Tabibu Health AI
Medical-grade health intelligence for consumers and teams: answers are grounded with citations from trusted clinical sources (Mayo Clinic, CDC, NIH, WHO, Cleveland Clinic, and peer-reviewed literature). I architected triple-source retrieval across medical knowledge bases, live web sources, and product databases so responses stay evidence-based and actionable. I implemented dual AI guardrails (input safety and output validation), emergency detection with localized guidance, multi-turn memory for coherent follow-ups, and a real-time product finder for medicines and supplements. Stack: Python, LangChain, LangGraph, RAG, Qdrant, Vite, React, Tailwind CSS, medical NLP patterns suited to regulated-style UX





