Answers from your knowledge — not guesses
A retrieval-augmented generation (RAG) assistant connects a language model to your documents, so it answers real questions with real sources. It's the difference between a chatbot that frustrates customers and a knowledge assistant your team and customers actually trust.
We build the full pipeline — ingestion, retrieval, citations, permissions, and evaluation — and deploy it where your users already are: your website, an internal portal, or Slack/Teams.
Who this is for
If your answers live in PDFs, manuals, policies, a help center, or a pile of support tickets, a RAG assistant turns that scattered knowledge into instant, accurate responses.
What we build
A production-grade assistant with the unglamorous parts done right: clean ingestion, grounded retrieval, citations, access control, and measurable quality.
Example use cases
Customer support, internal help desks, sales enablement, and document search are the highest-ROI starting points.
How we work
Discovery → content audit → ingestion pipeline → retrieval & citations → evaluation → deploy → monitor question gaps → improve.
Frequently asked questions
Who this is for
- Businesses with manuals, policies, SOPs, or large document libraries
- Support teams answering the same questions repeatedly
- Sales teams that need instant answers from product and pricing docs
- Internal teams onboarding staff who need fast, reliable answers
What we build
- Document ingestion pipeline (PDFs, docs, wikis, tickets, databases)
- Retrieval-augmented generation with source citations
- Chat interface (web widget, internal portal, or Slack/Teams)
- Access controls and per-document permissions
- Evaluation harness to measure answer quality
- Analytics on questions, gaps, and deflection
Example use cases
Frequently asked questions
A regular chatbot follows scripted flows or guesses from a general model. A RAG assistant retrieves your actual documents at query time and answers from them with citations — so it stays accurate and current as your content changes.