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Enterprise RAG-Based Document Intelligence

A production retrieval-augmented generation platform that turns sprawling enterprise document sets into grounded, cite-backed answers.

LangChainLlamaIndexPineconeFastAPI
Abstract indigo and amber cover illustration for the Enterprise RAG Document Intelligence project, showing layered document planes connected by glowing citation lines.

Highlights

  • Hybrid dense + BM25 retrieval with metadata-scoped filters for tenant isolation.
  • Chunking and embedding pipelines tuned per document type (contracts, policies, wiki).
  • Answer synthesis with inline citations, source previews, and refusal on low-confidence retrieval.

Outcomes

  • Reduced average research time per query by 60% across pilot teams.
  • Scaled to millions of chunks with sub-second p95 retrieval latency.

Stack

  • LangChain
  • LlamaIndex
  • Pinecone
  • FastAPI
  • PostgreSQL
  • OpenAI API