Af hverju Regex, ekki AI?

Fyrir reglugerðarsamræmi þarftu niðurstöður sem þú getur útskýrt og endurtekið. Ákveðna aðferð okkar skilar nákvæmlega því—engir svartir kassar, engar óvæntar uppgötvanir.

Nákvæm samanburður

We use the best tool for each job: deterministic regex patterns for structured data, and proven ML models for names and entities. Built on Microsoft Presidio.

Entity TypeDetection MethodExamples
Strúktúruð Gögn
Regex mynstur
Tölvupóstur, SSN, kreditkort, IBAN, símanúmer
Nöfn & Fyrirtæki
ML líkan (spaCy, Stanza)
Nöfn einstaklinga, nöfn fyrirtækja, staðsetningar
48 Tungumál
XLM-RoBERTa
Kross-tungumálaleg einingaviðurkenning
Endurtekning
100% Endurtekjanlegt
Sama inntak = sama úttak, í hvert skipti
Nafnaviðurkenning
Há Nákvæmni ML
Sannað NLP líkön með trauststigum
Skoðanleiki
+Algerlega skoðanlegt
Staða, tegund, traust fyrir hverja einingu

Hvernig mynsturgreining virkar

Hver einingategund hefur vandlega smíðað regex mynstur sem passa ákveðna snið.

Tölvupóstfang

[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}

Passar staðlaða tölvupóstsnið: local-part@domain.tld

Kreditkortanúmer

\b(?:4[0-9]{12}(?:[0-9]{3})?|5[1-5][0-9]{14}|...)\b

Passar Visa, Mastercard, Amex, og önnur kortasnið með Luhn staðfestingu

Þýska IBAN

DE[0-9]{2}\s?[0-9]{4}\s?[0-9]{4}\s?[0-9]{4}\s?[0-9]{4}\s?[0-9]{2}

Passar þýska IBAN snið með valfrjálsum bilum

Byggt fyrir samræmi

Þegar skoðendur spyrja "hvers vegna var þetta greint?" þarftu skýra svör. Regex-grundvallaða aðferðin okkar veitir nákvæmlega það.

  • GDPR grein 25: Persónuvernd með útskýranlegri úrvinnslu
  • ISO 27001: Skjalaskráð, endurtekning ferli
  • Skoðunarferill: Hver greining er hægt að rekja til ákveðins mynsturs

Dæmi um skoðunarsvar

Q: Hvers vegna var "john.smith@company.com" merkt?
A: Passaði tölvupóstmynstur á stöðu 45-68 með trausti 0.95. Mynstur: staðlað tölvupóstsnið staðfesting.

Upplifðu ákveðna greiningu

Prófaðu regex-grundvallaða PII greiningu ókeypis með 200 tokens á hring.

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.