01Already in production
The engine that generates the tests of the Premio Di Nicola 2026, a maths and logic competition for students in Abruzzo now in its 18th edition, comes from this work. See Generated learning paths and the technical article.
02How the work runs
- Discovery. Before any code: interviews, a look at the data you already have, technical and business constraints on the table.
- Architecture. Data schema, component boundaries and failure points decided on paper, when changing them costs an hour and not a month.
- Build. Short iterations with working demos instead of one delivery at the end. AI speeds things up where it makes sense; it never replaces review and testing.
- Handoff & scaling. Documentation, runbooks and a system your team can run without depending on me. No lock-in.
03Pricing
Every project is priced after a scoping call: the same word, "chatbot" or "agent", can mean a two-week prototype or a system in production for thousands of users. What moves the price:
- subjects and levels to cover;
- exercise types (closed, open, multi-step problems);
- integration with existing platforms (LMS, accounts);
- number of students and privacy requirements, especially for minors.
The first call is free and ends with a clear answer: whether the project makes sense, roughly how big it is, and what to do first.