Photo-Based Damage Assessment for Claims Processing

VigourSoft designs and deploys a photo-based damage assessment pipeline for auto and property claims, using models trained in Amazon SageMaker and, where useful, Amazon Rekognition Custom Labels. Claimants or adjusters upload photos through a mobile or web intake flow, and the pipeline estimates damage severity and repair cost range in minutes, flagging complex cases for human adjuster review while keeping model retraining and management centralized.

Scope of Work:

• Claim photo intake and use-case discovery (damage types, photo quality standards, claim volume)
• Custom vision model development and training in Amazon SageMaker (or Rekognition Custom Labels)
• Photo intake pipeline design (mobile or web upload to S3, Lambda processing)
• Adjuster review workflow for complex or low-confidence cases
• Model validation against historical claim photos and accuracy benchmarking

Deliverables:

• Trained and validated damage assessment model
• Deployed photo intake and assessment pipeline
• Adjuster review workflow for complex or low-confidence cases
• Model retraining and performance monitoring runbook

Target Audience: Insurance carriers and claims organizations handling high volumes of auto or property damage claims who want faster, more consistent damage estimates without adding headcount to the adjusting team.

Outcome Summary: Claims teams get a damage estimate within minutes of photo submission instead of waiting on a manual inspection. Complex cases are routed to a human adjuster, and the underlying model is trained and managed centrally through SageMaker.