HIPAA OCR: 725 Breaches, 275M Records
HHS OCR reported 725 HIPAA breaches in 2024 affecting 275M records — the highest ever. $10.22M average healthcare breach cost.
Handwritten Form OCR & PII Detection
A mid-size hospital processes 50,000 handwritten intake forms per year. Manual PII redaction at this volume requires 0.5 FTE.
HHS 2025: AI Clinical Notes Need PHI
AI transcription systems can inadvertently put Patient A's PHI in Patient B's record. Here's why real-time PHI detection before EHR commit is the control.
HIPAA MRN Detection Without a Regex PhD
Every hospital's MRN format is different. Memorial uses MRN:XXXXXXX, St. Mary's uses PT-YYYYY, University Hospital uses UHN-XXXXXXXXXX.
HIPAA: Hospital-Specific MRN Detection
HIPAA Safe Harbor requires removing medical record numbers — but MRN formats are not standardized. Epic, Cerner, and Meditech all use different formats.
HIPAA Safe Harbor De-ID at Scale
HIPAA Safe Harbor requires removing 18 specific PHI identifier categories. Academic medical centers need de-identification at scale but existing tools.
ISO 27001 & HIPAA BAAs for Healthcare
HIPAA Business Associate Agreements require 'satisfactory assurances' of appropriate safeguards. ISO 27001 maps directly to HIPAA 164.
Custom MRN Detection Without Code for HIPAA
Medical Record Numbers are hospital-specific — every healthcare system uses a different format. HIPAA Safe Harbor requires removing MRNs.
18 HIPAA Identifiers Your Tool Misses
HIPAA lists 18 PHI identifiers. Most anonymization tools detect maybe 6 of them. Medical Record Numbers vary by institution with no standard US format.
Reversible Encryption for Re-Contact
You can't contact Patient_001 for a follow-up visit. IRBs now require documented re-identification protocols — proving you CAN re-identify under.
Reversible De-ID for Clinical Research
When a study finds unexpected biomarker risk in 47 of 5,000 participants, researchers need to contact real patients. Only 23% of anonymization tools offer.
HIPAA ChatGPT with Browser Protection
77% of employees share sensitive work information with AI tools at least weekly. Real-time browser PII interception reduces leakage incidents by 94%.
Batch Processing 50K Clinical Notes Locally
A February 2026 SDNY ruling found AI-processed documents lose attorney-client privilege if not anonymized before processing.
LLMs Miss 50% of Clinical PHI
A 2025 study found LLMs miss more than 50% of clinical PHI in multilingual documents. 34.8% of all ChatGPT inputs contain sensitive data.
Explainable Redaction: HIPAA Audits
HIPAA Expert Determination requires documented methodology. Legal e-discovery requires per-redaction grounds. 34% of DPOs report insufficient tools for.
HIPAA in the Cloud: Zero-Knowledge for PHI
Business Associate Agreements don't prevent HIPAA violations when your cloud AI vendor processes PHI in plaintext. Here's what zero-knowledge architecture.
When CISOs Say No to Cloud PHI Processing
725 healthcare data breaches in 2024 affected 275 million records. With $10.22M average breach costs—highest of any industry—healthcare CISOs are.
PHI Detection: Snow Labs 96% vs GPT-4o
Not all de-identification tools are equal. ECIR 2025 benchmarks show F1 scores from 79% to 96%. Learn why accuracy matters and how to evaluate tools.
$7.42M: Healthcare Breach Costs Lead
Healthcare has been the #1 costliest industry for data breaches for 14 consecutive years. Learn why PHI is so valuable and how to protect it.
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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.