An audit of your data governance, infrastructure, and team structure against the demands of running AI in production. Gap analysis with a prioritized remediation plan.
For teams that have moved past the “should we do AI” question and need to know if the infrastructure, governance, and team structure can support it at scale.
An honest look at your data pipelines, storage, labeling practices, and model deployment infrastructure. Where the gaps are before they become outages.
Where your current practices fall short of the requirements for regulated industries, enterprise customers, or internal risk management.
Who you need to hire, who you’re missing, and how to structure the team so AI work doesn’t become a black box that only one person understands.
A ranked list of gaps to close, in the order that will unblock the most work. Not everything at once — the things that matter first.
A deeper engagement for organizations with more surface area to audit. Most of the work is on my side; you’ll spend about 4 hours total.
Scope the audit, exchange architecture docs, data inventories, org charts.
Review infrastructure, governance practices, team structure. Interviews with 2–3 stakeholders.
Score gaps, prioritize remediation, draft the report.
Report delivered. Walkthrough call with recording.
Paid up front. Refunded in full if I decline the work after the intro call.
Governance, infrastructure, and team gaps — with a remediation roadmap.
Book the intro call →No pitch. You’ll leave with a clear recommendation — even if that recommendation is that you don’t need an assessment at all.
Book the free intro call →
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