AI Engineer · Software Architect · Open-source builder

LinkedIn · Turin, Italy

I help product and engineering teams turn useful AI ideas into dependable products: private when they need to be, efficient enough to run in the real world, and clear enough for people to understand and trust.

When an idea crosses my mind, I build it, mostly to find out where it breaks. Every repository here is a small lab: an idea, an implementation, and a pile of problems I only discovered by trying.

Not everything works. Each project's README says what is proven and what is still open. Think of them as maps of the traps, drawn by someone who stepped on most of them first.

The pinned repositories below are what I would show first. Everything else is in the repositories tab, most recently updated first.

Configuration over hardcoding. Models, providers, policies, and infrastructure should be replaceable without redesigning the product.

Explicit contracts. Clear boundaries and verifiable outcomes make complex systems safer to change.

Local-first where it matters. Privacy, cost control, reproducibility, and offline use are product capabilities.

Evidence before claims. Tests, evaluations, and operational records should support every important guarantee.

Useful to people. Technical novelty matters only when its real-world benefit can be explained plainly.

My background spans full-stack development, microservices, distributed systems, data engineering, cloud-native architecture, and applied AI, with a research background in security and privacy for IoT systems. Away from the keyboard, I climb.

Current interests: Agentic AI · Local AI · Distributed Inference · MCP · Forecasting · Data Platforms · Cloud Native · Python · TypeScript · Java / Spring · React

The best place to reach me and follow my professional work is LinkedIn.