One diagnosis, then the build it points to. Engagements start small and contained, and expand only into work the diagnosis has already justified in dollars.
1Diagnosis
Diagnosis is a contained, fixed-scope engagement, usually a few weeks. I review what you already have, interview the people who would own the work, and map where AI can move revenue, margin, risk, or working capital. Each opportunity is sized in dollars and sequenced Now, Next, Later. You end with a ranked value thesis and a build plan attached to it, not a deck of possibilities.
2Solution
Solution is where the plan becomes a working capability. I stand up the prioritized initiatives inside your business: the data foundation, the models, the retrieval and agent builds, the tooling and MLOps, and the governance to run them safely. An engineering team builds under my direction. The architecture, the sequencing, the regulated-deployment judgment, and the accountability for the outcome stay with me. When I leave, your team can run what we built.
For companies that need senior AI direction without a full-time hire. I set the strategy, run the priorities, and stand up the capability, as a fractional Chief AI Officer or head of AI.
For funds that want AI to show up in portfolio value, not just in board conversation. I diagnose where AI moves an operating company's P&L, then lead the build that captures it. Sector-agnostic across the portfolio.
Every engagement is held against five pillars.
I hold engagements against these five because I have owned each one at scale, as the engineer building it and as the executive answerable for it.
I built and shipped AI under FDA, HIPAA, GDPR, and bank decisioning regulation, where a wrong output is a recall or a fine, not a bug ticket. That discipline travels. Whether or not your industry is regulated, the same rigor is what gets AI into production and keeps it there.