Is Your Inspection Problem a Good Fit for Computer Vision?
Before a camera goes near your line, describe the defect, the part, the cycle time and how you inspect today. An engineer reviews it — not an automated form — and comes back with a feasibility class, the sample images needed to confirm it, and the imaging risks specific to your environment.
Check my inspection use caseSee all Proof of Concept programsWhat this checks
For a quality or engineering team that has heard Computer Vision can catch defects human inspectors miss, but does not yet know whether their specific defect, part geometry and line speed make it a realistic candidate — or what it would actually take to find out.
What we do
- Review your use case description, defect type, cycle time and current inspection method.
- Assess the imaging environment — lighting, vibration, part orientation, line speed — against what a camera-based system needs to work reliably.
- Classify the opportunity honestly: promising, needs a controlled image study first, or not enough information yet.
- Specify exactly what sample images or a short site visit would confirm the classification, if the form alone cannot.
What we need from you
- A description of the defect or condition you want detected, and the part or product it appears on.
- Current cycle time and inspection method — manual, existing sensor, sampling rate.
- Whether example images of the defect exist already, and roughly how many.
- A description of the imaging environment — lighting, line speed, part orientation, available mounting space.
What you get back
- A feasibility class: promising, needs a controlled image study, or not enough information.
- The number and type of sample images needed to move from a class to a confirmed answer.
- Imaging risks specific to your line — the things that make CV projects fail in practice (inconsistent lighting, reflective surfaces, part movement).
- A recommended next step: proceed to the Computer Vision PoC, run a small image study first, or a different program entirely if CV is not the fit.
What this does not claim
This check never declares feasibility automatically from a form. A qualified engineer reviews every submission, and "not enough information" is a legitimate, common outcome — it means a short image study is the honest next step, not a rejection.
The Proof of Concept this leads to
Frequently asked questions
Do I need to send you real production images?
Only if you already have some — sending a handful of representative images (with confidential branding or product identifiers removed) speeds up the review. If you have none, describe the defect and environment instead; that alone is often enough for a first classification.
What does "needs a controlled image study" actually mean?
It means the description alone cannot confirm feasibility — usually because lighting, part variation or defect subtlety needs to be seen, not described. The recommended next step is a short, scoped image-capture exercise on your line before committing to a full PoC.
Is this the same as the Computer Vision PoC?
No — this is a free qualification step before that commitment. The PoC itself installs a camera, builds and validates a model against your line, and measures detection accuracy on real production parts.
Request this Proof of Concept
Tell us the scope you have in mind and we will come back with a written PoC plan: what gets connected, what you provide, how success is measured and what the decision at the end looks like.