Close the loop.

A customer picks up your retail coffee beans, turns the bag over, puts it back. SimSense sees it, understands it — and now its agents do something about it, while the customer is still in the room.

Watch the window shopping.

All day, people pick up the retail beans, look at the price, and put them back. No human catches the pattern between orders. The camera on the shelf does — every pick-up, every put-back.

• picked up today12
• bought1
• average look14 seconds

Twelve pick-ups. One sale.

SimSense clusters the almost-sales into a signal: same product, same hesitation, same walk-away. By late morning it isn't an anecdote anymore — it's a price-point problem with a timestamp.

• return-to-shelf rate92%
• hesitation clusterprice check
• flagged11:41 AM

It doesn't just report it.

New in SimSense: agents that finish the job. This one watched the beans all morning, formed a theory, and pinged you — with the fix already drafted.

A sign, up by lunchtime.

You said yes. The agent generated the sign, sent it over, and kept watching the shelf. Same beans, same foot traffic — different afternoon.

• since the sign3 bags sold
• pick-up → purchase1 in 4
• agent follow-uptomorrow 9 AM