agent-governance-toolkit

To enforce policy compliance and sandboxing for autonomous AI agents, wrap your tool calls with a governance wrapper to block, allow, or require approval for actions. This isolates agent execution via privilege rings and sandboxed runtimes.

Yes, you can apply AI governance policies across LangChain, AutoGen, and CrewAI frameworks. The toolkit is framework agnostic and integrates directly into custom runtimes to protect tool calls, messaging, and delegation.

Zero-trust identity for AI agents uses DID or SPIFFE-based identities with mTLS to secure inter-agent communication. This ensures that every agent interaction is authenticated and encrypted across diverse deployment environments.

You maintain tamper-evident audit logs for AI agent tool calls by implementing automated decision recording within your governance wrapper. This creates immutable, traceable compliance records for every evaluated policy and executed action.

Yes, AI agent governance supports Python, TypeScript, Rust, Go, and .NET SDKs. This multi-language compatibility ensures you can enforce policies, identity attestation, and sandboxed execution across diverse technology stacks.

You define allow or block rules for AI agent tool calls using YAML, Cedar, or OPA policies. These declarative policies evaluate every tool invocation, blocking unsafe actions or requiring human approval before execution.