Agentic Process Automation puts agents inside enterprise workflows at scale — thousands of them, making decisions, routing work, invoking tools. Evaluating whether each one is safe to operate requires matching performance criteria to the governance risk each agent actually carries.

That matching is the core problem. An agent can complete tasks quickly while violating policy. It can remain compliant while consuming too much compute to be viable. It can appear accurate while using tools incorrectly, escalating poorly, or behaving inconsistently across similar cases. A few summary metrics or anecdotal feedback are not enough. And even when the right things are measured, the meaning of a weakness depends on context. A reliability issue that is tolerable in a low-risk drafting workflow is disqualifying in a multi-step process where the agent has broad discretion. Without a way to classify the operating context and then evaluate the agent within that context, organizations drift toward either over-control or under-control.

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