Consulting · A US technology consultancy

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

An internal assistant over the company's own documents
The challenge

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
What we did

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
What changed

The results

Internal questions answered from one interface instead of three people
Financial reports gathered automatically for analysis
Document pipeline reused for new data sources

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