Deteksi & Anonimisasi PII Kelas Perusahaan
Regex patterns for structured data, proven ML models for names. Transparent, auditable results on Hetzner's ISO 27001-certified servers in Germany.
Mengapa Memilih 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.
Pelajari tentang teknologi kami →Hetzner Germany, ISO 27001 Certified
Semua pemrosesan terjadi di pusat data bersertifikat ISO 27001 milik Hetzner di Jerman. Data Anda tetap di UE tanpa masalah yurisdiksi yang mengejutkan.
Lihat detail keamanan →Harga Berbasis Token yang Dapat Anda Pahami
Bayar sesuai yang Anda gunakan dengan sistem token transparan kami. Tingkat gratis mencakup 200 token (~15-18 halaman/bulan). Tanpa biaya tersembunyi, tanpa kejutan.
Lihat harga →Integrasi AI dengan Perlindungan Privasi
Hubungkan alat AI Anda seperti Cursor dan Claude Desktop sambil menjaga data sensitif Anda aman dengan anonimisasi PII otomatis.
Your AI Tool
(Cursor, Claude)
MCP Server
(Anonymizes PII)
AI Processes
(Safe data only)
Restore Values
(Optional)
MCP Server bertindak sebagai pelindung privasi antara alat AI Anda dan data sensitif. Ini secara otomatis mendeteksi dan menganonimkan PII sebelum mengirim ke AI, kemudian mengembalikan nilai asli dalam respons—memastikan AI tidak pernah melihat data asli Anda.
Integrasi Alat AI yang Mulus
Bekerja dengan Cursor, Claude Desktop, dan alat kompatibel MCP lainnya
Arsitektur Berbasis Privasi
AI hanya memproses data yang dianonimkan—PII asli tidak pernah meninggalkan kendali Anda
Anonimisasi yang Dapat Dibalik
Tokenisasi memungkinkan Anda mengembalikan nilai asli saat diperlukan
Harga Token yang Sama
Menggunakan saldo token Anda yang ada—tanpa biaya tambahan
Alat AI yang Didukung:
Tersedia di rencana Pro dan Bisnis. Tingkatkan untuk membuka kunci.
Proses Dokumen dengan Aman
Privasi maksimum dengan penanganan file yang aman. Dokumen tetap di perangkat Anda — hanya teks yang diekstrak yang dikirim untuk analisis.
Drag & Drop
(Your files)
Local Processing
(On your device)
Analyze & Anonymize
(Text only)
Save Result
(Stay local)
Aplikasi Desktop memproses dokumen sepenuhnya di perangkat Anda. File dibaca secara lokal, hanya teks yang diekstrak yang dikirim untuk analisis, dan dokumen Anda tetap pribadi.
Penanganan File yang Aman
Dokumen tetap di komputer Anda — hanya teks yang diekstrak yang dikirim ke API aman kami
Penyimpanan Lokal yang Terenkripsi
Riwayat, preset, dan kunci enkripsi disimpan di brankas lokal terenkripsi Anda
Antarmuka Seret & Jatuhkan
Alur kerja yang sederhana dan intuitif—seret file dan dapatkan hasil secara instan
Berbagai Format
PDF, DOCX, TXT, dan lainnya—proses jenis dokumen apa pun
Tersedia untuk:
Mendeteksi nama, email, nomor telepon, kartu kredit, SSN, IBAN, alamat IP, dan lainnya di berbagai kategori.
Dukungan penuh untuk 48 bahasa termasuk Inggris, Jerman, Spanyol, Prancis, dan 43 lainnya dengan dukungan RTL untuk Arab, Ibrani, Persia, dan Urdu. Didukung oleh mesin NLP spaCy, Stanza, dan XLM-RoBERTa.
Ganti, Redaksi, Hash (SHA-256), Enkripsi (AES-256-GCM), atau Masker—pilih metode perlindungan yang sesuai dengan kasus penggunaan Anda.
Keandalan kelas perusahaan dengan pemantauan, cadangan otomatis, dan prosedur respons insiden.
Panduan Kepatuhan & Keamanan Gratis
Unduh sumber daya ahli untuk membantu organisasi Anda melindungi data sensitif dan memenuhi persyaratan kepatuhan.
Lihat Dalam Aksi
Tonton bagaimana anonym.legal melindungi data sensitif secara real-time di alat favorit Anda.

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
Siap Melindungi Data Anda?
Mulai dengan tingkat gratis kami—200 token per siklus, tanpa kartu kredit diperlukan.
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.