Looper turns what Watcher measures into the next change: a better model, a clearer instruction, a new rule or a better split of work between people and agents. Each one is simulated first and approved by a person.
Every change says what it is, the evidence behind it and who approved it.
Looper looks for the change most likely to save time or cut mistakes, then makes its case in Simulator before anyone is asked.
Move a step from a person to an agent, or back, as the evidence says.
Switch to a better or cheaper model when one wins on your work.
Rewrite the steps an agent follows where Watcher finds it going wrong.
Tighten or relax limits and approvals based on what really happens.
Connect the system or record an agent was missing.
When enough graded work builds up, train a model on your Context.
Every change is simulated first, and a person approves it.
Looper suggests. Your people decide.
Every change runs on past cases before anyone is asked to approve it.
The right person signs off, with the evidence in front of them.
If a change slips, Watcher flags it and you roll it back.
Each week builds on the last, and everything learned stays in your Context.
Thirty minutes with our team, on the workflow you would run first.