01 · Strategy
Enterprise AI strategy that survives the board
Most AI strategies fail because they confuse capability with use case. I build portfolios with prioritised problems, honest economics, and measurable controls before a single model ships.
Senior analytics · AI · transformational leadership
Twelve years inside Fortune 100 programmes, state government, and ventures of my own. I lead analytics and AI work that survives audit, regulation, and the second year of operation.
Trusted by
Engagements at Fortune 100 firms, state government, and operating businesses across regulated industries.
Practice areas
01 · Strategy
Most AI strategies fail because they confuse capability with use case. I build portfolios with prioritised problems, honest economics, and measurable controls before a single model ships.
02 · Platforms
Source-of-truth data models, contract-driven pipelines, and dashboards a CFO would actually defend. Built on dbt, Snowflake, BigQuery, Postgres, and a clear semantic layer.
03 · Healthcare AI
From predictive readmission to documentation validation and prior-authorisation automation. I have built clinical AI for Optum and now run AevoraOS for our own home care agency.
04 · Government
Legacy systems, accountability constraints, and the careful pace public work demands. I currently lead analytics architecture for a state department in Connecticut.
05 · Document intelligence
DocSensei, the platform I built and licensed to a Fortune 1000 insurance broker, processes complex policy documents at scale. Production patterns, not demos.
06 · Leadership
Hiring rubrics, roadmap discipline, and the cultural work that gets a data and AI function from cost centre to profit lever. Coached founders and senior leaders across three continents.
A note before you read further
I was kidnapped at fourteen and trafficked across the Sahara into Libya. Then I came home, finished school, and got to work.
The reason I tell this is not for sympathy. It is the most honest explanation of why I take risk seriously, why I refuse vanity work, and why my standard for what counts as a real outcome is higher than most. The story is on the next page.
Engagement
A · Advisor
Quarterly engagements with founders, CIOs and CDAOs. Strategy review, hiring rubrics, programme audits, and decision support on bets above $250k.
B · Operator
Three to six month embeds where I run the function, hire the team, ship the first three production systems, and hand it back with a working operating cadence.
C · Builder
Project work delivered through Solution Cabin. Document intelligence, predictive risk, agent systems, modern data platforms. Production code, not slideware.