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Diagnosis
We clarify the goal, data, constraints, and success metric before choosing technology.
For startups proving feasibility, building a credible demo, or preparing a solid foundation for an engineering team.
AI for startups: validate technical risk before scaling the product
We work with founders and early-stage teams to turn an AI hypothesis into a measurable MVP with explicit costs and limits.
Discuss the problemWhere we help
- Technical discovery and scoping
- AI MVPs and proofs of concept
- Make-or-buy assessment
- Preparation for scale
What your team receives
- Validation assumptions and metrics
- End-to-end prototype
- Cost, latency, and quality estimate
- Technical backlog and handover plan
From uncertainty to a verifiable delivery
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Technical proof
We reduce risk with a measurable prototype or a product vertical slice.
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Delivery
We build, integrate, and document a solution your team can maintain.
Projects that make the service concrete
Problems, constraints, architectures, and observable results: each project shows how we turn technical capability into a usable system.
People, not a black box
Simone Zannini and Matteo Cese stay involved through analysis, development, and delivery. Roles, profiles, and CVs are public.
Questions before starting
Can you start from a pitch or an idea?
Yes. We translate it into testable assumptions, required data, and a technical scope that can be demonstrated.
Will the MVP be ready to scale?
We design an evolvable base while clearly separating what validates the idea from what is required at scale.
Bring the problem, not a perfect specification.
We reply within two working days with the first technical questions and a sensible next step.
magosimo99@gmail.com