We are the first to marry visual data with process engineering
AI enabled real-time anomaly detection highlights unusual defect rates. As the system is self-learning, no process engineer need to manually tune thresholds.
Frequent-set analysis finds out which defects occur together inferring relationship among different defect types.
Data gathered from our analytics engine can be used to train our proprietary deep learning algorithm to perform prediction, reducing the troubles of unscheduled downtime and maintenance.
Heat-maps align defects of hundreds of thousands defects visually, so your process engineers can identify root causes in one glance.
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