA Detection
Greek AFM detected with 52% accuracy by generic tools. HDPA issued 89 decisions in 2024 — up 162% from 2022. Tourism and maritime sectors face distinct.
NAIH Hungary: TAJ-Szám and Adóazonosító Jel
Hungarian NER accuracy is 67% vs. EU average 82% — NAIH's 2024 assessment. TAJ-szám weighted checksum and adóazonosító jel detection gaps.
Explore anonym.legal
Tayari Kulinda Data Yako?
Anza na kiwango chetu cha bure—token 200 kwa mzunguko, hakuna kadi ya mkopo inahitajika.
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
- Common questions
- Glossary
- How tokens work
- Security posture
- Where we comply
- What we detect
- Case studies
- Release notes
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
- 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.