Manufacturing & Industrial
Inspection that happens on the line, not after it
Plant floors have constraints a cloud service cannot meet: the part leaves the cell in milliseconds, the network is an OT network, and the imagery often cannot go anywhere at all.
Use cases
Where AI pays off here
Surface and dimensional inspection
Every part checked at line rate, driving the reject mechanism already installed.
Assembly verification
Confirming presence, orientation and sequence before the next station.
Zone and PPE monitoring
Exclusion zones and safety compliance on cameras already in the plant.
Binding constraints
- OT / IT separation
- Line-rate latency
- Controlled technology restrictions
- Uptime and fail-safe behaviour
Engagements
How we typically start
- 01Physical AI
Edge AI & Computer Vision
Detection, inspection, tracking and safety on-device. Milliseconds, and no network dependency.
- 02Physical AI
Vision Systems Integration
Cameras, optics, lighting, enclosures, and the PLC, SCADA and MES interfaces that make results act.
- 03Physical AI
Edge AI & Computer Vision
Detection, inspection, tracking and safety on-device. Milliseconds, and no network dependency.
Related proof: Surface defect inspection, decided at the camera in 12 ms
Start with a call, then a costed plan
Thirty minutes on the problem, the site and the constraints. If it looks like a fit, the next step is a four-week AI Pilot at a fixed price, with acceptance criteria signed before any code is written.