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I tell you where AI genuinely helps in your process, and where it is only another cost.

AI-generated image

AI arrived before the right questions did.The problem is almost never which model to use, but which step of the process is worth handing to a machine — and which is better left to a person.

  1. Look at the process

    I start from how you work today, not from what the model can do: where time is lost, where mistakes happen, where somebody re-reads everything by hand.

  2. Pick a single step

    I isolate one, the one with the best ratio of effort removed to risk introduced.One, not five: it is the only way to know whether it worked.

  3. Try it on your data

    I run it on your real cases and measure: how much it solves, how often it is wrong, what it costs per month.If it does not hold up, I say so before building.

  4. Put it in with limits

    I deliver it inside the workflow, with the checks and the points where a person has to confirm.A system that decides on its own with nobody watching is not something I hand over.

AI-generated image

This is not general AI training,and it is not installing a chatbot on your site.I do not promise that AI is needed: half the work is saying which steps are better left exactly as they are.

Do I actually need AI here?
Often not, and it shows up early: many processes are unblocked by ordinary automation, which costs less and does not get things wrong.When that is the answer, you get it — even though it is worth less to me.
Where does my data end up?
That is the first thing we decide: which data leaves the company, to which supplier, and how long it is kept.If the answer is not acceptable, we change the tool, or we change the step.
How do I know it works?
With a trial on your real cases and a number before and after.If the number does not improve enough to justify the cost, that step stays as it is.

Tell me about the process that's jammed — together we choose the right piece to unblock it.

software@stelion.it