Nobody can find what we already know
The answer exists in a document somewhere and it is faster to ask a colleague than to search for it.
What is actually going on
The content is unstructured, so nothing indexes it usefully. Extraction into structured records, then retrieval that cites what it used, is what turns an archive into something answerable. The hard part is permission aware retrieval, so an assistant cannot surface a document the person asking could not open.
Who usually owns this
IT director, Knowledge leader, COO
How people describe it
- "AI answers based on company documents"
- "chatbot that cites internal documents"
- "make PDFs emails and recordings searchable"
What resolves it
- RAG Consulting. RAG consulting: retrieval-augmented generation grounded in your documents, with vector databases, citations, and access controls, so AI answers from your data.
- Answer Engine Optimization Services. AEO and GEO services that get your brand cited in ChatGPT, Perplexity and Google AI answers. Answer content, schema, llms feeds, and cross-engine measurement.
Read up on it first
- Why Nobody Can Find What Your Company Knows. Start here. Asking a colleague wins because it solves four problems at once: the content is unstructured, nothing indexes it usefully, nobody knows which copy is current, and the asker may not be cleared to see it. Any fix that solves one loses to the colleague. Also, the statistic everyone quotes for this is from 2012.
- Retrieval That Respects Who Is Asking. Choosing an approach. One design decision separates a knowledge assistant that can be approved from one that cannot: permissions resolved per user at query time, or a permission graph copied into the index. One test tells them apart, and it is the test most often skipped.
- What to Ask Before a Knowledge Assistant Build. Scoping the work. Eight questions, six of them about the permission model and the evaluation set, because those decide whether it gets approved and whether it works. Plus the acceptance criteria split into the four your security reviewer owns and the four your business owner does.
Proof
Adverse event processing from 18 days to 4 hours
We cut adverse event processing from 18 days to 4 hours for standard reports and 6 hours for serious cases. This overhaul pushed on-time submission compliance to full within three months. Automating data handling freed up the equivalent of five of the eight specialists’ time, shifting their focus from routine processing to signal detection.
- 18 days to 4 hours, Adverse event processing time.
- Full, On-time FDA submission compliance.
- 5 of 8, Pharmacovigilance specialists' time freed.
- 6 sources, Adverse event data sources unified.
Getting it approved
Other problems
What is actually going on
Who usually owns this
How people describe it
What resolves it
Read up on it first
Getting it approved
Three pieces, in the order the question usually arrives. Each one is evidence-led and names its sources.
Whoever signs this off is asking a different question from the one you are asking.
is the worksheet for that conversation. Yours whether or not you hire us.