Steven MacLeod

About

I'm a data-centric system designer, data philosopher and public speaker with 25 years experience designing, building and configuring enterprise data systems. My career has seen me working across government and industry delivering large-scale product, compliance, and industrial systems, often in environments where reliability, auditability, and long-term correctness matter. Much of my early work involved data migrations, which led to me performing autopsies on failed systems — pulling them apart to see why they broke. It's very clear that systems fail because the underlying data model is structurally broken, logic is scattered, systems are patched, and from that point on failure is inevitable. I wasn't interested in working on systems that needed constant fixing. So, I set out to develop a data platform that allows systems to remain correct as they scale, change, and are used in new ways. That meant rethinking the data layer rather than the UI. Making the logic explicit. Treating metadata as execution, not documentation. And defining structure, behaviour, and governance once, so they remain consistent over time. That work took years of research. It resulted in the Occam Data Platform — an ontology-native system where the meaning of the business is defined once and used to generate the operational and analytical systems that depend on it. Because the logic is explicit and executable, the system remains deterministic, auditable, and stable as it scales — and provides a semantic foundation AI can work with directly, rather than probabilistic inference from broken structures. We've built that platform. My focus now is on delivering Occam to become a core component of a modern, AI-native data architectures — where meaning is explicit, behavior is deterministic, and AI can operate without guessing.