Xabier Muruaga

I shape production AI & GenAI from value framing through deployable architecture, with embedded governance and technical assurance. The objective is simple. Capture material value while keeping risk, economics, and operational ownership under control.

In large organizations, GenAI stalls for predictable reasons. Fast prototypes do not survive scale when decision rights are unclear, policies fragment across teams, and accountability is reconstructed after the fact. Drift follows in risk exposure, economics, and operational complexity.

I make scale deliberate. I define the architecture, decision boundaries, and acceptance criteria that let teams deliver consistently. I embed assurance into the way systems run so policy, evidence and economics are not negotiated on every release. This is what enables sustained expansion of high-value use cases without compounding risk or cost.

This site documents the approach in two forms. Case studies show applied work through concrete artifacts and acceptance criteria.