DocRAG
Document Intelligence Platform
A full-stack RAG platform that lets teams ask natural language questions about their own documents and get accurate, cited answers.
The use case is straightforward to describe and surprisingly hard to do well: let users ask questions about their own documents and get accurate, cited answers.
DocRAG handles the full pipeline — document ingestion, semantic chunking, vector indexing via Qdrant, and chat-based retrieval through a Next.js frontend. The non-trivial part is making the retrieval reliable enough that answers are actually grounded in the source material, not hallucinated. Getting that right requires careful chunking strategy, query handling, and reranking logic.
The live demo is publicly accessible. The underlying architecture is designed to be adapted for specific enterprise contexts.
Technology Stack
Domain
Project type
Full-Stack Product
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