Artificial Intelligence Diagnostic
AI Diagnostic
We look at your process and say where AI goes in and what has to exist first. If it is already in, we measure how much it is used, what it costs and what it could still return. Scope and price in writing before we start.
Two situations, one diagnostic
Not using AI yet
Where AI goes in first
We map the process as it runs today and point to the steps where AI returns most, what it may read, who signs off when it is wrong, and what has to exist first: data in place, review agreed, cost measured.
Already using AI
How much it returns, and how much more it could
We measure how much the team uses it, what each answer or task costs, and where a standard, a review or a limit is missing. And we say, in writing, what more it could return with what you already have.
What you get
A document with what we found, in what order it matters, what it costs to do, and what to do without us. Then a conversation with your engineers and your leadership in the same room, because the two of them hearing it separately is how it stops being acted on.
The diagnostic stands on its own. Whatever comes after is agreed in writing, after it.