USP – Educational RAG Application
Retrieval-Augmented Generation application for Universidade de São Paulo enabling intelligent question-answering for educational content.
Context
USP needed intelligent system allowing students and faculty to interact conversationally with vast academic materials, lecture notes, and research papers.
Challenge
Building accurate question-answering system with document processing pipelines, semantic search, and optimized retrieval for educational queries.
Solution
Implemented LangChain with large language models and vector databases (Pinecone/Weaviate). Built document processing with AWS Textract and React-based natural language search interface.
Technology Stack
ai
processing
search
frontend
Impact & Results
Intelligent question-answering with conversational interaction for educational queries
Document processing pipelines for academic materials and research papers
Advanced embedding strategies improving response relevance by 40%
Natural language search interface for students and faculty
Technologies
Links
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