Your documentation, answering questions in plain language
Most companies already wrote down the answers — in handbooks, SOPs, product manuals, and wikis nobody can search well. I turn that documentation into an AI knowledge base your employees (or customers) can simply ask, getting cited answers from approved sources in seconds instead of pinging a colleague and waiting.
Sound familiar?
Answers exist but can’t be found
The information is in Confluence, SharePoint, Drive, and a dozen PDFs — effectively invisible the moment someone needs it mid-task.
Experts are the search engine
Your most experienced people spend hours a week answering the same routine questions instead of doing the work only they can do.
Onboarding takes months
New hires learn by interrupting veterans, because finding the right document takes longer than asking.
Support repeats itself
The same product questions arrive over and over, and each one is answered by hand — slightly differently every time.
How I approach it
Inventory and prepare the sources
We identify which documents are authoritative, which are stale, and what access rules apply. Your documentation is transformed into structured, searchable knowledge.
Build Q&A on a measured foundation
Retrieval and answer quality are tested against real questions from your team before launch — so "it works" is a measurement, not an impression.
Answer with citations, escalate with grace
Every answer links to its source. Questions the documentation can’t answer are escalated to a human instead of being guessed at.
Meet people where they already work
The assistant lives in Slack, Teams, your help desk, or your intranet — not in yet another tool nobody opens.
What you get
- An AI knowledge assistant grounded in your approved documentation
- Cited answers with “I don’t know” behavior instead of guesses
- Integration with your existing chat, help desk, or intranet tools
- An update path for new and changed documents, plus handoff docs and training
Backed by published testing
Reclaiming AI Document Search Quality Through Configuration Testing And Parameter Sweeps
Four rounds of systematic testing — 16,143 evaluations across 40+ configurations — produced a single evidence-based RAG setup, overturning several "best practice" assumptions along the way.
Read the full studyFit check: text-based documentation works best — handbooks, SOPs, manuals, policies, FAQs, and knowledge base articles. Image-heavy documentation is usually a poor fit, and I’ll say so during the free discovery if yours is.
Find out what this would look like for your team
The consultation and initial discovery are free — you get a preliminary recommendation whether or not we work together.
Book a Free Consultation