AI-powered defect detection that learns your production line, not just defect libraries. Catches solder bridges, cold joints, missing components, and trace defects with <100ms inference—no 6-month training cycles required. Deploys in days and adapts on the job, getting smarter with every shift. 180x faster than manual inspection while eliminating operator fatigue inconsistencies.

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Vision models that understand design intent, not just pixel patterns. Validates component polarity, IC orientation, and BOM correctness by reasoning against your design files—catching functional defects that pass traditional AOI. Prevents field failures from reversed capacitors and rotated ICs that look visually perfect. Leverages large-scale pre-training to understand manufacturing fundamentals—deploys with structural intelligence, adapts to your specific production reality.

LLM-powered root cause analysis that synthesizes visual defects, process parameters, and operator logs into actionable insights. Ask "why are solder defects increasing on Line 2" in natural language—get correlations between reflow temperature drift and quality spikes. Predictive intelligence that alerts before defects occur, not after. Transforms quality data into manufacturing knowledge.

AI-driven traceability that connects dots across your supply chain—from component batches to assembly stations to quality outcomes. Automatically correlates supplier lot numbers with defect patterns, isolating issues to specific batches in minutes instead of weeks. Learns which suppliers and processes correlate with quality, building institutional knowledge that compounds over time.