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Vision and on-site AI

Eyes on the line, day and night.

Check finished goods and site safety on the cameras you already have.

An inspector reviewing a camera-equipped production line.

Cameras on the line already record. Nobody watches them. A computer at the site raises what you ask for: a defect, a missing helmet, entry into a restricted bay. Footage and event records stay on your premises.

Illustrative example

What this could look like in practice

A garment factory wants a reason code on every reject, not a tally at shift end. An overhead camera at each finishing station marks a piece pass or fail in about a second and records where the defect sat. The supervisor gets a per-station, per-style reject report, so a run of the same defect stops the line instead of surfacing at final audit. None of the footage leaves the factory network.

How the system helps

The work it takes off your team

  • Runs on your existing cameras, with footage kept on site.
  • Watches for the classes you define, using your reason codes.
  • Checks goods at line speed and records why one failed.
  • Keeps working when the internet is down.

Considerations

Things to settle before building

  • Camera angle and lighting set the limit. Survey the site first.
  • Early false alarms need supervisor review time. Budget for it.
  • Clip retention and worker footage need HR and legal sign-off.

Outcome measures

Useful things to measure

Suggested yardsticks for judging whether a system like this is earning its place — not results we promise.

  • Rejects caught on line versus audit
  • Escapes reaching final QC
  • Findings confirmed versus dismissed
  • Event to alert time

Where it applies

Sectors where this fits

Factories, assembly and packing lines · Warehouses and yards · Construction and project sites · Utilities and infrastructure inspection · Defence and perimeter monitoring that must run disconnected