governance

Open-source SDK for governing AI agent tool calls before side effects happen, with policy enforcement, approval flows, audit logs, and local execution.

Open-source agentic mesh for governing AI agents across enterprise systems, with identity, policy enforcement, audit trails, observability, and Kubernetes-native deployment.

Open-source governance harness for AI agents with policy enforcement, human approvals, isolated execution, budgets, and signed audit evidence. It includes a CLI, REST API, web dashboard, SDKs, and adapters for common agent frameworks.

A governed workflow execution spec for MCP hosts, with fail-closed semantics, version pinning, checkpoint enforcement, and a reference implementation plus conformance suite.

An open-source governance layer and policy-decision daemon for autonomous AI agents, designed to enforce guardrails, budget limits, and runtime policy checks.

Runtime governance and containment for AI agents. Faramesh sits between an agent and its tools to enforce policy checks, approval steps, credential isolation, and tamper-evident audit logs before risky actions execute.

A governed memory runtime for AI assistants with typed storage, policy checks, audit logging, tenant isolation, and hybrid retrieval. The repo includes a backend API, worker jobs, SDK examples, architecture docs, and eval harnesses.

A governance plugin for OpenClaw that registers instances with a Recursant registry and intercepts tool calls, LLM prompts, and chat messages for auth, PII redaction, rate limiting, and auditing.

CtxVault is an open-source receipt layer for governed AI context. It shows what evidence was selected, caveated, blocked, omitted, and how a context packet can be audited or rolled back.

A proof-of-concept governance harness for agentic coding loops, using machine-level policy enforcement, validation hooks, and a deterministic control point to keep agent outputs within approved rules.

A repository for a zero-trust execution boundary that sits between AI agents and real system actions. It evaluates policy, approval, scope, freshness, replay, and evidence before allowing operations to proceed.

A governance framework for multi-agent AI systems, with agent lifecycle controls, memory, runtime hooks, and quick-start scaffolding for governed projects.

A GitHub repository that proposes a practical methodology for evaluating how AI systems behave during real work, with quick-start, practitioner, and methodology guides included.

VAIBot is an AI governance product focused on agent security. This page explains its prompt-injection threat model and positions the product as a circuit breaker that gates tool calls and other egress actions before they execute.