Protegrity

Founded 1996

Protect sensitive enterprise data and govern access across cloud and artificial intelligence workflows

Pricing model

Demo

Rating

★ People love it

Time to value

Long Setup (> 1 day)

You can use Protegrity to discover, protect, and control sensitive enterprise information across databases, cloud environments, and machine learning pipelines. It tokenizes private data like patient records and financial identifiers at the source so models and analytics systems can work with protected values without exposing readable details. The system enforces access policies, authenticates automated agents, and filters model outputs to prevent sensitive data leakage. You can also generate synthetic data for testing, create anonymized datasets, and track compliance audits across complex data workflows.

What Protegrity does

Scan connected databases for sensitive customer informationDefine encryption and tokenization rules for individual data columnsInspect model inputs and outputs for sensitive text stringsConfigure dual-principal authorization for automated workflowsGenerate privacy-safe synthetic datasets for application testingTrack policy coverage gaps across enterprise data sourcesAudit authorized data decryptions and access logsTokenizes sensitive fields at the source to preserve relational joins without exposing raw dataDiscovers and classifies sensitive data across databases and cloud systemsApplies semantic encryption to provide machine learning models with protected equivalentsControls agent actions using dual-principal authentication for users and autonomous toolsFilters and inspects model outputs to stop inference attacks and data leakageGenerates synthetic data for software testing and model trainingCreates irreversibly de-identified datasets for external analytics

Pricing breakdown

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