The consultant who has actually shipped enterprise AI

I started Define Data because I kept seeing the same thing: companies under real pressure to deliver AI, surrounded by advice from people who have never shipped it. Pilots that never reach production, data that cannot be trusted, governance treated as an afterthought. They did not need another deck — they needed a partner who has built this before. That is what Define Data is: a senior-led practice, with trusted specialists I have worked with for years brought in as each build demands.

Most recently I was Head of Data & Product at an enterprise AI platform serving 20+ enterprise customers of 500 to 10,000 employees. I architected the core AI platform — retrieval augmented generation, semantic layer, metadata architecture, vector search, context engineering and tenant isolation — and designed the governance that made it trustworthy: provenance, confidence scoring, permissions and auditability. I led Product, Engineering and Data, ran executive discovery workshops with CTOs and Heads of Data, and co-designed the agent architecture behind configurable enterprise AI use cases.

Before that I built and led the Data, Analytics and Business Systems function at a Series C fintech — owning architecture across Salesforce, NetSuite, HubSpot and Jira, building an AI-ready Snowflake/dbt platform, and improving pipeline data quality by 80%.

Earlier I led digital analytics for a €50 million banking transformation — 1.5 billion events a year from more than a million customers, presented straight to the steering committee — and grew from analyst to leading a team of analysts and data scientists across a €500 million e-commerce business in 14 markets.

That is the full span — AI, data, systems and the executive table — and it is exactly the span AI transformation has to cross to work.