"I help organizations bring Generative AI from experimentation
to secure, scalable, and governed
production systems on Google Cloud."
I guide engineering and business stakeholders in bridging the gap between fragile experiments and robust IT infrastructures.
Strategic guidance for CTOs and engineering teams in designing LLM pipelines. Primary focus on FinOps (cost optimization), Data Privacy (GDPR), and Enterprise Security.
Bridging the gap between Data Science and IT operations to build zero-downtime deployment pipelines, integrating automated evaluation gates (LLM-as-a-Judge) to prevent regressions.
Aligning business goals with technical feasibility. Building roadmaps to scale AI adoption, maximizing ROI and mitigating technological risk.
To ensure my advisory is constantly backed by solid, field-tested engineering, I run a dedicated sandbox architecture lab: Kybername.it.
Here I design and validate cutting-edge reference patterns for the GenAI ecosystem:
Beyond code: socio-technical principles and systems thinking to decode and govern enterprise complexity.
My background bridges Electronic Engineering and Management (MBA) with cybernetics and complex systems theory. This socio-technical approach ensures architectures don't merely solve isolated technical tasks, but seamlessly align with enterprise operational constraints, regulatory frameworks, and long-term business dynamics.
In an era of rapid AI evolution, ethics translates into Responsible AI. We face complex challenges not by blindly relying on the black box, but by building deterministic rails, rigorous security policies, and transparent architectures that protect the company's long-lasting value.
I consider AI not an end, but the most powerful means to liberate human time. Extreme automation of routine work serves to restore people's freedom of action necessary to focus on creative, strategic, and relational thinking.