UCLA Women's Basketball RAG Analytics Chatbot
An intelligent Retrieval-Augmented Generation (RAG) chatbot for UCLA Women's Basketball statistics and analytics, powered by Anthropic Claude 3.5 Sonnet, Flask, and ChromaDB.
UCLA Women's Basketball coaches and analysts needed an intuitive, natural-language interface to query complex player statistics, game-by-game performance trends, and contextual tactical data without running manual SQL/Python queries.
The team built a RAG pipeline leveraging Claude 3.5 Sonnet, a Flask API backend, and vector embeddings in ChromaDB to retrieve play-by-play and player performance data, generating real-time conversational responses with comprehensive error handling.
Delivered a fast, conversational scouting interface capable of answering natural language analytics questions across player stats, team trends, and opponent breakdowns.