
Averroes Ai Automated Visual Inspection
No-code AI-powered visual inspection software delivering high accuracy and minimal false positives for quality control.
About Averroes Ai Automated Visual Inspection
Averroes provides an AI-based visual inspection platform that achieves over 99% accuracy with nearly zero false positives. Designed as a no-code solution, it enables effortless setup and deployment for automated inspection across diverse industries. Users can train custom AI models without programming knowledge, ensuring compatibility with various data sources and hardware. Averroes enhances quality assurance processes, surpassing traditional manual checks by offering continuous learning and integration capabilities for more reliable inspection outcomes.
How to Use
Create, upload, label, and train custom AI models on the Averroes platform. Upload reference images without defects, then input inspection images to train the AI for anomaly detection. A small dataset of 20-40 images per defect type suffices for accurate visual assessments with minimal setup effort.
Features
- Intuitive no-code AI model training and deployment
- Flexible deployment options including cloud and on-premise
- Over 99% accurate defect detection with low false positives
- Seamless integration with existing inspection systems
- Continuous learning to improve detection accuracy over time
Use Cases
- Precise defect segmentation for detailed analysis
- Object detection across manufacturing sectors
- Defect classification in industrial production
- Anomaly detection in food and beverage manufacturing
- Quality assurance in semiconductor fabrication
Best For
Pros
- Reduces costs and saves time with automation
- Achieves high accuracy with minimal false alarms
- Versatile for multiple industries and data types
- No coding required simplifies AI implementation
- Easily integrates with existing inspection tools
Cons
- Performance relies on quality of training data
- May have industry-specific limitations
- Initial image data collection is necessary for training
