From Pixel to Payouts: A Multi-Agent System for Real-Time Insurance Claims Processing
The traditional process for auto damage evaluation is relatively slow, subjective, and prone to fraud. With this presentation, the goal is to show a Multi-Agent System designed for the automation and standardization in real-time of the car damage evaluation, disrupting the initial claims workflow. The system is built around an Orchestrator Agent with the role to coordinate specialized AI agents: a Vision Agent (powered by OpenAI GPT-5.2) for damage analysis and severity classification, two Cost Estimation Agents (powered by Perplexity's sonar-pro) to provide comparative quotes (OEM vs. Aftermarket), and a Shop Finder Agent for local repair options. The system produces a report that includes a description of the damage, severity, comparative repair costs in local currency, and recommended repair shops, all embedded into a Gradio/Streamlit interface. The task of this approach is to reduce the processing time, improve transparency for customers, and provide insurers with objective data to enable faster claims resolution.
