Accident analysis & liability assessment
Government & Insurance · Transportation / LegalTech / Insurance
Case turnaround in the human-reviewed workflow versus prior manual handling.
- Client
- Government & Insurance
- Industry
- Transportation / LegalTech / Insurance
- Scope
- Mobile AI system for accident reporting and liability assessment.
Inside the project
Challenge
Manual accident investigations were time-consuming and lacked standardization. The aim was to automate accident reporting and liability evaluation.
Solution
A mobile-enabled AI system for accident reporting with real-time vehicle validation, damage assessment, and fault attribution — YOLOv8 validates vehicles, deep-learning models classify damage type and severity, and spatial analytics apply legal and insurance rules with real-time report generation.
Our approach
YOLOv8 validates the vehicles on-scene, deep-learning models classify damage type and severity, and spatial analytics apply approved legal and insurance rules to organize the evidence into a reviewable case timeline. Every output is human-reviewed decision support: the system presents contributing factors and a confidence score — never a final legal, enforcement or insurance judgment — and a qualified reviewer confirms or overrides at a prominent review gate, with evidence integrity, rule versions and reviewer actions preserved for audit and appeals. Standardized reports generate in real time, cutting claims from weeks to hours.