AI Governor by Credo AI | Control and trust your agents | Enterprise Agent Governance
Agent Governor
Research Preview
Control and trust your agents.
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.
Org intent
- 🎯 Org goals
- 🛡️ Risk priorities
- 📋 Compliance needs
The policy to enforcement gap
You wrote the policy. The agent never read it.
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.
Intent has to become control.
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.
Control has to execute at runtime
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.
How Agent Governor works
From organizational intent to runtime control.
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.
Stage 01 · Policy
Define and create policy
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.
Stage 02 · Configuration
Compile policy to code
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.
Stage 03 · Enforcement
Enforce at runtime
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.
- Block · stop the action
- Allow · let it proceed
- Escalate · route to a human
- Advise · inject guidance
Stage 04 · Observability
Observe and trust
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.
Why Agent Governor
Security flags it. Observability shows it. Governance decides it.
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.
Embedded governance
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.
Runtime enforcement
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.
Agent control across your stack
Consistent governance across the agent frameworks you deploy. Not tied to a single cloud, model provider, or vendor.
Policy from day one
Out-of-the-box policies aligned to EU AI Act, NIST RMF, and sector frameworks. Most tools assume you already wrote the policy.
Learns from what it observes
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.
Supported agents
Starting with Claude Code. More agents harnesses on the way.
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.
- Claude Code (Full hook coverage) - LIVE NOW
- Codex (In development) - Coming Soon
- Cursor (In development) - Coming Soon
- Microsoft Copilot (In development) - Coming Soon
Join the preview
Built for the enterprises deploying agents today.
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.
Early access for design partners shaping the product with us. We respond to requests within a week.
Research preview · not generally available · no production SLA. Credo AI Agent Governor is a Beta Service.
The trusted leader in AI governance. Helping enterprises govern agentic AI systems at scale.