Most companies have AI pilots. Far fewer have AI in production.
The gap is rarely the model. It is data nobody cataloged, identity never designed for non-human actors, governance that exists as a document rather than as a control, and cost nobody can attribute to a feature. Those are architecture problems.
Engagements
Most relationships start with the two-week readiness assessment. It is designed to be a small, bounded first purchase that leaves you with something useful either way.
Enterprise AI Readiness Assessment
A scored picture of where you actually are across eight domains, which of your initiatives are buildable now, and a 90-day roadmap.
Cloud Well-Architected Review
One Azure subscription or landing zone against the five Well-Architected pillars. Every finding names the control it failed and the artifact that showed it, and cost findings are stated in dollars a month rather than as "consider optimizing".
Enterprise Architecture Health Check
Applications, integration, data, cloud, security, IAM, DevOps and technical debt, with a current-state assessment and a modernization roadmap.
AI / Agent Architecture Accelerator
Design of an enterprise agent platform: LLM gateway, workload identity, governed retrieval, tool registry, guardrails, evaluation and per-call cost control.
Architecture Governance Accelerator
Principles, standards, review lanes, ADR-as-Code, exception management and policy-as-code gates. Governance that runs in a pipeline rather than in a meeting.
The Well-Architected and IaC gates draw on a control catalog and framework mappings I maintain as code, so your engagement starts from a working set rather than a blank page.
Fractional Chief Architect / CTO
Senior architecture leadership on a monthly retainer, for organizations that need the judgment without another full-time executive.
Cloud & modernization architecture
Landing zone design, migration architecture, and well-architected review across Azure and AWS. Usually scoped from a health check.
How I assess
Three things that make the output worth acting on.
Against evidence, not interviews
Every finding is tied to an artifact I asked to see: the configuration where model names live, the permission set an agent actually holds, a monitoring dashboard with real values in it. Executives describe the intended state. The systems describe the real one.
Readiness follows your weakest domain
Not your average one. An organization strong in seven domains and absent in one cannot ship, and an averaged score hides exactly that. I lead with the binding constraint and what it blocks.
Feasibility is capped by reality
A use case needing retrieval over unstructured content is not feasible while that content is uncataloged, however much the sponsor wants it. You get a prioritized matrix of what is buildable now, what needs specific remediation, and what is not this year.
What the assessment delivers
Two weeks, five stakeholder interviews, one live executive readout.
How engagements work
Fixed price, fixed scope
You know the cost before the work starts, and the statement of work says what is excluded as clearly as what is included.
You own the deliverables
I retain my own templates and methods, and reuse them on your behalf rather than rebuilding them at your expense.
No production data
Assessment is performed against your systems in place. I do not request or receive production data, which keeps your security review short.