Bakit hindi nakikita ng aking PII detection tool ang mga pangalan at ID sa mga dokumento sa Aleman, Pranses, at Polish?

Karamihan sa mga PII tools ay nakatuon sa Ingles — ang isang German Steuer-ID (11 digits na may checksum), French NIR (15 digits), o Polish PESEL ay may mga natatanging format na hindi kayang maabot ng generic regex patterns. Ang anonym.legal ay gumagamit ng tatlong-tier detection stack: spaCy language-native models para sa 25 high-resource European languages, Stanza para sa 7 karagdagang wika, at XLM-RoBERTa cross-lingual transformers para sa 16 lower-resource languages. Sa 285+ entity types kabilang ang DACH, Nordic, at Eastern European identifiers, ang GDPR-compliant detection ay gumagana sa lahat ng estado ng EU.

Ang aming tool ay nakakakita ng US SSNs ngunit hindi nakikita ang German Steuer-IDs, French NIRs, at Swedish Personnummer — paano kami makakakuha ng kumpletong EU coverage?

ang anonym.legal ay nagbibigay ng 285+ uri ng entidad kabilang ang mga country-specific identifiers: German Steuer-ID (11-digit na may checksum), French NIR (15-digit na may gender indicator), Swedish Personnummer (10-digit na may century indicator), UK NI/NHS numbers, Dutch BSN, Polish PESEL, at marami pang iba. Ang bawat identifier ay may format-specific validation at checksum algorithms na nakabuilt-in. Ang Vanilla Presidio ay nakakakita lamang ng ~55 uri ng entidad — ang anonym.legal ay pinalawak ito ng 5x gamit ang region-specific recognizers.

Ang Presidio ay tanging nakakakita ng mga 55 uri ng entidad — kailangan namin ng mga European tax IDs, IBANs, at German registration numbers. Mayroon bang komprehensibong mga library?

Ang anonym.legal ay nagpapalawak ng ~55 default entity types ng Presidio sa 285+ na may komprehensibong regional coverage: DACH tax at registration IDs, lahat ng EU IBAN formats, Nordic personnummers, UK NHS/NI numbers, APAC national IDs, Latin American CPFs at CUILs, at mga financial identifiers (SWIFT, crypto wallets). Lahat ng recognizers ay may kasamang format validation at checksum verification kung naaangkop.

By George Curta · Last updated 2026-04-072026-04-07

Bumalik sa Mga Tampok

PII Detection: 285+ Uri ng Entidad

Ang aming regex-based detection engine ay tumutukoy ng higit sa 50 uri ng personal na impormasyon na may pattern-based na katumpakan. Parehong input, parehong output - sa bawat pagkakataon.

Subukan Nang Libre Buong Sanggunian ng Entidad

Paano Gumagana ang Pagtuklas

Pattern Matching

Gumagamit ng maingat na nilikhang regex patterns para sa bawat uri ng entidad, na tinitiyak ang pare-pareho at mahuhulaan na mga resulta sa lahat ng dokumento.

Confidence Scoring

Bawat pagtuklas ay may kasamang confidence score (0-1) batay sa lakas ng pattern at konteksto, na tumutulong sa iyo na salain ang mga resulta.

Pagkaalam sa Konteksto

Ang nakapaligid na konteksto ng teksto ay nagpapabuti sa katumpakan ng pagtuklas, binabawasan ang mga maling positibo habang nahuhuli ang mga edge case.

Supported Entity Types

Comprehensive coverage of personal information types across categories

Personal Identifiers

Person Names
Email Addresses
Phone Numbers
Date of Birth
Age
Gender
Nationality

Financial Information

Credit Card Numbers
IBAN
BIC/SWIFT
Bank Account Numbers
Tax IDs
VAT Numbers

Government IDs

Social Security Numbers (SSN)
National ID Numbers
Passport Numbers
Driver's License
Health Insurance IDs

Location Data

Street Addresses
Cities
ZIP/Postal Codes
Countries
GPS Coordinates

Digital Identifiers

IP Addresses (v4/v6)
MAC Addresses
URLs
Domain Names
User IDs

Organization Data

Company Names
Organization IDs
Registration Numbers
Department Names

Temporal Data

Dates
Times
Date Ranges
Timestamps

International Formats

German ID (Personalausweis)
UK National Insurance
Spanish DNI/NIE
Italian Codice Fiscale
And 20+ more country-specific formats

Suporta sa Custom na Entidad

Kailangan bang tuklasin ang mga custom na pattern? Lumikha ng sarili mong mga uri ng entidad gamit ang regex patterns o gamitin ang aming AI-assisted pattern generator.

Manwal na Paglikha ng Pattern

Tukuyin ang mga regex pattern para sa mga proprietary identifier tulad ng mga internal employee ID, project codes, o custom reference numbers.

AI Pattern Generator

Ilarawan kung ano ang nais mong tuklasin sa simpleng wika, at ang aming AI ay bumubuo ng mga optimized regex pattern para sa iyo.

Alamin ang tungkol sa AI Entity Creation →

Simulan ang Pagtuklas ng PII Ngayon

Subukan ang aming detection engine nang libre na may 200 tokens bawat cycle. Walang kinakailangang credit card.

Lumikha ng Libreng Account

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.