RAG driven Hospital Tier updation : Engineered a Retrieval-Augmented Generation (RAG) pipeline for a Healthcare Cost Estimation Engine to dynamically classify over 2,400 Indian medical facilities into strict pricing tiers.
Technology Stack & Workflow: Built with Python, Pandas, and the Serper.dev API to seamlessly fetch real-time web context and route it through a Large Language Model (LLM) for analysis.
Precision Tiering: Accurately categorizes hospitals across the full spectrum of care, from localized day-care clinics to massive tertiary corporate centers.
Advanced Feature Extraction: Automatically extracts critical boolean flags—such as identifying charitable organizations and pediatric-only centers to further refine cost modeling.
Business Impact: Successfully eliminated static NLP logic leaks, ensuring that the variable base cost multipliers applied to complex medical procedures remain highly accurate and strictly market-aligned.
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