AI delivery advisory
From AI idea to production, with the decisions made explicitly.
Discuss AI delivery advisoryThe situation
You have AI use cases and pressure to show results, but it is unclear which ones to pursue, what they will cost to run, or how you will know the output can be trusted.
How I help
We qualify the use cases against business value and feasibility, decide the architecture direction and what to buy rather than build, set up evaluation and cost control, and plan the path from proof of concept to production.
What you leave with
- A prioritized shortlist of use cases, with the business-case logic behind each.
- A proof-of-concept-to-production roadmap with owners and decision points.
- An evaluation and guardrail approach: what is validated, how, and by whom.
- A cost model and the levers that control it: model selection, routing and caching.
- A clear list of what not to build.