Protect
Your Data
in AI Models
use in AI systems without slowing teams or breaking compliance.
Define Policy Once.
Enforce It Everywhere.
Traditional security was built to control infrastructure and identities.
AI requires security that governs data.
Protegrity decouples policy, enforcement, and cryptography to enable secure computation on protected data — enforcing governance in real time across on-prem, cloud, and SaaS.
Users — Apps — Models
- Compliance
- Quantum
- Sovereign Data
- Secure Agents
- Secure Inferencing
-
Control
Plane- Discovery & Classification
- Centralized, Agentic Policy
- Real-Time Audit & Observability
-
Execution
Plane- API & Endpoints
- Semantic Tokens & Guardrails
- Pseudonymization & Anonymization
-
Advanced
Cryptography- Vault & Vaultless
- Queryable Encryption
- Iceberg Encrypted Data Type
Data — Systems — Code
- Distributed Enforcement
- On-Prem, Cloud, SaaS
- Agent, Proxy, SDK
Secure, Production-Ready AI Pipelines
Most AI projects stall when sensitive data can’t be used safely in production workflows.
Protegrity removes the security, risk, and compliance barriers that slow progress or block AI deployments.
Query enterprise data using natural language without exposing sensitive fields — enabling analytics that remain accurate, explainable, and governed in production.
Orchestrate agents that retrieve data, reason across systems, and take action — while data stays protected and agent behavior remains auditable and production-ready.
Augment models with enterprise data without leaks or compliance violations — with secure, governed access, retrieval, and generation end to end.
Share data across teams and systems without duplication or exposure — with protection that travels with the data, enabling collaboration while maintaining control.
Drive Growth
Reduce Risk
ACHIEVE COMPLIANCE
THE LATEST
FROM PROTEGRITY
Privacy Under Pressure: Why Recoverability Is Now Part of Governance
Data Privacy Day is becoming less about awareness and more about readiness. In IT Brief’s latest coverage, security and infrastructure leaders warn that AI and cloud adoption are moving faster…
Agent Security Isn’t a Prompt Problem: Put Controls at the Boundary
MIT Technology Review’s sponsored feature, “Rules fail at the prompt, succeed at the boundary,” looks at why prompt injection has become one of the defining security risks of agentic AI….
From Q-Day to Crypto Agility: What Security Leaders Should Do Now
In a SecurityWeek Cyber Insights 2026 analysis published on Jan. 27, Kevin Townsend looks at what’s known—and what’s still uncertain—about quantum’s impact on cybersecurity. The near-term takeaway is straightforward: today’s…
See Your
Data Made
Safe for AI
Explore how Protegrity protects sensitive enterprise data across analytics, cloud, and AI.