Guardian Agents run inside your stack through the HAI Guardian SDK. They watch what your AI says and control what it does in real time, without changing how your teams build.
You wrote the policy. The agent never read it.
Guardian closes that gap. Your controls stop being words in a document and become live rules that sit inside the agent's harness. They get checked on every action and enforced the moment risk crosses the line.
You wrote the policy, but the agent never read it. Guardian Agents turn your controls into live rules that live inside the agent's harness. Every action is checked, enforced and logged in one trail you can audit.
Set warn and block thresholds for every Guardian control. Decide what your AI is allowed to say with Sentinel and what it's allowed to do with Operative. Start from a ready-made library that already maps to the frameworks you report against.
Guardian runs through a single SDK. There are no agents to install and nothing changes in how your teams build. The same integration powers both monitoring and enforcement, right inside the harness your agents already run in.
Every prompt, response and tool call gets a score from 0 to 1 inside the harness, before anything runs. Below the line Guardian warns and logs it. Above the line it blocks the action on the spot, and the agent has no way to reason around it.
Every warning and block lands in one incident log and one tamper-evident audit trail. You get a continuous record of everything your agents say and do. Query it, set alerts on it, and show regulators exactly what governance did.
Both run through the same SDK, share one threshold, and write to the same incident log. The only difference is whether they watch or act.
Sentinel keeps an eye on model and agent output in production. It catches unsafe, leaking or off-policy behaviour without getting in the way of the workflow.
Sentinels give you visibility. They tell you what is happening without stepping in.
When risk crosses the threshold, Operative steps in. It governs which tools an agent can call, what it can reach, and how much it can spend, all in real time.
Operatives turn governance into action.
Runtime monitoring enforces what an agent is actually allowed to do. It happens before the call runs, not after the fact in an audit.
Decide which tools an agent can invoke, then stop the call before it runs.
rm -rf /Gate exactly what an agent can reach across your environment.
Keep autonomous spend attributed, capped and auto-contained.
Every agent runs under a known identity, so each action is attributable and every control resolves against who is acting.
Encode your own rules on the same threshold model. It stays your policy, enforced with the same warn and block mechanics.
Join the organizations that turned governance from a blocker into an enabler. Full visibility, continuous risk testing, and compliance proof — on autopilot.
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