Production RAG
Smart Context Selection
Before: users had to manually pick which documents went into the AI's context, then we'd dump up to 300 pages of raw text into every request. Slow, expensive, and fragile when documents grew.
After: the user just asks the question. The system identifies the relevant documents, pulls only the chapters that matter, and stitches them into a context that is ~80% smaller without losing any retrievable information. Built as a generalisable context tool used across analyses, chats, and documentation flows.
~80% smaller · lossless