Bringing structure to complexity.
Cloud, AI, and enterprise architecture. Understand the system, make the design decisions, and define a path from an idea to something your team can operate.
An assessment before investment. A blueprint before implementation. Architecture leadership and governance as the system evolves.
Understand the current state, identify material risks, and decide what to change before committing to more build work.
Turn agreed requirements into a target architecture, explicit tradeoffs, and an implementation plan.
Implement an approved design with validation, operating documentation, and a defined handover.
Bring a regular architecture review cadence to roadmap, platform, vendor, and delivery decisions.
Review architecture against agreed standards, track exceptions, and keep accountable actions visible.
Diagrams, decision records, risk and owner maps, and implementation plans. Not just a recommendation, but the reasoning and the next action.
View example deliverablesAgree the goal, the system boundary, and the evidence.
Compare options and record the tradeoffs and owners.
Define implementation, validation, and handover.
The two Azure frameworks answer different questions; use the Cloud Adoption Framework for estate decisions and the Well-Architected Framework for a single workload, and name the control owner where they overlap.
Use the action-authority question from Microsoft's AI Decision Framework to decide whether an agent drafts, executes with approval, or acts alone, and what each level costs to operate.
Use Microsoft's AI Decision Framework to gate the use case, operating model, and action boundary before choosing Copilot Studio, Microsoft Foundry, or a custom agent.
Bring the system, the business goal, and the constraints. Scope, deliverables, and fee are agreed before work starts.
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