Databehandleraftale

For erhvervskunder, der har brug for en formel databehandleraftale (DPA) som en del af deres GDPR-compliancekrav.

Hvad er en DPA?

En databehandleraftale (DPA) er en juridisk bindende kontrakt mellem en dataansvarlig (dig) og en databehandler (anonym.legal), der regulerer, hvordan personoplysninger håndteres.

I henhold til artikel 28 i GDPR skal organisationer have en databehandleraftale på plads, når de anvender tredjeparts databehandlere til at håndtere personoplysninger på deres vegne.

Vores standard-DPA omfatter

✓Genstand og varighed af behandlingen
✓Behandlingens art og formål
✓Typer af personoplysninger, der behandles
✓Kategorier af berørte personer
✓Den dataansvarliges forpligtelser og rettigheder
✓Tekniske og organisatoriske sikkerhedsforanstaltninger
✓Krav til underdatabehandlere
✓Procedurer for underretning om brud på persondatasikkerheden

Anmod om en databehandleraftale

Indtast din e-mailadresse, så sender vi dig et link til at udfylde din organisations oplysninger. Din underskrevne aftale ankommer på e-mail lige bagefter.

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.