An internal assistant over the company's own documents
Consultants were hunting through years of internal documents by hand and pulling financial reports manually. We built a RAG assistant that answers over the whole corpus with live data.
RAG over the internal corpus
Live financial data pipelines
Next.js + FastAPI + Pinecone

What was actually broken
Knowledge lived in thousands of documents with no index, and answering a simple internal question meant asking three people. Meanwhile financial analysis depended on reports gathered by hand.
- Client
- A US technology consultancy
- Industry
- Consulting
- Duration
- Ongoing engagement
- Team
- Senior engineer-led
- Stack
- Next.jsFastAPIFlaskPineconePython
The approach
- Built an internal RAG system over company documents with vector search
- Implemented Flask services that gather real-time financial reports for AI consumption
- Shipped a Next.js interface integrated with FastAPI and Pinecone
- Architected document processing pipelines for scale and repeatability
The results
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