By · Last updated 2026-05-01

Späť na blogGDPR a Dodržiavanie

Interne identifikatory zamestnancov su tiez osobne udaje

Kazda velka organizacia ma vlastne interne identifikatory, ktore spajaju anonymizovane zaznamy so skutocnymi ludmi. 34 % pokut GDPR sa tyka neadekvatnych technickych opatreni.

May 1, 20268 min čítania
employee ID anonymizationproprietary identifier detectionquasi-PIIGDPR custom entitiesno-code pattern builder

Co su kvazi-osobne udaje?

GDPR Clanok 4 pokryva akekolvek udaje, ktore mozu identifikovat osobu. Udaje nemusia priamo niekoho menovovat. Staci, aby umoznili identifikaciu prostrednictvom dalsich krokov.

Interne identifikatory zamestnancov su jasnym prikladom. Vezmite hodnotu "EMP-EU-123456". Tento retazec nikoho nenaziva. Ale HR system obsahuje jednoduchu vyhladavaciu tabulku. EMP-EU-123456 odkazuje na Mariu Schmidtovu, Seniorna Inzinierka, Mnichov. Kazdy s pristupom k tejto tabulke ju moze najst. Podla GDPR je toto ID osobny udaj.

Rovnake pravidlo plati aj pre ine interne kody:

  • Cisla klientskych uctov, ktore odkazuju na zaznamy v CRM
  • Projektove kody, ktore odkazuju na mena klientov v zmluvnych systemoch
  • Cisla odkazov na pripady v pravnych suboroch
  • Cisla zdravotnych zaznamov, ktore odkazuju na zaznamy pacientov

Odstranenie mien a e-mailov nestaci. Ak v subore zostanu interne identifikatory, re-identifikacia je iba dva kroky vzdialenosti.

Preco tato medzera vedie k pokutam

34 % vsetkych pokut GDPR sa tyka neadekvatnych technickych opatreni podla Clanku 32. Tento udaj pochadzza zo spravy DLA Piper 2025 GDPR Annual Report. Neschopnost detegovat kvazi-identifikujuce interne identifikatory patri do tejto kategorie.

EDPB vybavil v roku 2024 viac ako 900 pripadov v ramci koordinacneho mechanizmu. Cezhranicne vymahanie znamena, ze jedna medzera v zdielanych datasetoch moze viest k koordinovanemu konaniu napriec niekolgymi clenskimi statmi EU.

Standardne nastroje na ochranu osobnych udajov nachadzaju univerzalne vzory: mena, e-maily, telefonne cisla, narodne identifikatory. Nepoznaju vas interny format ID. Ziadny nastroj ho nepozna, kym mu to nepoviete. To je ta medzera.

Ako funguje tvorca vzoru bez kodu

Globalna logisticka spolocnost potrebuje anonymizovat zaznamy zamestnancov pre externy audit. Ich zamestnanecke ID pouzivaju tento format: EMP-[REGION]-[6 cislic]. Tri priklady: EMP-EU-123456, EMP-APAC-789012, EMP-AMER-345678.

Compliance tim vlozi tri priklady do pomocnika vzoru AI. AI vrati:

  • Vzor: EMP-[A-Z]{2,4}-\d{6}
  • Zodpoveda vsetkym trom prikladom
  • Navrhnuty nazov entity: EMPLOYEE-ID
  • Odporucany dalsi krok: otestovat s viacerymi kodmi regionov

Tim otestuje dalsich desaf vzoriek. Vzor funguje pre vsetky.

Ulozia vlastnu entitu do zdielaneho GDPR prednastavenia timu. Vsetkych 47 dokumentov v baliku auditu sa spracuje v jednej davke. Kazde zamestnanecke ID je nahradene rolovo zalozitym stitkom. Auditna firma dostane subory, ktore uz neodkazuju na ziadnu jednotlivcu.

Netreba ziadna pomocna inzinierstna pomoc. Cely setup trva menej ako hodinu.

Co nasleduje

Ak je vlastna entita ulozena v zdielaNom prednastaveni, vsetci clenovia timu pouzivaju rovnake nastavenie. Novy personel ho dostane na prvom dni. Davkove ulohy, volania API a rucne nahravania pouzivaju rovnaky vzor.

Auditny zaznam zobrazuje, ktore prednastavenie bolo pouzite pre kazdy subor. Ak DPA pozada o dukazy vasho procesu anonymizacie, mozete ich predlozit.

Pre cely pracovny postup nastavenia vlastnej entity pozrite vlastne PII identifikatory pre organizacnu anonymizaciu. Pre udrzanie tohto nastavenia konzistentneho napriec timami pozrite prednastavenia konzistentnosti anonymizacie pre audit GDPR.

Zdroje

Pripravení chrániť vaše údaje?

Začnite anonymizovať PII s 285+ typmi entít v 48 jazykoch.

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.