Credo AI Agent Governor transforms enterprise intent - your mission, goals, policies, risk appetite, and regulatory obligations - into executable runtime controls that guide agent decisions, enforce policy with actions, and provide governance observability so you know the controls are doing their job.
Agents at your organization are already calling tools, accessing sensitive data, and taking actions in the real world. The gap between your policy and how it's implemented is where incidents happen.
Business intent - your mission, policies, risk appetite, regulatory obligations - describes what good looks like. It is not, by itself, something an agent can act on. Turning that intent into a concrete, machine-readable control is hard, and most organizations skip it, leaving agents to operate against intent no system actually checks
A control that only lives in a document, a spreadsheet, or a team is not enforcement. For it to be real, it has to run as code, inside the agent's own loop, checked at runtime, before every action. Most controls never make it that far, so the agent runs as if they don't exist. The result: data leakage, audit findings, and actions no human ever signed off on.
Agent Governor solves both. Initially Credo AI provides regulatory and risk informed out-of-the-box policies to configure your agent harness. In the near future we will also enable you to bring your goals, risk priorities, and compliance needs into the policy, then make it machine-readable and enforceable.
Agent Governor is the route from what your organization intends to what your agents actually do. Intent becomes policy, policy becomes governance-as-code, code becomes enforcement inside the agent harness at runtime. Telemetry flows back as proof that your agent is on course.
Codify your business context –organizational intent, policies, and risk posture– into policy. Start from out-of-the-box policies aligned to EU AI Act, NIST RMF, ISO 42001, and sector frameworks, based on your organizational posture, AI risk intelligence, and regulatory intelligence.
Every policy compiles to governance-as-code: versioned, machine-readable configuration that modifies how the agent runs. Governance teams define intent. Admins deploy it. No hand-written controls per agent, no governance stranded in a document.
Governance and control embedded in the agent’s harness . Policy is enforced inside the agentic loop, on invocations, before any action runs. Four key actions resolve every event.
Enforcement events flow back as live telemetry. See your policy in action, spot what's noisy, and tune it. This is the observability that lets you trust what your agents are doing and know that governance is working.
AI security tools look for what could go wrong before an agent acts. Observability tools show you what happened after. We call the space between decision governance: making sure what an agent actually does matches the context and intent it was given, in the moment it acts. Agent Governor is informed by regulatory intelligence, AI risk intelligence, and organizational intelligence.
Governance lives inside the agent, not bolted on beside it. Intent to policy to code to enforcement, informed by regulatory, AI risk, and organizational intelligence.
Controls run inside the agent harness: the software that actually runs an agent end to end, deciding what tools it can reach, what data it can see, and what happens before and after every action. Enforcement there is deterministic- the agent cannot reason around a rule that's wired into its harness, only work within it. Invocations and actions checked at runtime.
Intent becomes policy, policy becomes governance-as-code, code becomes control, telemetry becomes runtime action. Agent Governor is the route your governance travels to reach the agent, and the proof it keeps them on course.
Consistent governance across the agent frameworks you deploy. Not tied to a single cloud, model provider, or vendor.
Out-of-the-box policies aligned to EU AI Act, NIST RMF, and sector frameworks. Most tools assume you already wrote the policy.
Live telemetry from enforcement decisions. In future you will also be able to see exactly what your agents are doing, and turn that telemetry into runtime action, policy decisions and policy audits.
Agent Governor is built around the standard agent harness lifecycle: session start, before and after every tool call, session end. Any harness that exposes those events can be governed
The average large enterprise is expected to be running more than 150,000 agents by 2028 far more than its human workforce. We are working with a small group of organizations to shape what Enterprise Agent Governance at that scale looks like in practice. If you are deploying agents and need systematic control over what they can do, we want to talk.
The trusted leader in AI governance. Helping enterprises govern agentic AI systems at scale.
