AI vehicle damage inspection & claims analysis

The challenge

An insurance and fleet management provider handled upwards of 800 vehicle inspection reports every month. Manual adjustments required examiners to inspect dozens of smartphone pictures per incident, causing claim turnaround bottlenecks of 48 hours and human inconsistencies in assessing severity.

The technical solution

RG Systems engineered an AI and computer vision processing pipeline connected seamlessly to mobile web capture:

1. Guided Mobile Photo Capture: Smartphone camera interface with outline overlays to enforce consistent angles and lighting conditions.
2. Multimodal Damage Segmentation: Hybrid neural network combining convolutional detection and multimodal vision models trained to pinpoint panel dents, paint abrasions, fractured glass, and misaligned panels.
3. Instant Claim Assessment Sheet: Immediate classification by severity tier (Minor, Moderate, Severe) with recommended repair vs. replacement flags.

The microservice architecture was developed with FastAPI and deployed at the edge to return structured verdicts in under 15 seconds.

Operational results

• Inspection processing time cut from 48 hours to 15 seconds.
• 94.2% classification accuracy benchmarked against certified human adjusters.
• Automated fraud detection by comparing claim photos against baseline intake records.
• Over 350 engineering hours saved monthly on manual claims review.