Client Challenge
A financial services company was moving part of its operations into a shared service centre. The documentation described the steps, but not the judgement behind them: which exceptions matter, who to call, and what to do when the system says no. That knowledge lived in a few experienced people.
Handovers, workshops and documentation projects lose that knowledge with every step. The client wanted to know whether it could be captured, checked and kept current at the pace of a transition.
Response
We built a knowledge engine and tested it on one sub-process in one market. It reads the existing material, asks the experts what is missing, and records the result in a form that can be checked.
The AI read and drafted, the client's experts approved, and nothing entered without a source. Along the way it surfaced contradictions between documents, gaps nobody had on paper, and procedures that had never been written down, with one person as the only fallback.
The same discipline runs through all our work: see how we work.
Outcomes
The client's own experts checked the result item by item and rated 94 percent of it correct. The remainder became a corrections list before go-live instead of an error after it.
This was a proof in one sub-process, not a production system. Loading documents is the easy part; keeping the model right is the work. What it shows is the value within reach: one definition of the work, audit evidence by default, a cleaner handover, and an assistant that answers with a reference.
