An advanced computer vision system that automatically detects and segments vehicle damage from images using foundation models. Built for insurance and fleet operations, it reduces manual inspection time, improves accuracy, and enables scalable damage assessment workflows.

The system continuously improves through feedback loops, making it more accurate over time.

Key Capabilities

• High-precision damage detection using segmentation models
• Detection of both major and minor damages
• Annotated outputs with masks and confidence scores
• Batch processing for large-scale inspections
• Continuous learning pipeline for model improvement