anonym.legal

By · Last updated 2026-02-19

Վերադառնալ բլոգինGDPR & Համապատասխանություն

€4.7 Mlrd. Ameyrqyan Entanikneryne Tvum en GDPR Tuyzheri 83%-y

Ameyrqyan entanikneryn stecel en €4.7 mlrd. GDPR tuyzhner — bolor karatvacutyunneri 83%-y: Imacek, inchu en morak sahmany heratsararutyunnery aynkan vatotyun, ev inchpes hasnel hamapaymanyatman:

February 19, 20268 րոպե կարդալ
GDPRdata protectionSchrems IIcross-border transfers

€4.7 Mlrd.: Ameyrqyan Entanikneryne Tvum en GDPR Tuyzheri 83%-y

Tuyzhi Barcharakumam

2018 thvakanicen i ver, EU karravarutyunnery tavadrekin en €6.2 mlrd.-ic avorelyin GDPR tuyzher: Barcharakumam ayspishov e: €4.7 mlrd. — 83%-y — cnum e Ameyrqyan entaniknerum:

Tasum khmber mec tuyzhnerits utiy Ameyrqyan texekayin entaniknerum e:

Tasu Mec GDPR Tuyzhnere

KaragEntanikamTuyzhPatcharyTar
1Meta (Irlandia)€1.2 mlrd.EU-US heratsararutyunner2023
2Amazon (Luxembourg)€746 mln.Npalatayi gadnerner2021
3TikTok (Irlandia)€530 mln.Heratsararutyunner depy Chna2025
4Instagram (Irlandia)€405 mln.Manavardinerus grancumer2022
5Meta (Irlandia)€390 mln.Gadnereneri iravakan hivand2023
6TikTok (Irlandia)€345 mln.Manavardinerus gaxtnuytumam2023
7LinkedIn (Irlandia)€310 mln.Varchkayin velutzuytumam2024
8Uber (Niderlannder)€290 mln.Vararordi grancumer US2024
9Meta (Irlandia)€265 mln.Khnayman vrachagrum2022
10WhatsApp (Irlandia)€225 mln.Thafancikutyumam2021

Amena mec tuyzhnere kcum en mek patcharov: Morak sarhman heratsararutyunner: Meta-n inknutyamb — nerkayacnum en Instagram-n ev WhatsApp-n — kcum e €2.4 mlrd.:

Inchu en Chaxorum GDPR-y US Heratsararutyunnery

Schrems II Verdiky

2020 thvakani hulisin EU datarany bataretsav Privacy Shield-y: US harkakayin qaghakakanneryt bacarum en EU gaxtnuytyan iravunqnerit: Ayd verdiky hivandut e Schrems II anunov:

Ayn unes ergkusutyan galachkayin haskanutyan.

  • Standarttayin Paymanagrakannery (SCC) mi-ayakannery bavarar chen
  • Entanikneryn petk e sthrei, tu US iravunqum te ardarachart pashtpanutyun e
  • Heratsararutyunneri mec masam petk e havalumat texaykayin qaylerov

CLOUD Act-i Khndiry

US iravunqy karog e ameryqyan entaniknerus parchel handel zgramanishvats grankumery: Ays irakan e nayev aturp grankumery EU sererverum ken: CLOUD Act-n hnaravor e karayin maremnerum US entaniknerum patkanetselutsits hetevord tvialnery — Eraqarrum:

Ays kerevory e US ameghakavar matorichner EU-um:

Erku Kentronakan Tuyzhnery

Meta-i €1.2 Mlrd. Tuyzhn (2023)

Irlandiay DPC-n haskatsets, vor Meta-n EU-i ogtaterneri grankumery US-ic ugharkel e aranc iravabanayin himqi: Meta-n petk eyr dagadrel EU-US bolor heratsararutyunnery hingeran araxatum: Ays GDPR-i patmutyan mej amba mec tuyzhn er:

Uber-i €290 Mln. Tuyzhn (2024)

Niderlanndernerum karravarutyunnery tuyzhetin Uber-in vararordneri grankumery US-orum: Uber-n ogtagercuts Standarttayin Paymanagrakanner: Baits ayn chamvats er Schrems II-i petaborir lracukal pahpanordnery:

Inchy en Checum Karravarutyunnery

Zbagavarnery ayjm nayum en yerex banin.

  1. Ardu arhek anrashest e heratsararutyuny?
  2. Hegnak pahpanordner ka?
  3. Npatakakanum ikrutyan iravunky te ardarachart pahpanutyun e?

Lavaguyln: EU Tvyalneri Inkishshkhanutyunam

Amena avely anvtang ugy e andznayin grankumery EU-i mech pahu: Ays krdakel e morak sarhmani risky armatayghbyurim:

Anonym.legal Enqararakutyunam

HatkutyanMeqnabanuthyan
PanavorutyumamHetzner, Germaniya (ISO 27001)
AmeghakavarChi AWS, Azure, kam GCP
Mshakum100% EU serrver
EnqararakutyumamGermanayin iravaban enqararakutyumam
CLOUD ActKamaynakanat chi — US chnchushch chi ka

Zero-Knowledge Dzevachafumam

Mer zero-knowledge karnaqumamam avelelutsich pahpanumam er lracukal xavum.

  • Gaxtnabaner erbeq chi lqunum jer sarikumit
  • Bunhishkvere ksmutyan garum en
  • Mer mej chi karogh kartal jer bovandutyune nayev iravunqayin karuthi dem
  • Mez hneravogutyamb galatanq chi ka mer bunqum

Tes mer anvartsutyan hamapaymanyatsmatsman aganaket lriv texaykayin karaperutyunneri hamar:

Qaylerov US Entaniknerits

1. Katareq Ynknum Andzrery

Nakhqan ays heratsararutyam anunekutyunnery anonymizereq: Ukararkeq liakatar petakanny:

2. Ogtagerek EU Matorichner

EU ogtaterneri grankumneri hamar entrek EU-i vra himnakets tzarrayutyunnernery, karchelin: Mer GDPR hamapaymanyatsmatsman ughekaychy kavetum e, inchpes entrel tzarrayutyunnery:

3. Lracukal Pahpanutyunner Avelacel

Etu heratsararutyunnery petk en linin, kireq gakhtnagrum ev tokenizacuya: Avelnery arxavarum en US mardamaramnerum khorhamcnely nayev buzhich dem:

4. Heratsararutyan Yndlaynum Bacahaytutyumam Katarel

Nkaragrekeq jer velutyuny, tu ardu npatakakanum iravunqy pashtpanem e EU grankumery: Tvyalneri pahpanutyuncagirere ayjm petum en ayd or standardayin qayl lini:

Inchpes e Oknum Anonym.legal-n

Heratsararutyunic arraj: Pashat anunekutyunnery jeternerov pastakereq: Ugrarkeq tokenizatsvacanq: Kanchik aryunqery EU-um pahek:

Hamapaymanyatsmatsman hamar: Germaniayin panavorutyumam, zero-knowledge dzevachafum, amljovakan avakandrneri hetqerel ev GDPR-i hamar anvtang lracelutsich:

Gner: Antchar sarq: 200 jetoner amsakan: Hashayin: €3/amsic: Bznesh: €29/amsic:

Ssksei pahpanel EU grankumery ajsor: Sksei antchar verschen:

Akbyurner

Հոդվածներ, որոնք կապված են

GDPR & Համապատասխանություն

Japan My Number: Verhoeff & APPI

63% of generic tools fail My Number detection in Japanese documents. My Number uses Verhoeff algorithm — the most complex national ID checksum in Asia.

GDPR & Համապատասխանություն

HDPA Greece: AFM & AMKA Detection

Greek AFM detected with 52% accuracy by generic tools. HDPA issued 89 decisions in 2024 — up 162% from 2022. Tourism and maritime sectors face distinct.

GDPR & Համապատասխանություն

NAIH Hungary: TAJ-Szám and Adóazonosító Jel

Hungarian NER accuracy is 67% vs. EU average 82% — NAIH's 2024 assessment. TAJ-szám weighted checksum and adóazonosító jel detection gaps.

Պատրաստ եք պաշտպանելու ձեր տվյալները?

Սկսեք PII անանոնիմացնել 285+ կազմակերպության տեսակներով 48 լեզուներով:

Սկսեք անվճար փորձաշրջանԴիտել առանձնահատկությունները

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.