Which image formats does image redaction support?

PNG and JPG (JPEG). Other raster formats such as TIFF, BMP, WebP, and GIF are not currently supported.

Does image redaction require a paid plan?

Yes. Image redaction requires a Basic plan or higher. The free plan supports text anonymization only.

How does it find PII inside an image?

The image is run through OCR (Tesseract) to extract its text layer and each piece of text's position, then that text is analyzed by the same PII detector used for documents. Detected regions are covered with a black box on the image itself.

Is the redaction reversible?

No. Image redaction covers the detected region with an opaque black box directly on the image pixels — this is a one-way, visual redaction, not a reversible encryption like the text anonymizer offers.

How accurate is OCR-based detection on scans?

Accuracy depends on scan quality, resolution, and handwriting versus print. Low-quality scans and handwritten text lower OCR accuracy, which lowers detection recall — review redacted output before relying on it for high-stakes documents.

Bumalik sa Mga Tampok

I-redact ang PII sa Loob ng mga Larawan

Ang mga legal na exhibit, na-scan na ID documents, at HR screenshots ay kadalasang may dalang personal na data bilang mga pixel, hindi teksto. Pinapatakbo ng aming image pipeline ang OCR, tinutukoy ang PII sa na-extract na teksto, at tinatakpan ang bawat tugma ng itim na kahon.

Subukan sa Web App API Reference Desktop App

Paano Ito Gumagana

Tatlong hakbang, isinasagawa server-side sa iyong na-upload na larawan.

1. OCR

Kinukuha ng Tesseract ang text layer mula sa iyong PNG o JPG, kasama ang posisyon nito sa pahina.

2. Tukuyin

Ang na-extract na teksto ay dumadaan sa parehong PII detector na ginagamit para sa mga dokumento, na tumutukoy ng mga pangalan, ID numbers, petsa, at iba pang entity kasama ang confidence score.

3. I-redact

Ang bawat natukoy na rehiyon ay tinatakpan ng solidong itim na kahon (ang default na fill) direkta sa larawan, at ang na-redact na file ay ibinabalik para i-download.

Kung Saan Ito Makatutulong

Anumang na-scan o kinunang larawan ng dokumento kung saan ang PII ay nasa loob mismo ng larawan.

Legal Exhibits

I-redact ang mga pangalan, address, at case numbers sa na-scan na exhibits at mga larawan ng ebidensya bago i-produce o i-file.

ID Documents

Takpan ang numero ng passport, driver's license, at national ID sa mga kinunan o na-scan na identity documents.

HR Scans

I-redact ang personal na data sa na-scan na employee forms, timesheets, at onboarding paperwork bago ibahagi o i-archive.

Mga Suportadong Format

Dalawang image format ang suportado sa ngayon.

Suportado

PNG
JPG / JPEG

Hindi Pa Suportado

• PDF page images (gamitin ang PDF pipeline para sa text-layer PDFs sa halip)
• Iba pang raster formats (hal. TIFF, BMP, WebP, GIF)

Basic Plan Pataas

Nangangailangan ang image redaction ng Basic plan o mas mataas. Ang mga account sa free plan ay maaaring mag-anonymize ng teksto ngunit hindi ng mga larawan; ang pag-upgrade ay nagbubukas ng PNG/JPG uploads sa file-size limit ng iyong plano.

Tingnan ang Mga Plano

Mga Madalas Itanong

Aling mga image format ang suportado ng image redaction?

PNG at JPG (JPEG). Ang ibang raster formats tulad ng TIFF, BMP, WebP, at GIF ay hindi pa kasalukuyang suportado.

Nangangailangan ba ng bayad na plano ang image redaction?

Oo. Nangangailangan ang image redaction ng Basic plan o mas mataas. Ang free plan ay sumusuporta lamang sa text anonymization.

Paano nito hinahanap ang PII sa loob ng isang larawan?

Ang larawan ay dumadaan sa OCR (Tesseract) upang kunin ang text layer nito at ang posisyon ng bawat piraso ng teksto, pagkatapos ay sinusuri ang teksto na iyon ng parehong PII detector na ginagamit para sa mga dokumento. Ang mga natukoy na rehiyon ay tinatakpan ng itim na kahon sa mismong larawan.

Nababaligtad ba ang redaction?

Hindi. Tinatakpan ng image redaction ang natukoy na rehiyon ng opaque na itim na kahon direkta sa mga pixel ng larawan — isa itong one-way, visual na redaction, hindi isang nababaligtad na encryption tulad ng inaalok ng text anonymizer.

Gaano kaaasahan ang OCR-based detection sa mga scan?

Ang katumpakan ay nakadepende sa kalidad ng scan, resolution, at kung sulat-kamay o naka-print. Ang mababang kalidad na scan at sulat-kamay na teksto ay nagpapababa sa katumpakan ng OCR, na nagpapababa naman sa detection recall — suriin ang na-redact na output bago umasa dito para sa mga dokumentong may mataas na stakes.

I-redact ang PII sa Iyong mga Larawan

Mag-upload ng PNG o JPG sa web app, o direktang tawagan ang API.

Subukan Nang Libre

Limitations / Important note

OCR-based text extraction is probabilistic; low-quality scans and handwriting lower detection recall.
Redaction is a visual, one-way black box over the detected region — not reversible encryption.
This page is informational and is not legal advice.

How we measure — our methodology

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, held by our hosting provider.
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

Automated checks run on every release.

Each surface gets its own sweep script and report.

Human reviewers spot-check the output each week.

We test detection against sample documents before each release.

A failing unit or integration run stops the release.

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.

Paid plans can buy top-up credits.

Credits reset at the end of each cycle.

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.