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Provides an infrastructure to govern AI agents with runtime policy enforcement. It allows companies to ensure AI agents operate within defined boundaries and provides audit evidence for compliance. Enforcement occurs…

Blocks prompt attacks, scores agent trajectories, and traces execution steps for artificial intelligence agents.

Secures AI agents by mapping tool usage, minting capability tokens, and enforcing runtime policies.

Monitors AI agent actions, enforces permission boundaries, and automatically rolls back damage without code changes.

Secures LLM agents against prompt injection by scanning for vulnerabilities and blocking unsafe tool calls.

Enables control over AI model calls, tool invocations, and agent actions before execution. It provides real-time policy enforcement with cryptographic evidence.

Provides runtime infrastructure for autonomous AI agents, including identity, permissions, audit logging, and governance.

Enables control over autonomous AI model calls, tool invocations, and agent actions. Real-time policy enforcement with cryptographic evidence is provided.

Provides a compliance layer for AI agents with cryptographic boundaries, access control, and tamper-evident audit trails.

Secures AI agents with verifiable identity and enforces authorization decisions for every action across LLM and MCP traffic.

Secures AI agents with zero-trust identity, an LLM and MCP gateway, runtime defense, and forensic lineage for security teams.

Provides an anti-hallucination layer and deterministic gates to connect artificial intelligence models to reality.

Checks AI agent actions against defined rules to allow, pause for review, or block them.

Provides runtime security and sandboxing for AI agents to dynamically adjust permissions as tasks change.

Open-source runtime for governing production AI agents with rule enforcement, human oversight, and audit logs.