A structured diagnostic across your data, knowledge, AI capability, and governance. In 4–6 weeks, you get a clear picture of what's working, what's broken, and what to do first.
Book a diagnostic callMost organisations have data teams, dashboards, and a couple of AI pilots. But they also have a persistent feeling that they're not getting the return. Decisions still rely on gut. Teams duplicate work. AI projects die after the demo.
The issue is rarely a lack of data or tools — it's a lack of clarity about where the real bottlenecks are. Without that clarity, every investment is a gamble.
Data lives in silos — every team has a different "version of the truth" and nobody trusts the numbers.
Successful proof-of-concepts stuck in a loop — the organisation can't operationalise them.
IT builds capability nobody asked for. Business asks questions nobody can answer. Both frustrated.
Board mandate to accelerate AI, but no clarity on where to start or what to prioritise.
Tangible outputs — not a deck that gathers dust. Each deliverable feeds directly into your next decision.
Visual mapping of how data, knowledge, and decisions flow through your organisation — and where the fractures are.
Assessment across six dimensions: AI readiness, governance, data quality, flows, landscape, and literacy. Benchmarked against industry peers.
Specific gaps between current state and target capability — with clear causal chains showing why certain initiatives have stalled.
Prioritised action plan with quick wins (0–3 months) and strategic bets (3–12 months), sequenced by impact and dependencies.
Board-ready presentation synthesising findings, risks, and recommendations. Designed to create alignment and unlock budget.
If you decide to go further: a scoped proposal for the next phase — typically a Data & AI Strategy, operating model redesign, or platform build.
Structured and efficient — designed to minimise disruption to your teams while maximising depth of insight.
Stakeholder interviews, landscape mapping, define assessment boundaries and success criteria.
Six-layer diagnostic: AI readiness, governance, quality, flows, landscape, and literacy. Interviews, surveys, system reviews.
Pattern analysis, maturity scoring, gap identification. Build the prioritised roadmap and executive readout.
Executive presentation. Workshop with leadership to align on priorities. Handover of all deliverables.
Needs to build the business case for data investment — with evidence, not assumptions.
Facing pressure to "do AI" but needs to understand the organisational gaps before committing budget.
Has a team in place but can't get traction. Needs an independent assessment of what's really blocking progress.
Responsible for the roadmap but needs a structured diagnostic before committing to a multi-year programme.
30 minutes. No pitch deck. No obligation.