Why manufacturing teams adopt this
Manual visual inspection is inconsistent, fatiguing, and cannot keep pace with production line speeds. Traditional machine vision requires expensive calibration for each new product type. Training new AI models typically requires thousands of labelled real-world defect images — which are difficult and costly to collect for rare defect types.
Computer vision models are trained using a combination of synthetic data (generated from CAD models or rendered scenes) and real-world imagery. A no-code labelling and training interface allows line engineers — not data scientists — to define new inspection tasks and train models within hours. Trained models are deployed at inspection stations to flag defects in real time, with human review reserved for borderline cases.
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