Runtime policy enforcement for AI agents. Evaluate every agent action against your organization's policies before execution, with observe and enforce modes.
Provides policy-based access control, incident tracking, and compliance monitoring to govern AI agent behavior. It enables organizations to enforce security rules and maintain audit trails by validating agent actions against trust levels and pattern-based policies.
Enables AI agents to self-govern by scanning code for hardcoded secrets, structural violations, and AI drift in real-time, providing fix packets for automatic remediation.
Behavioral governance layer for AI assistants that monitors for hallucination, inconsistency, and unsafe reasoning patterns while managing stateful AI sessions.
Pre-execution governance for AI agents. 45 MCP tools for hold queues, audit trails, risk scoring, and policy enforcement. Validates agent actions before they execute.