Data & RAG
Answers grounded in your documents, with sources.
Retrieval-augmented generation lets a model answer from your own material and show where each answer came from. Quality depends on the unglamorous parts: cleaning, chunking, permissions and testing. That is where we spend the time.
What you get
- Document pipelines for files, wikis, tickets and databases
- Search that respects who may see what
- Cited answers, and “not found” when the answer isn't there
- Accuracy test sets built from real questions
- Refresh schedules so answers stay current
A good fit when
People waste time hunting through documents, or asking the two colleagues who know.
Not sure where AI fits? Start with the assessment.
Two weeks, fixed price, and the fee comes off your first build. You finish with a ranked plan you can act on, with us or without us.