1 / 3
Diagnosis
We clarify the goal, data, constraints, and success metric before choosing technology.
For product teams and companies deciding where AI creates value, what to build, and how to ship it.
From feasibility and data to prototype and deployment: practical technical direction for companies applying AI beyond the demo.
Discuss the problem1 / 3
We clarify the goal, data, constraints, and success metric before choosing technology.
2 / 3
We reduce risk with a measurable prototype or a product vertical slice.
3 / 3
We build, integrate, and document a solution your team can maintain.
Problems, constraints, architectures, and observable results: each project shows how we turn technical capability into a usable system.
An AI product that turns lecture recordings into structured Word notes ready for study.
Read the case studyA Data Ops platform making ISTAT open data easier to use through documentation, APIs, search, and guided interfaces.
Read the case studyAn enterprise text-to-SQL interface designed to make data queryable without giving up control or auditability.
Read the case studySimone Zannini and Matteo Cese stay involved through analysis, development, and delivery. Roles, profiles, and CVs are public.
No. We start from the decision or process to improve. If a deterministic solution is better, we say so.
Yes. We can work alongside product and engineering, transferring decisions, code, and documentation.
We reply within two working days with the first technical questions and a sensible next step.
magosimo99@gmail.com