AI strategy “Something with AI” is not a project.

We assess your AI ideas by benefit, data, risk and running costs and tell you which one to test first. Sometimes the answer is: none yet.

Have your AI ideas assessed

Before the pilot

It gets expensive when the wrong problem is chosen.

  • A long list of ideas is not a roadmap

    Every candidate is checked with the same business and technical questions, not by enthusiasm.

  • A demo hides the data effort

    We check access, quality, ownership and retention of the data before a pilot builds on it.

  • A prototype is not a result

    Baseline, target and decision date are fixed before anything is built.

  • No model runs itself

    Approvals, monitoring, escalation and cost ownership belong in the design, not on a later list.

Your toaster doesn’t need AI. Your purchasing might.

We first check whether your project has a benefit, data and an owner. Only then which model.

Have your AI ideas assessed
Chrome toaster with two slices of toast

Self-check

Five questions before you pay for a pilot.

  • Is the problem measurable today?

    Good means: there is a baseline the pilot has to be measured against.

  • Is the data accessible and reliable?

    Good means: access, legal basis and ownership of the data are settled.

  • Who owns the outcome?

    Good means: one person is responsible for the operational result, not a committee.

  • Can someone review the exceptions?

    Good means: there is a way for people to look at uncertain cases during the pilot.

  • When is the decision made?

    Good means: date and criteria for continuing or stopping are agreed.

Three or more questions answered “no”? Then work on the foundation pays off first, not the pilot.

What you get

The result is a decision. Not another strategy slide.

  • Comparison of ideas

    Benefit, feasibility and risk for all candidates by the same criteria.

  • Gaps in the foundation

    What is missing in data, systems, ownership and control.

  • Pilot scope

    Scope, baseline, target, review path and criteria for continuing or stopping.

  • Cost frame

    Assumptions for build and operation, not just model fees.

  • Sequence

    Which steps who takes next, and which decision is made when.

Implementation is not included. It is a separate decision once a case proves viable.

Practical questions

Before we start.

Do we need to have chosen an AI platform already?
No. The platform follows once workflow, data needs and operational limits are understood.
Can you assess a running pilot?
Yes. We check baseline, measured result, data dependencies, cost and controls before you decide on a rollout.
Is implementation included?
No. The assessment delivers the basis for a decision and the pilot scope. Implementation only happens if the case holds up, and is commissioned separately.
Who should take part?
Usually the person who owns the process, a technical lead, someone for data or security and whoever approves the budget.

Bring your list of ideas. We will cross things off together.

Have your AI ideas assessed