
ML-powered data discovery tool for identifying and classifying sensitive data
ML-powered data discovery tool for identifying and classifying sensitive data
Protegrity Data Discovery is a data classification tool that identifies and classifies sensitive data across structured and unstructured sources. The product uses a dual-model architecture combining a machine learning language model (RoBERTa) with a rules-based engine (Presidio) to detect PII, PHI, PCI, and intellectual property. The tool processes unstructured data including natural language text, transcripts, documents, chatbot logs, support tickets, and free-text fields. It provides real-time redaction capabilities for chatbot conversations, automated cleanup of call center transcripts and medical notes, and pre-processing for GenAI RAG pipelines to prevent PII leakage into LLM prompts. Protegrity Data Discovery offers API access through a REST API and Python SDK for integration into applications and workflows. The product can be deployed using Docker containers or Kubernetes environments including AWS EKS for cloud-native scalability. Classification outputs include standard entity types such as PERSON, EMAIL, PHONE, ADDRESS, and CREDIT_CARD, along with confidence scores and character position data for targeted redaction or masking. Discovery results can be fed into Protegrity Governance for policy creation and protection rule refinement.
Common questions about Protegrity Data Discovery including features, pricing, alternatives, and user reviews.
Protegrity Data Discovery is ML-powered data discovery tool for identifying and classifying sensitive data, developed by Protegrity. It is a Data Protection solution designed to help security teams with Kubernetes, PII.
Scans files and databases for unencrypted PII like SSN, names, and addresses
AI-driven data classification platform for automated discovery & labeling
Detects sensitive data (PII, PHI, PCI) across application stacks