We need to know why it happened.
Root-cause systems that detect what changed, find what caused it, and recommend what to do.
Each step is fixed in scope and stands on its own. You only move to the next one when the last one has earned it.
I work with your people and your data to turn a vague question into a clear problem, requirements and a solution architecture.
You get: a sharp problem definition, requirements, a solution architecture, and a plan to build it.
I build a working proof of concept on your own data and validate it honestly, so you know whether it works before you invest.
You get: a tested prototype, the evidence behind it, and a clear go or no-go.
I lead delivery as your fractional technical product lead, with specialists from my network or your own team.
You get: a production solution, and a team that understands why it was built this way.
Root-cause systems that detect what changed, find what caused it, and recommend what to do.
Evaluation pipelines that test agents before launch and keep checking them after.
One end-to-end design that data science, engineering, analytics and product can all build against.
Churn and recommendation models tied to the actions your teams can actually take.
A sober look at which of your processes benefit from AI, and which don’t.
The best projects often start with a question that doesn’t fit a category.
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