RAG applications

Retrieval-augmented generation (RAG) lets a language model answer using your organisation's knowledge instead of only what it learned in training. Done well, it produces accurate, citable answers that stay current as your content changes.

Quality depends mostly on the retrieval pipeline: how documents are parsed, chunked, enriched, indexed and ranked — and whether users only see content they are permitted to see. That is where we focus.