AI Consulting
A roadmap with the unglamorous parts costed
Strategy work that ends in a slide deck helps nobody. Ours ends in a sequenced backlog, a build-or-buy call per initiative, and an honest view of what your data and team can actually support this year.
Capabilities
What this actually includes
The concrete pieces of work, so you can tell what you are buying rather than inferring it.
Opportunity mapping
Workshops across functions to surface candidate use cases, scored on value, feasibility and data readiness.
Data readiness assessment
An honest audit of whether the data behind each idea exists, is accessible and is good enough to build on.
Build, buy or wait
A recommendation per initiative, including the ones where the right answer is to buy a product or do nothing yet.
Governance and policy
Acceptable-use policy, model risk documentation, review gates and an approval path that does not stall delivery.
Team and operating model
What to hire, what to partner on, and how AI work fits your existing delivery process.
Sequenced roadmap
A quarter-by-quarter plan with dependencies, staffing and cost, written so a CFO can read it.
How we work
The sequence we follow
Discovery
Interviews across business and engineering, plus a direct look at the systems and data involved.
Assess and score
Each candidate scored on value, feasibility, data readiness and risk, using criteria we agree with you up front.
Prove the risky one
A short technical spike on whichever assumption would be most expensive to get wrong.
Sequence and cost
A roadmap with dependencies made explicit and a defensible cost range per initiative.
Hand over or build
Your team runs it, we run it, or we run the first one together and hand it over. Your call, made with real numbers.
Outcomes
What good looks like
Illustrative targets from engagements of this shape. Yours get agreed up front and measured.
0 weeks
typical engagement from kickoff to roadmap
0
initiatives de-risked by a technical spike
0%
of initial candidate ideas cut before build
Toolkit
What we build with
Chosen per engagement against your constraints — never a house stack applied regardless of fit.
Assessment
- Data readiness scorecard
- Feasibility spikes
- Cost modelling
Governance
- Model risk documentation
- Acceptable-use policy
- Review gates
Planning
- Sequenced backlog
- Staffing model
- Build/buy analysis
Enablement
- Team workshops
- Architecture review
- Vendor evaluation
Questions
Things clients ask first
Regularly. Roughly two in five candidate ideas get cut before build in a typical engagement — usually because the data is not there or an off-the-shelf product already does it.
Keep exploring
Related capabilities
Tell us what you are trying to build
A short call with an engineer, not a sales team. If we are not the right fit we will say so and point you somewhere better.