Find Sensitive Data Everywhere. So You can protect it anywhere.

Combines ML language understanding with pattern-matching rules for better results

Identify common sensitive data types (names, emails, SSNs, CC#s, etc.)

Tuned for high precision and recall in finding PII/PHI accurately

Analyze free-text fields and documents often missed by traditional DLP tools

Ideal for cleaning data before use in chatbots, RAG pipelines, or AI models

Handles semi-structured text alongside fully unstructured content effectively

Embed PII detection directly within your custom application logic

Automatically trigger downstream redaction, masking, or other protection actions

Includes API Playground for rapid testing

Run standalone Docker containers for local testing or small-scale deployments

Scale discovery workloads effectively using Kubernetes in private or public cloud

Deploy securely within internal enterprise environments

Outputs standard entity types (e.g., PERSON, EMAIL, PHONE, ADDRESS, CREDIT_CARD)

Includes a confidence score for filtering results or prioritizing actions

Provides start/end character positions to support targeted redaction or masking

Identify exactly where sensitive data exists to prioritize protection efforts

Use classification results to automate or streamline refinement of refine policy definitions

Enable risk-based data protection strategies based on identified data sensitivity