Getting an agent to act is easy. Getting it to stop is the engineering.

Step four catches most of it: the output is checked against what the run was meant to achieve, and anything below the confidence threshold stops and escalates rather than continuing. What gets through is caught by the trace, because every action is attributable to a run you can open and read. The honest part is that some will get through, which is why irreversible actions sit behind an approval gate rather than behind a promise.

Only the ones you configure it to. The gate in step three is set per action type, not globally, so drafting a reply can be automatic while sending it is not, and updating a record can be automatic while deleting one is not. You decide where that line sits before anything goes live, and you can move it later.

Rule based automation follows a path you drew in advance and breaks when reality does not match it. An agent decides the path at run time, which handles variation but needs verification and logging that a fixed pipeline does not. If your process genuinely never varies, a rule based tool is cheaper and we will tell you so. Agents earn their cost where the exceptions are the expensive part.

Only what you grant, with credentials scoped to the agent rather than borrowed from a person. Permissions are set per integration, and the trace shows exactly which system each action hit. Your admins can revoke access without waiting for us.

It scales with how often the agent runs and how much work each run involves. We design to a cost envelope you set, put ceilings in place so a looping agent cannot produce a surprise invoice, and report cost per run alongside success rate so the trade is visible rather than buried.

You can, for the parts that are configuration: rules, thresholds, and gates are yours to change, and the runbooks cover them. Structural changes are where we come in, either as a change request or as part of an operate and expand retainer. We deliberately do not build things only we can edit.