AI READINESS ASSESSMENT
Before you invest in a model, find out what your data will support
Most industrial AI projects fail before any modelling begins, because the data was never going to support the question being asked. Histories are too short, too sparse, or missing the process context that makes them meaningful. Failure modes were never labelled. Measurements exist but nobody recorded what the machine was doing at the time. A readiness assessment answers the uncomfortable question early and cheaply: given what you actually have today, what could realistically be built — and what would need to change first?
What the assessment covers
What data you actually hold
Sources, sampling rates, history depth, gaps and the honest quality of what is already being recorded.
Whether it answers your question
We start from the problem you want solved and work backwards to whether the data could support a model that solves it.
Labelling and ground truth
Most predictive work needs known outcomes to learn from. We assess whether those exist, and what it would take to start capturing them.
The gap to close
A clear statement of what would need to change — extra measurement, better context, more history — and roughly what that involves.
What to do first
A prioritised recommendation, which sometimes concludes that better measurement will deliver more value than any model would this year.
A realistic scope for a pilot
Where a model is viable, we define one problem, one line, and a success criterion measured against a KPI you already track.
How the assessment runs
A conversation about the problem
We start with what you are trying to improve, not with your data. The problem determines what the data needs to be.
A review of what exists
We look at the actual data — sources, structure, history and gaps — rather than at a description of it.
A written, honest answer
You get a short report: what is viable now, what is not, what would need to change, and what we would recommend doing first.
What it costs, and what you get
The assessment is a short, fixed-scope engagement producing a written report you own, whatever you decide to do next. It is deliberately independent of any commitment to build: if the honest answer is that your plant is not ready for AI, that is a useful and inexpensive thing to learn now rather than after a failed pilot.
FIND OUT WHERE YOU ACTUALLY STAND
Tell us what you want to improve and what data you have. We will give you a straight answer — including if the answer is "not yet".