The Challenge
Understanding the Problem
Manual visual inspection is slow, inconsistent, and expensive. A single missed defect can trigger customer returns, warranty claims, or worse — regulatory action. Our computer vision systems work 24/7 with sub-second detection speeds.
Our Approach
How We Solve It
Define Defect Taxonomy
Label production samples and define what constitutes a defect across your product range.
Train Custom ML Models
Build models trained on your specific defect signatures for maximum accuracy on your production line.
Edge Deployment
Deploy on edge hardware (Jetson Nano, Raspberry Pi CM4) or cloud inference depending on latency requirements.
Line Integration
Integrate with existing line stop / reject mechanisms via PLC I/O for seamless automated quality control.
Technical Stack
Technologies We Use
Use Cases
Real-World Applications
Real-time surface defect detection on sheet metal components
Textile quality inspection for weaving defects and color inconsistencies
Packaging integrity verification for food and pharmaceutical lines
Why Unartech
What Sets Us Apart
Models trained on your production data — not generic datasets that miss your specific defect patterns
Edge-first architecture for sub-100ms inference without cloud dependency
Seamless PLC integration for automated reject without operator intervention
Ready to Start Your Project?
Get a no-obligation technical consultation with our engineers. We'll assess your current setup and map out a delivery roadmap — with a fixed quote.