Protect Your Data from AI Agents Running in the Wild
Policy-Based Access Control for Sensitive Data That Moves Markets
Leakage of Material Non-Public Information (MNPI) — such as financial forecasts, M&A plans, or strategic reports — can trigger regulatory penalties and erode stakeholder trust.
In the age of autonomous agents, protecting information flow is the new perimeter. As AI agents interact with enterprise applications and data layers, they can retrieve and expose sensitive information within seconds — often without built-in safeguards.
PlainID closes these gaps. Built on proven PBAC architecture trusted by Fortune 2000 enterprises, the PlainID Platform applies policy-driven guardrails across the AI flow to deliver consistent, auditable information-flow control and data-security governance.
The Solution
Policy Management for Agentic AI
Protect Data Across the AI Flow (Demo Video)
Why It Matters: Business Benefits
- End-to-End Control: Unified policy lifecycle — Discover, Manage, Authorize — for every AI workflow.
- Governance You Can Read: The only enterprise solution with audit logs in plain language — built for both developers and auditors.
- Full Traceability: Controls both human and agent access with context-aware, auditable information-flow enforcement.
- Prevent Leakage at the Source: Dynamic policies stop unauthorized retrieval before response masking is even needed.
- Flexible Integration Model: Works across all major and emerging AI development and agent frameworks, with its enforcement module fully compatible with the enterprise's technology stack.
How It Works
A Simple, Guided Policy Experience
AI that does the heavy lifting:
- Natural-Language Policy Creation: Define and refine access rules in plain language.
- AI Recommendations & Data Mapping: Automate connections across datasets and identify related entities.
- Intuitive Canvas Interface: Visualize, auto-fill, and adjust policies effortlessly.
- Dynamic Guardrails: Apply real-time, context-aware controls at every AI layer — prompt, retrieval, tool invocation, and response — based on user role, data sensitivity, and governance policy.
- Audit Clarity: Every access event and policy change recorded, versioned, and exportable for audit or regulatory evidence.
Control AI Agents Before They Expose Sensitive Data
Apply dynamic access controls across your AI systems to keep MNPI protected and compliance intact — from the very first prompt. Let us show you how to protect MNPI across your AI systems.
