From Pilot to
Production.
Use-case triage, tool selection, governance, and deployment — engineering judgment for companies done experimenting.
The pilot worked in the demo and died in the workflow. AI initiatives fail at the seams — data, permissions, process, and people — not in the model. That's an engineering problem, and it's ours.
Use-case triage
Every AI idea scored for value, feasibility, and risk. Most get killed. The right ones get built.
Architecture & tooling
Model, platform, and integration choices you won't have to unwind in a year.
Governance
Data boundaries, human-in-the-loop gates, and audit trails sized to your risk.
Production deployment
Working systems in the real workflow — adopted, measured, maintained.
Triage
Inventory and score the use-case backlog against value and feasibility.
Prove
Smallest production-shaped pilot that generates real evidence.
Deploy
Integration, training, and rollout into the actual workflow.
Govern
Measurement, guardrails, and a quarterly improvement cadence.
Use-case inventory + scored roadmap.
Pilot to production, scoped by system.
Ongoing AI leadership — see Fractional CAIO.