AI for Italian SMEs: from pilot to everyday work
In small and mid-sized companies, AI often stops at the same point: a pilot that works, and then nothing. The reason is rarely the technology: the project started from the tool, not from the problem. We do the opposite. We look at how you work today, find where you lose time and money, and bring AI in only where it matters, all the way into everyday work.
Why AI stalls at the pilot stage in SMEs
A platform is bought, a model is switched on, there is a demo. Then everyday work stays the same because nobody decided which task or decision should improve.
The first question is always the same. Which task, done every day by someone in your company, becomes shorter or safer if this system works? If the answer is not clear, the project does not start.
How we work, in 4 steps
- We read the process with the people who do it, not only with those who manage it.
- We choose one starting point, one that can be measured.
- We build and test on real work, with the people who will use it.
- We bring it into everyday work and check that it holds. If the data is sensitive, the system runs inside the company.
Where AI can start in your company
Five questions, two minutes. Your answers stay in your browser: we do not store or send them. The result is a pointer to get started, not a diagnosis.
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Start from a process
You have a specific task, data in order, and one person responsible: it is a good starting point. The next step is to measure how that task works today and try AI there, on real work.
First put the data in order
AI works on the data it finds. If it is scattered across systems, spreadsheets, and email, or nobody knows where it is, the first step is to decide where it should live and who keeps it up to date.
First choose the task, and who owns it
Without a specific task to improve and one person responsible for it, even a good tool stalls. The first step is organizational, not technological: pick a small process and give someone ownership of it.
Start from what is there. Who uses it, for which task, with whose approval: the first step is often already there.
With health, personal, or confidential data, consider a system that runs on-premises, inside the company. On-premise AI
When data cannot leave: on-premise AI
For health, legal, personal, or confidential data, we propose language models that run on the company's own machines, or on a server under its control. When the data is about patients or covered by professional secrecy, we explain how on the page on on-premise AI.
Pierantonio Idini
Pierantonio uses AI every day: he built, on his own and in one week, the application he uses to follow his company's tasks, hours, and expenses. The hard part, he says, was not the code: it was knowing what to ask for. He brings the same thing into companies.
Building my own app with AI: what I learned
Often the moment to start is a bigger change, such as a family business succession.
Frequently asked questions
Do I need to buy new software?
Not necessarily. We often start from tools you already have. If we need something new, we choose it after understanding the process.
Will my data leave the company?
It depends on how the system is designed. For sensitive data, we propose on-premises systems.
How long does it take?
It depends on the process. We tell you once we have seen it, before starting.
What changes for the people who work there?
The system is tested with the people who will use it, on their own work. If it does not help them, it does not go in.
What if it turns out not to be useful?
We say so frankly, and we stop there.