Services01

Needs assessments

A clear-eyed look at where machine learning or agentic systems can actually move one of your business metrics — and where they can’t. You get an honest map of the opportunities, the data they’d need, and what it costs to be wrong, before anyone commits to building anything.

Deliverables

What you get

  1. 01

    Opportunity map

    Every plausible use case scored against the business metric it would actually move — revenue, cost, risk, or time — ranked by impact and effort.

  2. 02

    Data-readiness read

    An honest inventory of the data each opportunity would need, what you already have, what's missing, and what filling the gaps would cost.

  3. 03

    Cost of being wrong

    For the top candidates: what a bad model does to your customers or your team, and whether the failure modes are survivable.

  4. 04

    Buy, build, or skip

    A plain recommendation per opportunity — buy a vendor product, build it in-house, or skip it — with the reasoning written down so your team can argue with it.

  5. 05

    First-step plan

    The smallest useful thing to do next, with the decision it answers and the evidence that would change it.

Shape

How it runs

Two to four weeks, not quarters. Week one is conversations and data access: the decision you’re stuck on, the team that would own the outcome, and a look at what you actually have in the warehouse. The rest is analysis and writing — the output is a document your leadership can read in twenty minutes and your engineers can argue with for a month.

Fit

Who it’s for

Teams with real AI curiosity and real data, but no clear picture of where the leverage is — or a leadership team that needs one trusted voice to separate the plausible from the theater before the budget gets spent.

Boundaries

What’s explicitly not included

  • Model training or production builds — this is diagnosis, not construction.
  • Vendor selection run as a paid referral. If a vendor product fits, you'll hear it; there's no commission riding on the answer.
  • Financial, investment, legal, or tax advice — this is technical advisory only.

Begin

Tell us what you’re trying to build.

A short note about your team, your data, and the decision you’re stuck on is the best way to start. You’ll hear from the principal, not a sales team.

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