AI Strategy & Readiness
Before anything is built, we work out whether it should be.
The readiness review is a fixed two-week engagement. We map where your data actually lives and what state it is in, trace who makes the decision the system is meant to support, and test each candidate use case against effort, value and risk.
It ends with a scored shortlist — including the ones we think you should drop, and why.
What we do
- Data landscape and quality assessment
- Decision mapping across the process
- Use case scoring and prioritisation
- Risk, governance and residency review
- Cost and effort modelling
- Sequenced delivery roadmap
This is for you if
- You have a list of AI ideas and no way to rank them
- A pilot worked in a notebook and stalled after that
- You need to brief a board on what is realistic
- You are not sure your data can support what is being proposed
What you get
- A scored shortlist of use cases, with the weak ones named
- A sequenced roadmap with dependencies made explicit
- A written view of the data and governance work required first
- A cost and timeline estimate you can put in front of finance
Two weeks is cheap. Nine months building the wrong thing is not.