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AI ConsultantThe tool is the last decision, not the first.
Most AI projects fail on the problem, not the model. We start by finding the work that is repetitive, high-volume and well-recorded - then say whether AI is even the right answer.
How we engage
Honest scoping, including when the answer is no.
You get a recommendation you could hand to another vendor. That is the point.
Use-Case DiscoveryWe look at the work being done, not the technology, and rank where automation would actually pay.
Data Readiness ReviewWhether the data you hold is complete, labelled and accessible enough to build on.
Build, Buy or SkipA straight recommendation per use case, including the ones not worth doing.
Privacy & Data BoundariesWhat can leave your infrastructure, what cannot, and what that rules in or out.
Cost of OwnershipRunning cost modelled up front - inference, hosting and the human review it still needs.
Roadmap & First BuildA sequenced plan starting with the smallest thing that proves the value.
Start with an assessment.
Two weeks, one department. You get a ranked list of candidate use cases with effort and payback against each.