AI College Assistant & Academic RAG Platform

Build a next-generation AI-powered college assistant that uses RAG architecture to intelligently answer questions from uploaded academic documents — syllabus, exam schedules, college rules, faculty information, and more. The system processes uploaded PDFs and documents using vector embeddings, stores them in a vector database, and uses an LLM to generate accurate, contextual answers grounded in real college data — eliminating hallucinations. **Key Innovation:** Students can simply ask questions like "When is the ML exam?" or "What is the attendance requirement?" and get instant, accurate answers from official documents. **Technical Excellence:** This project demonstrates cutting-edge GenAI skills — RAG pipelines, vector databases, LLM integration — skills that are in extremely high demand at AI companies.