SENSITIVE DATA SHOULDN’T BE
OFF-LIMITS.
data behind lengthy approval processes. Your data scientists need real
data to build effective AI—without creating compliance headaches.
95% OF AI PROJECTS FAIL. HERE’S WHAT 5% DO DIFFERENTLY.
Organizations across industries need to move faster with AI—but sensitive data is the bottleneck. Traditional controls can’t keep up as policies fracture across tools and clouds, RBAC starves models of useful signals, and “safe” data copies multiply risk. GenAI expands the surface area for data risk at every stage—training, prompting, outputs, and multi-agent interactions. Without built-in safeguards, organizations face:
COMPLIANCE
RISKS
SENSITIVE
DATA LEAKS
STALLED
AI INNOVATION
SENSITIVE DATA IS SLOWING YOUR AI DOWN. FIX THAT.
Zero trust for AI means your data carries its own security everywhere it flows—from warehouse to vector database to LLM prompt—automatically enforcing the right access for each use case. Instead of copying and sanitizing datasets for each AI project, your teams get instant access to protected, production-ready data that adapts its permissions based on who’s using it and how.
Ship AI faster—without leaking data.
Data scientists and ML teams don’t have time to wrestle with sensitive data. Protegrity eliminates manual prep and duplicate datasets, embedding protection directly into your data. Your teams get compliant, production-ready data from Day 1, and your models get instant access to approved signals—so you can ship AI faster, without compromising security.
Prove compliance on demand.
Auditors and regulators don’t want promises—they want proof. Protegrity unifies policy enforcement and audit trails across your AI pipeline—ingestion, training, orchestration, and output. You get continuous, provable control, showing protection was enforced every step of the way.
Protection that keeps up with AI.
Native cloud tools are duct tape—fine for a patch, not for securing tomorrow’s AI pipelines at scale. Protegrity’s vendor-agnostic zero-trust fabric seamlessly connects clouds, data warehouses, and AI platforms like AWS, Azure, GCP, Databricks, and Snowflake. Because federated protection lives with the data itself, your data stays protected through every change in tools, models, and environments—without constant rebuilds, brittle integrations, or risky blind spots.
COMPLETE PORTFOLIO OF AI PROTECTION METHODS
Our modular capabilities work together to safeguard the full AI pipeline at every stage of your GenAI journey—all unified in one platform.
Real-time discovery and protection of sensitive data at ingest, output, and everywhere in between.
Irreversibly transform PII for privacy-preserving analytics and AI model training.
Ask questions of structured data in plain language, with embedded protection ensuring insights stay secure.
Dynamic, context-aware controls that prevent data leakage and block unsafe interactions in real time.
Generate statistically accurate, bias-aware datasets without exposing sensitive information.
