Define organizational rules centrally and enforce them across your entire agent ecosystem.
A compliance requirement shouldn't need a separate implementation for every department and technology. When the same rule is rewritten by every team, it stops being one rule and becomes several versions of it, and the audit has to check them all.
Rules that stop an agent from exposing credentials, secrets or another tenant's data.
Which agents can talk to which systems, in which environment and under which identity.
Which models are allowed per use case, with cost and context limits.
Which tools each agent can call, and which require human confirmation before they run.
How personal and regulated data is masked, retained and logged.
Industry requirements as executable rules, authored from the compliance spreadsheet, with one legal citation per rule.
When a run pauses to wait for a person, and how many people need to approve.
Internal policies that apply to the whole fleet, no matter who built the agent.
Enforce policies across agents without rebuilding each implementation one by one. When an agent tries to call a tool, fetch data or use a model, the call passes through the organization's rule before it goes out: if the rule blocks it, it doesn't go out; if it requires approval, the run pauses and waits for a person; if it allows it, the call proceeds, and the record stays.
Policy enforced at the boundary instead of excused afterwards: spending caps, four-eyes approval on sensitive actions and a kill switch per tenant.
Policy decides whether a call can go out. The business rule decides what the agent does with the case: how much to offer, who approves, which bracket applies. It leaves the prompt and moves into a rules engine, in four steps.
Decision tables authored by whoever owns the rule.
Canonical and versioned, with aggregation and quantifiers.
The rules engine is an adapter, replaceable by contract, not a lock-in.
The agent calls the rule from the language, and a decision id lands in the trail.