Most AI initiatives fail before a line of code is written — wrong use case, no data readiness, no executive alignment. We run a structured advisory engagement that ends with a scored, sequenced roadmap your whole organisation can commit to.
Structured discovery, honest scoring, and a business case leadership can actually approve.
Sessions with every relevant department to surface real bottlenecks, not the loudest opinion in the room.
Every candidate initiative scored on business value, data readiness, and delivery risk — on one page.
A dated plan with named owners and phases, not an open-ended “innovation backlog.”
Cost ranges benchmarked against comparable delivered work, with expected return per initiative.
A leadership-facing deck you can present as-is, not a technical document nobody outside IT reads.
The evaluation topology and a real scoring snippet — not a black-box consulting matrix.
// elhaa Opportunity Scoring Model const score = scoreUseCase({ businessValue: 8, // 1-10, stakeholder-rated dataReadiness: 6, // 1-10, audited deliveryRisk: 3, // 1-10, lower is safer weighting: 'balanced' }); // -> { rank: 2, tier: 'quarter-one', confidence: 0.82 }
Leadership had approved an “AI budget” with no shortlist — three departments were independently evaluating vendors for overlapping use cases, and none had validated data readiness.
We ran discovery across six departments, scored eleven candidate use cases, and sequenced the top three into a roadmap with named owners and quarterly milestones — killing two of the original three department proposals as lower-value.
*Illustrative example based on a representative engagement.
Structured sessions with stakeholders to surface real bottlenecks, not assumed ones.
Every candidate use case scored on business value, data readiness, and delivery risk.
A sequenced 12-month plan with named owners, budget ranges, and expected ROI per initiative.
Roadmap handed to delivery teams (ours or yours) with clear success criteria per phase.
Every candidate initiative rated on value, feasibility, and data readiness.
Leadership and technical teams agree the roadmap before a line of code is written.
Cost ranges benchmarked against comparable delivered engagements, not guesses.
How quickly the top-ranked use case can move into a Diagnose Sprint.
We're engineers first — every use case on the roadmap is scored against what we know is actually buildable, not just what sounds good in a slide. Many roadmaps we write convert directly into a Diagnose Sprint with us or another vendor.
Typically 2–4 weeks depending on organisation size and how many stakeholders need to be interviewed.
No. The roadmap and business case are yours to take anywhere. Many clients do continue with us since we already understand the context, but there's no lock-in.
That's common, and exactly what the data-readiness scoring is for — it flags which use cases need a Data Engineering engagement first, rather than letting you find out mid-build.
Yes — it's designed to be a living document. Most clients revisit it quarterly, and we're happy to run that review with you.
A 30-minute call. We'll tell you honestly whether this is the right solution — and what it would take.
A short form, then a 30-minute call. We reply within one working day.
We'll be in touch within one working day.