You find out what is genuinely automatable here, counted from your own history.
Two to three weeks
We read your own conversations and operations, privacy-first, and hand you the numbers: how long people wait, what never gets answered, what repeats, and exactly which share an agent could take — and which actions would still need a person.
What staying as you are costs
Another quarter of deciding by anecdote. Then in month three someone asks whether the AI helped and by how much, and the honest answer is that nobody counted before it started.
What happens
- Days 1–2Nothing touches production. You send a read-only export of the workflow's own history; no write access to anything, and no change to how the work runs while this happens.
- Days 3–7The counting. How long people wait for a reply, what share of requests never got an answer at all, which questions come back week after week, and when the queue really peaks rather than when you think it does.
- Days 8–11The sorting. Every recurring request becomes the list of actions it implies, and every action lands on the risk tier table: read, draft, reversible change, external, irreversible. This is where you see which part an agent could take and which part has to stay with a person.
- Days 12–14The read-out. Ninety minutes with your team, then the written baseline. Yours to keep whether or not we ever work together again.
What you have at the end
- Baseline: response times, unanswered share, repeat questions
- The automatable share, counted from your own history — not estimated
- An approved-answer backlog you own, whether or not you continue
- The action list split by risk tier: what an agent may do, what a person must
What it takes from your side
- Six to twelve months of the workflow's own history, exported read-only
- One person who knows how the work is really done, for about three hours in total
- Ninety minutes for the read-out, with whoever makes the decision in the room
