How Tempo learns what normal looks like in a store

02Normal is local

The same shelf, price, or display can mean different things in different stores. A useful agent cannot treat every account as identical.

Tempo needs to learn what normal looks like by store, product, route, and season.

03Feedback is the training signal

When a manager confirms a flag, dismisses it, edits the next action, or approves a fix, that answer should become part of the operating standard.

• Confirmed flags make future detection sharper
• Dismissed flags reduce noisy repeats
• Manager edits teach the preferred action
• Fixed issues update the account history

04Every visit makes the next one smarter

Location memory turns field work into compounding context. The next rep arrives with better expectations because the last visit was captured, judged, and resolved.