Most organisations we meet are not short of AI ideas. They are short of a way to tell which ideas are real. Somebody has a list - predictive maintenance, a document assistant, quality inspection from photographs - and every vendor who sees it says yes to all of it.
We say no to some of it, and we say it with a measurement. Looking for an AI strategy? This is the version of one that starts from what your data can actually support.
Two ways in
Readiness Scan
€4,950 excl. VAT. Fixed price, typically two to four weeks. One workshop day with the people who own the decisions, a structured review of the data and systems you already have, and a scored, prioritised list of up to eight candidate use cases - with the ones that will not work marked as such, and why. Nothing runs on your data yet; this is the honest, fast version. Ends in a written report and a one-hour readout.
Feasibility Assessment
€24,500 excl. VAT. Fixed price, typically eight to twelve weeks. The measured version. We take the two or three most promising candidates and run real baselines on your actual data: what accuracy is achievable with what uncertainty, where the data is not good enough yet, roughly what deploying it would look like and cost to run. You get numbers, not a slide - and a build outline you could hand to any supplier.
The scan tells you where to look. The assessment tells you what is there. Most clients start with the scan, partly because its data review is also the check that makes a fixed price for the assessment possible; some already know which question matters and go straight to the measurement.
Timelines start once the data and access are in place, not at signature. If the data turns out not to support the question, that is written up as a finding - what is missing, how much would be enough - rather than left as a stalled project.
What you get
- 1
Decision-maker workshop
A day with the people who will sign off. What decisions would a model actually change, what does being wrong cost, and what do you already measure?
- 2
Data and systems review
What exists, where it lives, how clean it is, who owns it. Most infeasibility is discovered here, before any modelling.
- 3
Scored shortlist
Each candidate rated on feasibility, data readiness, value and risk - including the ones we recommend dropping, with the reason.
- 4
Baselines on your data (assessment tier)
Simple, honest models on the top candidates. Achievable accuracy, calibration, what is missing.
- 5
Readout and roadmap
Presented to the same people who were in the workshop. A prioritised plan you can defend, and what it would take to start.
Not included: picking vendors or tools for you, extracting or labelling your data, and building the solution. If the answer is build, we quote that separately - and you are free to take the plan elsewhere. How your data is handled during the work is your choice at intake; the three levels are set out with the other assessments.
Who this is for
Leadership who need to decide where AI belongs before committing a budget. R&D groups with more ideas than capacity. Anyone who has been told "AI can do that" and wants a second opinion from people who build the models rather than sell the software.
It works equally well as a first engagement with us or as an independent check on a plan someone else proposed.