Sheet C-09 · Case record
Client withheld — NDA
RAG-based knowledge retrieval across thousands of enterprise documents — LangChain, OpenAI embeddings and Pinecone serving cited answers in under half a second.
Sheet 01 · Record
85%
Less time hunting documents
<500ms
Average answer time
98.5%
Answer accuracy vs source
Sheet 02 · Brief
01 The challenge
Thousands of SOPs, policies and technical manuals sat scattered across SharePoint, Google Drive and legacy systems. Employees averaged 45 minutes per query hunting for the right information, and different teams got different answers to the same question.
02 The approach
A Retrieval-Augmented Generation pipeline: LangChain handles ingestion and chunking, OpenAI embeddings power semantic search, Pinecone stores the vectors. A FastAPI backend adds intelligent caching under a conversational React frontend — and every answer carries a citation back to its source document and page, so trust is checkable.
Sheet 03 · Results
The results
Sheet 04 · Stack
Sheet 05 · Next
