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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…

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

Monitors, authorizes, and prices tool and model calls made by coding agents.

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

Enforces policies, approvals, spend controls, and auditability across enterprise artificial intelligence applications and agents.

Blocks unsafe AI agent actions before execution using versioned policy enforcement and verifiable chain-of-custody proofs.

Provides runtime authority and shared application budgets for autonomous agents.

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

Provides an external pre-execution admission boundary to control automated and artificial intelligence actions.

Verifies, governs, and audits AI agent actions before production data changes.

Governs autonomous agent actions with policy enforcement, approval controls, and tamper-evident receipts.

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

Provides a runtime boundary for AI agents to enforce access limits, inspect actions, and export signed evidence.

Provides a financial control plane with identity, spending policies, deterministic authorization, and an auditable ledger for AI agents.

Enforces granular per-agent permissions and logs requests for AI agent MCP integrations.

Provides agent trust infrastructure including threat modelling, adaptive adversarial testing, and model-assisted review.