
Business Problem
Insurers face mounting pressure to settle claims quickly, especially after natural disasters when thousands of cases flood in. Traditional workflows depend on manual review of policy documents, handwritten forms, PDFs, and compliance rules, forcing adjusters to spend hours searching and cross-verifying details. This results in weeks-long processing times, high operational costs, and dissatisfied customers.
Technology Solution
We built an AI-powered claims assistant using a Retrieval-Augmented Generation (RAG) pipeline that streamlines end-to-end processing:
• OCR Extraction: Azure AI Document Intelligence reads scanned and handwritten forms to produce structured text.
• Semantic Retrieval: Data is embedded and indexed in a FAISS vector database for fast, clause-level lookups across policy terms and guidelines.
• AI Evaluation: Cohere Command R+ retrieves relevant clauses, evaluates claims, determines validity and payout, and generates an explainable reasoning trail.
• Domain Templates: Predefined prompts for travel, health, auto, and property claims ensure consistent assessments.
• Application Layer: FastAPI (Python) and Vue.js power APIs and a web app for transparent claim visualization.
• Deployment Flexibility: Insurers can choose Cohere APIs or self-host Llama 3 (8B) on AWS SageMaker to meet data governance needs.
Technology Stack
• OCR & Extraction: Azure AI Document Intelligence
• Indexing & Retrieval: Semantic embeddings + FAISS vector store
• LLM Engine: Cohere Command R+
• Alternative LLM: Llama 3 (8B) on AWS SageMaker
• Application Layer: FastAPI (Python), Vue.js UI
Benefits & Impacts
TRUSTIMONIALS
Success Delivered, Trust Earned


