Every store in America already has cameras. Billions of hours of footage go to waste.
However much footage a space records, it still relies on a person to notice every incident, track every item, and catch every problem before it costs money. Vedere connects to the cameras a space already owns, understands what is happening, and surfaces the loss before anyone notices it.
What we sell
- 01A trusted problem record, not a bounding box.
- 02It carries a type, a ranked root cause, an urgency, a dollar impact, the retained evidence, and a recommendation a manager can act on or dismiss.
- 03Detections are an intermediate artifact. You never buy one.
How we judge ourselves
- 01Problem precision: when Vedere says table four waited eleven minutes, it did.
- 02False support per camera-hour: how often the system interrupts someone for nothing.
- 03Detector leaderboard scores are not the metric. Perception work is justified by moving the two numbers above.
When we say nothing
- 01The system abstains rather than fabricates.
- 02Below the visibility floor a stream produces a data-quality status, never an operations alert.
- 03That rule holds on this website too: the footage on the demo page is real, and what the model cannot see is stated instead of implied.
One engine, rules forked per space.
Warehouse and logistics leads the front door, because the problems are largest per instance — dock and trailer dwell, blocked aisles, labour set against real demand. Restaurants are where the whole chain is built end to end, from occupancy through sessions to an impact figure. Retail is next after the first paying pilot. What changes between them is the rules and the detector model, both version-pinned code; the engine, the evidence trail and the deletion path are the same everywhere.
Or write to michael@vedere.tech.