casesUse Cases

PII Redaction for Every Pipeline.

From LLM pre-processing to log sanitization — see how European developers use euRedact to build GDPR-compliant applications.

AI EngineersML TeamsData Scientists

LLM Pre-Processing

Strip PII before it reaches your AI models.

Sending customer data to LLMs creates GDPR compliance risk. euRedact runs locally, removing structured PII from prompts before they leave your infrastructure — so your AI pipeline stays compliant without sacrificing functionality.

  • check_circleRedact names, IDs, and IBANs before calling OpenAI, Anthropic, or local models
  • check_circleZero-latency inline processing — no extra API round-trip
  • check_circleWorks with RAG pipelines, chat systems, and batch processing
from euredact import redact

# Sanitize before sending to your LLM
clean = redact(user_message, country="NL")
response = llm.chat(clean.redacted_text)
Legal TeamsCompliance OfficersDPOs

Document Anonymization

Anonymize contracts, reports, and case files at scale.

Legal teams, insurance companies, and government agencies process thousands of documents containing personal data. euRedact detects and replaces PII across 32 European country formats — from Dutch BSNs to German Steuer-IDs — in a single function call.

  • check_circleChecksum-validated detection eliminates false positives on national IDs
  • check_circleReferential integrity preserves document readability (NAME_1, IBAN_1)
  • check_circleProcess PDFs, Word documents, and plain text with consistent results
from euredact import redact

result = redact(contract_text, country="DE")
# "Herr Max Mustermann, Steuer-ID 12345678901"
# → "Herr [NAME_1], [STEUER_ID_1]"
DevOps EngineersSREsPlatform Teams

Log Sanitization

Clean PII from logs before they reach your SIEM.

Application logs routinely capture email addresses, phone numbers, and national IDs. euRedact integrates into your logging pipeline to strip structured PII in real-time — keeping your observability stack GDPR-compliant without manual review.

  • check_circleSub-millisecond processing handles high-throughput log streams
  • check_circleDetect emails, phone numbers, IBANs, and 25+ PII entity types
  • check_circleDrop-in integration with Python logging, Node.js streams, or batch jobs
import logging
from euredact import redact

class PIIFilter(logging.Filter):
    def filter(self, record):
        result = redact(record.getMessage())
        record.msg = result.redacted_text
        return True
Data EngineersAnalytics TeamsDBAs

Database Field Redaction

Mask PII columns before exporting or sharing data.

When sharing datasets with third parties, analytics teams, or across departments, PII must be removed. euRedact processes database exports field-by-field, detecting country-specific identifiers that generic tools miss entirely.

  • check_circleBatch-process CSV, JSON, or database rows efficiently
  • check_circleCountry-aware detection catches formats US tools ignore
  • check_circleDeterministic output — same input always produces the same result
import pandas as pd
from euredact import redact

df = pd.read_csv("customers.csv")
df["notes"] = df["notes"].apply(
    lambda x: redact(x, country="BE").redacted_text
)
ResearchersML EngineersUniversities

Research & Training Data

De-identify datasets for ML training and academic research.

Machine learning teams and researchers need real-world data without real-world PII. euRedact's referential integrity mode preserves data structure and relationships while replacing all identifiable information — enabling compliant model training on European datasets.

  • check_circleConsistent labels across documents (NAME_1 stays NAME_1)
  • check_circlePreserves statistical properties of the underlying data
  • check_circleSupports GDPR Article 89 research exemption workflows
from euredact import redact

for doc in research_corpus:
    result = redact(doc, country="FR",
                    referential_integrity=True)
    clean_corpus.append(result.redacted_text)
Support LeadsProduct ManagersQA Teams

Customer Support Pipelines

Redact tickets and chat logs for analytics and QA.

Support teams accumulate vast amounts of personal data in tickets, chat transcripts, and email threads. euRedact cleans these before they reach analytics dashboards, QA tools, or third-party integrations — protecting customer privacy at every step.

  • check_circleProcess Zendesk exports, Intercom logs, or custom ticket systems
  • check_circleDetect PII across multiple European languages in a single pass
  • check_circleEnable safe sharing of support data with product and engineering teams
from euredact import redact

for ticket in zendesk_export:
    clean = redact(ticket["body"],
                   country="NL")
    ticket["body"] = clean.redacted_text

Built for European Industries

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Legal & Compliance

Law firms anonymizing case files, contracts, and court documents for sharing or archival.

local_hospital

Healthcare

Hospitals and health-tech de-identifying patient records for research and inter-departmental sharing.

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Financial Services

Banks and fintechs redacting transaction data, KYC documents, and customer communications.

apartment

Government & Public Sector

Agencies processing citizen data for FOI requests, inter-department transfers, and open data.

school

Education & Research

Universities de-identifying student records, survey data, and research corpora for GDPR compliance.

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Insurance

Insurers anonymizing claims data, medical reports, and policy documents for actuarial analysis.

Your Use Case. Our SDK.

euRedact handles structured PII redaction for any European data pipeline. Get started in under a minute.

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