Match Medical Symptoms to Products with OpenAI, Qdrant & Google Sheets RAG

This advanced RAG-based AI medical agent workflow automates intelligent product recommendations for healthcare ecommerce, focusing on hair and scalp issues. Users input symptoms via chat, triggering a vector similarity search in Qdrant against product embeddings generated from Google Sheets data using OpenAI. The AI agent then responds with the top 3 relevant products, including names, descriptions, and links.

Key benefits include seamless integration of structured product data with semantic search, reducing manual recommendation efforts and boosting conversion rates. It's ideal for ecommerce businesses, AI developers building symptom-matching assistants, or anyone leveraging RAG for domain-specific queries without custom coding.

Setup involves preparing a Google Sheet with product details (name, symptoms, description, link), connecting credentials for Google Sheets, OpenAI, and Qdrant, populating the vector DB via initial execution, and activating the chat trigger for real-time interactions. This time-saving automation handles data ingestion, embedding, storage, retrieval, and generation in one robust pipeline.