AI Readiness Assessment
Know what to
build first.
A one-to-two-week review of your infrastructure, data and AI opportunities, ending in prioritised use cases and a practical delivery plan.
What we deliver
One to two weeks.
A plan you can act on.
Find out what is feasible, what has to change first and where the first budget should go.
Across infrastructure, data and AI. The usual first step before a build.AI readiness review
Six dimensions. One plan.
- DataAvailability and quality01
- AnalyticsHow your teams use information02
- AI adoptionCurrent use cases and opportunities03
- GovernanceOwnership, access and risk04
- InfrastructureGPUs, platforms and delivery capability05
- SponsorshipPeople, priorities and funding06
What you take away
- 01
A scored view of readiness
Data, platforms, people and governance, scored on evidence.
- 02
Use cases worth pursuing
Ranked by business value and feasibility.
- 03
A practical delivery plan
A target architecture and the order to build in.
- 04
A summary for decision-makers
A short recommendation for leadership, finance and legal.
Across your technology landscape
We assess your existing environment before recommending what comes next.
How we work
One to two weeks
to a clear decision.
A focused review, with decisions and outputs at each stage.
- 01 / Understand
Agree on the goal.
Business context and the decisions ahead.
- 02 / Review
Examine the evidence.
Data, platforms, teams and governance.
- 03 / Prioritise
Compare the opportunities.
Business value, feasibility and delivery risk.
- 04 / Plan
Define the next steps.
A target architecture and the order to build in.
From engineering to impact
The value,
in practice.
A closer look at a related client engagement.
Model-ready data, right after close.
A global consumer goods company waiting weeks after each quarter close for model-ready marketing data.
Your next step
Find the right
first build.
Forty-five minutes on your workload, environment and constraints. You leave with a proposed first step.

