Principal Enterprise Architect | Enterprise AI Strategy, Governance & Architecture | Building Getamazednow Assure
I work at the point where business capability, technology strategy and architecture governance become practical enterprise decisions. My background spans complex technology portfolios, multi-cloud platforms, integration modernisation and enterprise AI adoption across retail, banking, financial services and other regulated environments.
My current focus is the transition from successful AI experiments to trusted enterprise operation: the architecture, governance, observability, control and evidence required for AI to operate reliably at scale.
Getamazednow Assure did not begin as a predefined product suite. It began with a practical enterprise question: how do organisations move AI from promising experiments into production while keeping approved intent, deployed behaviour, operational evidence and governance connected?
I explored different parts of that problem through architecture research and working implementations: agent orchestration, AI observability, digital sovereignty, governance evidence and operational control.
As the work developed, those capabilities stopped looking like separate experiments. They began to form one connected enterprise platform. The repositories evolved with that convergence and were renamed around the product capabilities they now represent.
The result is Getamazednow Assure — an IntentOps platform designed to turn approved intent into enforced, observable and evidenced reality.
The platform brings together seven connected product modules.
Maintains business capability maps, application portfolios and technology roadmaps against the live enterprise estate, creating the architecture context for governed change.
Creates the trusted record for each consequential AI or agent change, connecting purpose, approval, expected behaviour and observed reality.
Turns approved intent into machine-testable policies, controls and delivery gates, with mappings to enterprise and regulatory frameworks. Govern also houses reusable Control Packs, beginning with the Australian Digital Sovereignty Reference Architecture (ADSRA).
Provides drift detection, telemetry and conformance evidence showing whether deployed AI continues to behave as approved.
Builds the evidence graph linking intended, approved, deployed, observed and changed states into a reconstructable history.
Develops reusable enterprise AI skills and architecture capabilities that can be assembled into governed workflows and platform integrations.
Provides the runtime and implementation spine connecting contracts, gates, evidence hooks and governed memory across the Assure platform.
The research and reasoning behind the platform are documented in my writing on AI observability, control planes and measurable Responsible AI.
- Part 1: AI Observability Is No Longer Optional
- Part 2: Building the AI Control Plane
- Part 3: Responsible AI in Production
- Retail Cannot Afford Variable Truth
- Enterprise architecture, business capability and technology portfolio strategy
- Enterprise AI strategy, governance and responsible adoption
- Architecture assurance and investment decision support
- Multi-cloud, integration and platform modernisation
- AI observability, agentic governance and operational evidence
I am open to conversations about Principal or Lead Enterprise Architect, Enterprise AI Strategy and Governance, Head of Enterprise Architecture, Chief Architect and Fractional advisory opportunities.