AI Data Security Platform for Secure Enterprise AI
Protect sensitive enterprise data before it enters AI workflows and govern how AI systems use it. Protegrity helps teams build secure AI pipelines without slowing innovation or compromising compliance.
Accelerate AI Innovation with Secure, Data-Centric Protection
AI initiatives move faster when teams can safely use the data they need. Protegrity applies data-level protection across AI models, analytics pipelines, cloud platforms, SaaS environments, and secure data sharing workflows.
With centralized policy, distributed enforcement, and advanced protection methods, your organization can reduce data exposure risk while keeping AI and analytics projects moving.
A Data-Centric Security Platform Built for AI Workflows
Protegrity helps enterprises protect sensitive data at the source, enforce governance across systems, and safely power production AI workflows across cloud, SaaS, and on-prem environments.
Data-Centric Security Architecture
Traditional security was built to control infrastructure and identities. AI requires security that governs the data itself.
Embedded and Semantic Controls
AI requires controls that protect data before it enters AI workflows and govern interactions as AI systems use it.
Secure Intelligent Workflows
Most AI projects stall when sensitive data cannot be used safely in production workflows due to compliance barriers.
Data-Centric Security Architecture
Define Policy Once. Enforce It Everywhere.
Protegrity uses a data-centric security architecture that separates policy, enforcement, and cryptography. This allows organizations to protect sensitive data wherever it moves — across users, applications, models, systems, and code.
With centralized governance and distributed enforcement, teams can secure computation on protected data while applying real-time controls across on-prem, cloud, and SaaS environments.
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
Embedded and Semantic Controls
AI Security in the Data Flow
AI requires controls that protect data before it enters AI workflows and govern interactions as AI systems use it.
Protegrity combines embedded controls upstream with semantic controls at runtime. Sensitive data can be discovered, governed, protected, and privacy-enhanced before it enters AI pipelines — then monitored and controlled as AI systems interact with it.
This approach helps teams use sensitive data with precision while maintaining trust, privacy, and governance.
Upstream Embedded Controls
Downstream Semantic Controls
Example Treatment Copy
SSN:
392-61-4981
Encrypted:
123-45-6789
Masked:
***-***-8702
Anonymized:
Person_1
Synthetic:
537-82-9135
Secure Intelligent Workflows
Secure, Production-Ready AI Pipelines
Most AI projects stall when sensitive data cannot be used safely in production workflows.
Protegrity removes the security, risk, and compliance barriers that slow progress or block AI deployments. Teams can build intelligent workflows that use enterprise data while keeping sensitive information protected, governed, and observable.
From natural-language analytics to agentic workflows, knowledge graphs, and secure data sharing, Protegrity helps AI teams move from proof of concept to production with confidence.
Secure Text to Analytics
Query enterprise data with natural language while protecting sensitive fields—delivering accurate, explainable, and well-governed analytics in production.
Secure Agentic Workflows
Allow AI agents to retrieve, reason over, and act on enterprise data while maintaining data protection and governance controls.
Secure Knowledge Graph
Protect sensitive entities, relationships, and attributes used in AI-powered reasoning and discovery workflows.
Secure Data Sharing
Share protected data across teams, partners, vendors, and systems without unnecessary duplication or exposure.
Accelerating Value at ScaleSecure, Production-Ready AI Pipelines
Enterprise-scale impact that unlocks new possibilities with data. Protegrity enables faster AI adoption, better outcomes, lower costs, and reduced exposure with measurable results.
95%
DRIVE GROWTH
Faster AI time-to-value by using sensitive data immediately without manual approvals, removing security delays, and accelerating production deployment.
70%
increase in data sharing
Data sharing has improved, enabling better collaboration across teams and partners while maintaining control and ensuring fast, secure access without duplicating data.
15x
return on investment
Stronger ROI is driven by reduced audit work, simplified compliance by excluding AI scope, and lower overhead when adopting new systems and tools.
Why Choose Protegrity
AI security requires more than protecting access to systems. It requires protecting the sensitive data moving through those systems.
Built for multi-platform environments
Works across all clouds, data platforms, and AI stacks—no need for data duplication, re-architecture, or vendor lock-in.
Security and governance that move with the data
Policies and controls are embedded in the data itself, not tied to any single system, so protection stays intact wherever the data is used.
Centralized policy with federated enforcement
Define governance once and apply it consistently across distributed systems—maintaining control without slowing teams or creating fragmentation.
See Protegrity in Action
Get a personalized, live walkthrough of the Protegrity platform. See how data-centric protection enables analytics and AI across cloud, hybrid, and on-prem environments—while supporting regulatory compliance.
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