Capability 07 · Vision AI
The line moves faster
than anyone can watch.
A vision flow for teams inspecting, counting, or measuring by eye — on production lines, drawings, or technical PDFs — where most of the work goes unchecked.
The situation
Quality is sampled because watching everything doesn't scale.
Inspection happens by eye. On the line, quality is sampled at a few percent because checking every unit by hand is impossible.
On drawings and PDFs, someone counts items and measures by hand, one at a time. It’s slow and hard to repeat exactly.
The visual information is all there. It just depends on a person catching the same thing, every time.
The challenge
A clever model isn't the point. A usable inspection is.
A demo that detects something in good light is the easy part. The hard part is making it a workflow people trust.
That means deciding what counts as a correct result, when a human must look, and how uncertain cases are handled.
Without those rules, a vision model never leaves the demo.
The capability
The model supports the inspection. It doesn't make the call alone.
We build a vision workflow that detects, classifies, measures, or inspects the visual input — image, drawing, or PDF.
Results are structured and shown visually, tied back to the source. Confident cases move forward; uncertain ones go to review.
A person confirms what matters, and the approved result returns to the workflow.
How the flow works
Before / after
Inspection is sampled or done by hand. Drawings and images are checked by eye, one at a time, and consistency depends on the day.
The workflow checks the visual input, structures the result, and holds uncertain cases for review. Coverage goes up; the team reviews exceptions.
Controls
- A defined detection target
- Agreed criteria for a correct result
- A confidence threshold for review
- Human review for uncertain cases
- Every result traceable to its source
- Performance monitored over time
- Approved results logged
- Output returns to the agreed system
Where this applies
What changes
Questions about vision
What does computer vision need in order to work on a factory floor?
Consistent conditions and enough examples of what good and bad look like. Lighting, camera position and framing usually matter more than the model itself. Where those are stable, inspection and monitoring run reliably day after day.