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By · Last updated 2026-04-20

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HIPAA-uskladeni ChatGPT s browser zastiom PHI

77% zaposlenika tjedno dijeli osjetljive poslovne podatke s AI alatima. Presretanje PII u preglednicku u stvarnom vremenu smanjuje incidente curenja za 94%.

April 20, 20268 min čitanja
HIPAA ChatGPT complianceclinical AI learningPHI browser protectionmedical education AIreal-time PHI interception

Klincki AI problem

Lijeci i medicinski studenti koriste ChatGPT i Claude svaki dan. Provjeravaju doze lijekova. Traze dijagnoze. Pregledavaju planove skrbi. Alati su korisni.

Ali lijepljenje stvarnih pacijentskih podataka u te alate HIPAA je rizik. Tekst odlazi na posluzitelje AI pружatelja. Bez potpisanog Ugovora o poslovnim suradnicima (BAA) za taj servis, akt kri HIPAA. Standardni ChatGPT i Claude racuni ne ukljucuju BAA-ove za klinicku upotrebu.

Mogucnosti nisu dobre. Koristite AI sa stvarnim podacima i riskirajte krsenje. Ili rucno uklonite sve PII iz biljezaka prije lijepljenja — spori korak koji zauzeti klinicari cesto preskacu. Preskakanje stvara upravo onu povredu kojoj je proces trebao sprijeciti.

Zasto rucni pregled ne funkcionira

HIPAA Safe Harbor zahtijeva uklanjanje 18 vrsta identifikatora. Lijecnik ce primijetiti ime pacijenta i datum. Ali neki identifikatori su lako propusteni.

Geo-podobjekti su jedan primjer. Dob u kombinaciji s datumom prijma je drugi — zajedno mogu ciniti pokriveni identifikacijski par prema HIPAA-i. Ti obrasci nisu ocigledni pod vremenskim pritiskom.

Menlo Securityjevo istrazivanje iz 2025. pokazalo je da presretanje PHI u preglednicku u stvarnom vremenu smanjuje curenje za 94%. Taj jaz pokazuje sto klinicari propustaju u usporedbi s onim sto alati hvataju. Cyberhaven podaci potvrduju razmjere: 77% zaposlenika tjedno dijeli osjetljive poslovne podatke s AI alatima.

Kako pomaze prosirenje preglednika

Chrome prosirenje provjerava tekst u trenutku podnosenja. Pokrenuto je prije nego upit stigne do AI-ja. Klinicist vidi kratki pregled. Pokazuje koji je PHI prona den i sto ce biti maskirano.

Ovo nije tvrda blokada. Lijecnik moze nastaviti, urediti ili zaustaviti. Dodaje jednu kratku provjeru inace brzoj radnji.

Uzmite primjer nastavnika interne medicine koji koristi Claude za ucenje temeljeno na slucajevima. Lijepe biljescu slucaja koju su vec pregledali. Prosirenje pokrece drugi prolaz. Ako je biljesca bila cista, nema upozorenja i sesija nastavlja. Ako je detalj proklizio — par datuma ili ime malog mjesta — alat ga hvata prvi.

Ovaj model dobro odgovara klinickom radu. Zadrzava lijecnika u kontroli. Dodaje sigurnosnu mrezu za obrasce koje ljudi cesto propustaju.

Pogledajte nasu usporedbu tocnosti PHI otkrivanja za usporedbe alata. Nas vodic za HIPAA cloud zero-knowledge pokriva BAA pravila i zastite. Vodic za DLP preglednika ima detalje postavljanja.

Izvori

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HHS OCR reported 725 HIPAA breaches in 2024 affecting 275M records — the highest ever. $10.22M average healthcare breach cost.

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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.

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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.

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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

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.