Computer Vision
Q-Vis
Q-Vis delivers quantum-enhanced vision for object detection, image processing, and image compression — achieving detection accuracy, processing speed, and payload sizes that classical computer vision systems struggle to match on edge hardware.
10x less data · 10x fasterUse Cases
- →UAV/AUV: Real-time object detection for aerial and sub-surface autonomous systems
- →Manufacturing: Edge-based fault and defect detection on the production line
- →Agritech: On-device image compression for crop and field monitoring over low-bandwidth rural networks
- →Security: Low-latency surveillance and perimeter monitoring at the edge
Patents
2 patents published covering the hybrid quantum-classical framework behind this product.
Benchmarks
| Feature | Classical AI (SOTA) | Quanverge Hybrid |
|---|---|---|
| Training Images | Hundreds of Thousands | Tens of Thousands |
| Hardware | GPU Required | CPU / Edge Device |
| Inference Latency | Baseline | 10x Faster |
| Image Payload | Full-resolution transfer | Compressed On-Device |
| Power Draw | High (GPU cluster) | Low (edge-deployable) |
| Deployment | Weeks | Days |
Estimate your Q-Vis ROI
Estimated latency with Quanverge
ms
Based on: 10x faster inference at edge
Images needed with Quanverge
images
Based on: 10x less data
Illustrative estimate based on Quanverge's published benchmarks — actual results vary by deployment.