We design embedded systems and boards that run AI models on the production line itself. The decision is made locally in milliseconds — no network latency, no per-call cost, and no images leaving the plant.
When quality control is visual and sampled, a defect surfaces after a whole batch has been produced. The cost shows up as rejects, rework and customer complaints.
We work alongside your QC staff, in the real conditions of the line.
We define the defect types with your team and collect samples to train the model.
We design the board and vision system for the line’s vibration, temperature, dust and lighting, and test it on site.
It runs alongside your existing inspection so results can be compared before it takes over.
We do not replace the line. We add a node that speaks its language.
Detecting defects, missing components and deviations on every piece.
Monitoring vibration and temperature to predict failure before downtime.
Automatic code reading, linking every piece to its batch.
The production cycle leaves no time for an image to travel to a remote server. It also means no data leaves the plant and there is no per-call cost.
Installation is planned around a scheduled stop. Trial operation runs in parallel with existing inspection, without affecting production.
We hand over a documented retraining process so your team can add new types without needing us each time.
The board is designed for the real conditions — vibration, temperature, dust — and tested on site before installation.
Yes, over the industrial protocols you already use, so the system can mark or reject a piece automatically.
Longer than a software project, because it involves hardware and on-line testing. We give a realistic timeline in the free review.
In a free 20-minute call we look at your line, your defect types, and whether embedded AI is genuinely the right answer.