Industrial AI-Based Vision
Complete visual inspection systems – not just AI models.
The industrial problem
Manual visual inspection is slow, subjective, and hard to staff – and classic rule-based vision systems struggle with natural variation in surfaces, materials, and assembly situations. An AI model alone does not solve this: production needs a complete, reliable inspection system.
How it works
We develop AI vision systems end to end: camera selection, optics, lighting, image acquisition, dataset preparation, annotation strategy, AI model training, edge deployment, PLC and robot integration, user interface, production reporting, model monitoring, and continuous improvement.
A successful AI vision system is not only an AI model – it is a complete industrial solution that runs every cycle, integrates with your line, and can be maintained and improved over years.
Typical data sources
- Area scan and line scan cameras
- 3D cameras where geometry matters
- Controlled lighting matched to the defect types
- Images collected directly from the production line
Business value
- Consistent, objective quality decisions every cycle
- Reduced manual inspection effort
- Full inspection instead of sampling
- Traceable quality records with images
Deployment architecture
- 1Cameras and lighting acquire consistent images
- 2AI models run locally on edge hardware
- 3Decisions go to the PLC within the cycle time
- 4Images and results are stored for traceability
Integration
- PLC integration for line control and rejects
- Robot integration for pick, place, and inspection
- Results in SQL databases and production reports
- Edge deployment on NVIDIA Jetson or industrial PCs
Example use cases
- Visual quality inspection and defect detection
- Segmentation, object detection, and classification
- OCR, barcode, and label reading
- Completeness and assembly verification
- Position and orientation verification
- Surface inspection, counting, and dimension estimation
- Anomaly detection for unknown defect types
Interested in this solution?
Tell us about your machines and processes – we will propose a practical architecture and a pilot you can evaluate.
Discuss your project