Industrial computer vision: automatic detection of microscopic defects

The initial problem

Microscopic defects, inspections that do not scale, fragmented technical information, and slow answers to specialized questions in high-precision environments.

The previous process

Quality inspection depended on manual review, and technical knowledge was scattered across manuals, PDFs, and presentations that only a few experts knew well.

The solution we implemented

Computer vision for anomaly classification with advanced visual analysis models and a detection pipeline, plus a RAG platform on Google Cloud to query technical documentation, PDFs, PPTX files, and manuals in natural language.

Integrated systems

• Computer vision
• Google Cloud
• RAG
• Technical documentation (PDF/PPTX)

The result

Better early detection, fewer unidentified errors, quality traceability, and fast access to knowledge without depending on a handful of experts.