Apr 2025 – Present · 1 yr 2 mos · Remote

• Designed and developed a Healthcare RAG Assistant to query multi-format medical and
• regulatory documents (PDF, CSV, Excel, HTML, TXT).
• Implemented FAISS + OpenAI embeddings for scalable retrieval and built a custom prompt
• framework to ensure compliance and factual accuracy.
• Integrated an AI-powered PDF Image Interpreter (PyMuPDF, PIL, Gemini API) to extract and
• summarize images, automating image-to-text explanations for compliance and medical
• reviews.
• Authored a detailed RFC outlining ingestion workflows, chunking strategies, metadata
• schema, semantic indexing, and retrieval pipelines, and benchmarked results showing that
• the RAG system reduced insight retrieval time from 45–90 min/report to under 10 seconds
• (~99% faster), improved accuracy from ~65–70% to over 90% (+25% gain), and cut analyst
• weekly effort from 10–15 hours to under 2 hours (-80% effort).
• Proposed a low-temperature LLM response strategy to minimize hallucinations and enhance
• reliability in regulatory and clinical contexts.