Computer Vision in Production: What Works

Production vision systems fail when training data does not match the line — different lighting, angles, or product variants. Budget time for on-site capture and continuous sampling, not just model tuning.

Start with a single defect class or inspection point. Expand only after precision and recall are stable across shifts.

Edge deployment needs clear budgets

Edge deployment needs latency budgets and offline behavior defined upfront. Cloud-only inference breaks the moment connectivity does.

Operators need confidence scores and easy escalation to manual review. Black-box rejections erode trust fast.