DefectVision
AI-Powered Visual Defect Detection
AI-powered visual defect detection trained on 50,000+ infrastructure images. Identify corrosion, cracks, loose connections, and 40+ defect types with comprehensive detection capabilities.
The Inspection Quality Challenge
Manual photo review is tedious, inconsistent, and error-prone. Even experienced inspectors miss 15-25% of defects—not from negligence, but from fatigue and volume.
Manual Review Reality
- 50-500 photos per inspection
- 0.8-8.3 hours to review
- 15-25% of defects missed
- Reviewer fatigue after 100 photos
With DefectVision
- Process 1,000 images in 17 minutes
- High detection accuracy*
- Consistent results every time
- Consistent analysis quality
43 Defect Types Detected
Trained on 50,000+ labeled infrastructure images across multiple asset types.
Structural
- Corrosion (light/moderate/severe)
- Cracks (hairline/structural)
- Deformation
- Buckling
- Missing members
Connections
- Loose bolts
- Missing bolts
- Corroded fasteners
- Damaged welds
- Plate damage
Guy Wires
- Cable fraying
- Corrosion
- Slack conditions
- Anchor damage
- Insulator damage
Equipment
- Antenna damage
- Cable damage
- Unsecured cables
- Equipment corrosion
- Ice bridge damage
Grounding
- Disconnected grounding
- Grounding corrosion
- Inadequate grounding
Foundation
- Foundation cracks
- Erosion
- Settlement
- Grout damage
Enterprise-Ready Features
Real-Time Processing
Process images in under 1 second with GPU acceleration. No waiting, no queues.
Human-in-the-Loop
AI assists, humans verify. Accept, reject, or modify classifications with full control.
Flexible Deployment
Cloud SaaS for quick start, on-premise Docker for air-gapped environments, edge for field use.
Enterprise Integration
REST API, batch upload, webhook notifications, and streaming results for large workloads.
Technical Specifications
Model Architecture
- • YOLO v8x (largest variant)
- • 50,000+ training images
- • 1280×1280 input resolution
- • 43 defect classes
Performance
- • <1 second/image (GPU)
- • 1,000 images/17 minutes
- • Up to 95%+ accuracy (mAP@0.5)*
- • <10% false positive rate
Input Formats
- • JPEG, PNG, HEIC
- • RAW formats supported
- • Batch upload API
- • FieldCapture integration
Deployment
- • Cloud SaaS (GPU)
- • On-premise Docker
- • Edge-optimized model
- • Air-gapped option
Transparent AI. Honest Capabilities.
We believe in transparency about what our AI can and cannot do. DefectVision is a powerful tool that assists—but never replaces—human expertise.
What DefectVision Does
- •Identifies potential surface defects from images
- •Provides confidence scores for each detection
- •Prioritizes images for human review
- •Maintains complete audit trail of all decisions
Important Limitations
What DefectVision does not do
Does not replace engineering judgment
AI detections are suggestions that must be verified by qualified engineers. Final assessments require professional expertise.
Does not guarantee 100% detection
Detection accuracy varies by defect type, image quality, and environmental conditions. Some defects may not be detected.
Cannot assess internal or subsurface damage
Visual AI can only analyze visible surface conditions. Internal structural damage requires other inspection methods.
Performance depends on input quality
Detection accuracy is directly related to image quality, lighting conditions, and camera resolution.
These limitations are disclosed in accordance with our commitment to transparency. AI outputs should always be reviewed by qualified professionals.
Our Accuracy Commitment
DefectVision achieves 95%+ accuracy (mAP@0.5) on our validation dataset for common defect types including surface corrosion, visible cracks, and loose fasteners. Accuracy varies by defect type, image quality, and environmental conditions. All accuracy claims are validated through independent testing.
Important Limitations
What this product does not do
Does not replace engineering judgment
AI detections are suggestions that must be verified by qualified engineers. Final assessments require professional expertise.
Does not guarantee 100% detection
Detection accuracy varies by defect type, image quality, and environmental conditions. Some defects may not be detected.
Cannot assess internal or subsurface damage
Visual AI can only analyze visible surface conditions. Internal structural damage requires other inspection methods.
Performance depends on input quality
Detection accuracy is directly related to image quality, lighting conditions, and camera resolution.
These limitations are disclosed in accordance with our commitment to transparency. AI outputs should always be reviewed by qualified professionals.
See DefectVision in Action
Upload your own inspection photos and see real detection results. Schedule a demo to explore the full capabilities.
Schedule Consultation30-minute focused session • Your data, your use case • No sales pressure