PII redaction resource center
Technical guidance for controlling personal data in enterprise workflows.
- Educational guides
- Evaluation guides
- Technical scope
- Implementation questions
Educational guides
Understand the methods and workflows
PII Redaction vs Data Masking vs Tokenization
Compare PII redaction, data masking, and tokenization by reversibility, data utility, security properties, and enterprise use case.
Read guidePII Redaction for AI Prompts
Learn how policy-based PII redaction can protect AI prompts and attachments while preserving useful context for enterprise AI workflows.
Read guidePII Redaction for Logs and Observability
Reduce PII exposure in application logs, traces, error reports, and observability pipelines without removing operational context.
Read guidePII Redaction for Customer Support Data
Apply PII redaction to customer-support conversations before data reaches analytics, AI assistants, vendors, or test environments.
Read guideStructured vs Unstructured PII Detection
Compare PII detection in database fields and JSON with detection in free text, transcripts, documents, logs, and AI prompts.
Read guideEU AI Act and Personal Data in LLM Apps: Checklist
A practical checklist for teams building LLM applications that touch personal data, covering AI Act risk classification, data minimisation, and vendor due diligence.
Read guideDetecting EU PII: IBANs, National IDs, VAT Numbers
A technical guide to detecting EU-specific personal data: IBANs, national identification numbers, VAT numbers, and multilingual names, by format and country.
Read guideEvaluation guides
Compare approaches and requirements
How to Evaluate PII Redaction Software
A practical enterprise checklist for evaluating PII redaction software across detection, policy, deployment, security, and operations.
Read guideEnterprise PII Detection: Requirements and Evaluation
Understand enterprise PII detection requirements for custom data types, multilingual content, policy context, observability, and deployment.
Read guideAI Data Loss Prevention and PII Redaction
Evaluate AI data loss prevention for prompts, attachments, PII redaction, destination policy, and enterprise AI governance.
Read guidePII Redaction API: How to Evaluate One
Evaluate a PII redaction API on detection per data type, reversible tokens, response contracts, latency, data handling and failure modes before integrating.
Read guideAutomated vs Manual PII Redaction
Compare automated and manual PII redaction by scale, consistency, contextual judgment, review requirements, privacy risk, and operating cost.
Read guideOpenAI Privacy Filter vs Presidio vs PII Gateways
Compare OpenAI's open-weight Privacy Filter, Microsoft Presidio and managed PII gateways by detection method, coverage, restoring, deployment and upkeep.
Read guideLiteLLM, Portkey and Kong: Adding PII Masking
Compare how LiteLLM, Portkey, and Kong AI Gateway handle PII masking against a dedicated redaction layer, and where each fits in an existing stack.
Read guideSee it on your own data
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