An enforcement layer that validates AI agent actions against governance policies, including path permissions and content scanning, at runtime. It enables secure, role-based execution of file operations and commands with zero token overhead by processing policies independently from the agent's context.
Enforces deterministic policies on AI agent tool calls, evaluating actions against compliance modules (SOC 2, HIPAA, GDPR, etc.) and returning ALLOW, BLOCK, or CONSTRAIN decisions with an audit trail.
Runtime policy enforcement for AI agents. Evaluate every agent action against your organization's policies before execution, with observe and enforce modes.
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.
Provides real-time policy enforcement for AI coding agents by intercepting and validating their actions against organizational standards like naming conventions, security policies, and compliance rules before execution. Prevents violations through immediate feedback and auto-correction suggestions.
Policy-based governance for AI agent tool calls. YAML policies, approval gates, risk assessment, and audit logging across LangChain, OpenAI, Anthropic, and MCP.
