Service
Put AI where it moves the number
A single use case chosen for its impact, put into production with the success criterion agreed before we start.
One use case in production, not a pilot
The problem it solves
The conversation about AI usually starts with the tool and ends in a pilot nobody uses. The right order is the opposite: first the process that hurts, then whether AI is the answer, and often it is not.
What I do
I look at where the time goes in your operation and point at the place where a language model genuinely moves the number: classifying incoming items, drafting repeated replies, extracting data from documents, searching across your own documentation.
We pick one. What counts as working is defined before any code is written, and it goes into production with evaluation in place, so you know whether it is still working three months from now.
If the case does not justify the spend, I tell you so in the diagnosis and it ends there.
How it is measured
The criterion is agreed before we start and it is written down: cycle time, percentage of cases resolved without intervention, cost per operation. It is measured in production, on real data, not in a demo.
What I need from you
Access to a representative sample of the real data from the process, and to someone who can tell a good answer from a bad one.