Case Study: AI-Powered Process Automation for Manufacturing

The Challenge

A mid-sized European manufacturer was struggling with quality control bottlenecks on their production line. Manual inspection processes were slow, inconsistent, and costly — with defect detection rates hovering around 82%. The company was losing an estimated €400K annually due to undetected defects reaching customers and excessive false-positive rejections of good products.

Our Approach

SYNTHETIXMIND designed and implemented a computer vision-based quality inspection system integrated directly into the production line:

• Assessment & Data Collection — Analyzed existing QC processes and collected 50,000+ labeled images of products across defect categories
• Custom ML Model Development — Built and trained a convolutional neural network optimized for real-time defect detection
• Edge Deployment — Deployed the model on edge computing hardware for sub-100ms inference directly on the production floor
• Integration — Connected the system to existing MES and ERP platforms for automated reporting and traceability

The Results

“SYNTHETIXMIND didn’t just deliver a technology solution — they transformed how we think about quality. The system paid for itself in under half a year.”

— Head of Operations, European Manufacturer