Governed AI agents,
explained.
What it takes to let AI agents act on real systems — and keep people in control.
Each guide starts with a short answer, then explains the idea, the mistakes to avoid, and exactly what A2A Matrix does about it. No jargon you do not need, and no claims the product does not back.What is a governed AI agent runtime?
A governed AI agent runtime lets AI agents act on real systems only within permissions you set, with human approval for risky steps and a tamper-evident record.
Read the guideHuman approval for AI agents
How human-in-the-loop approval works for AI agents: which actions should wait for a person, quorum, separation of duties, delegation and expiry.
Read the guideAI agent audit trails
What an audit trail for AI agents must record, why it must be written with the change itself, and how hash chains and signed anchors make tampering detectable.
Read the guideGoverning MCP tools in the enterprise
MCP connects AI agents to tools. What can go wrong — over-broad access, tool poisoning, changed definitions, leaked keys — and how to govern it.
Read the guideThe A2A protocol, governed
What the Agent2Agent (A2A) protocol is, what it leaves to you — permission, credentials, trust — and how a governed broker makes calling other agents safe.
Read the guideThe EU AI Act and AI agents
What the EU AI Act asks of high-risk AI — human oversight, automatic logging, deployer duties — and what that looks like for AI agents. Not legal advice.
Read the guideThe same controls,
in your line of work.
What an agent would do, what it would never do alone, and who decides — for regulated industries.