Custom RAG assistant trained on company documents

The situation

Staff wasted time hunting through scattered documentation, and a generic chatbot just made things up.

What we did

We built a RAG pipeline over the company's documents — correct chunking, a tuned embedding strategy, and retrieval that returns sources with every answer. An eval set lets the team measure accuracy rather than guess at it.

The outcome

The team now has one searchable source of truth that answers from real documents and shows its sources, so answers can be trusted and verified.