Qualify the problem.
Before it costs you six months.
Every engagement starts here. Not because it is a commercial entry point — because it is the step that separates AI projects that work from the ones that do not.
What this is
Most companies come to us with one of four situations:
All four start the same way. We qualify the problem first.
What we do in the Diagnostic
Week one — Discovery
Structured workshops at two levels. Practitioners who know the ground truth of how the organisation works. Executives who hold the strategic context and the constraints. We are looking for three things: what is actually true about this organisation, where the long-term objectives and the short-term team incentives are misaligned, and what nobody has said out loud yet.
Week two — Analysis
We assess the technical environment, the data landscape, and the external factors — competition, LLM trajectory, market shifts. We are not looking for where AI is theoretically possible. We are looking for where it is actually executable, given your data, your team, and your risk tolerance.
Week three — Alignment
We present findings to the full team. Not a deck to be filed. A working session designed to surface disagreement, refine priorities, and reach a decision the organisation can act on.
What you leave with
AI Opportunity Audit
Every identified opportunity assessed across three lenses — business impact, technical feasibility, and product fit. Each rated by potential value and execution effort, so the decision on where to focus is clear and defensible.
Prioritised AI Roadmap
The top three to five bets sequenced over twelve months. What to build first and why. What to defer. What to deprioritise. Board-ready. Designed for internal alignment.
Product Brief for the Top Priority
A scoped document for the highest-priority opportunity. Problem definition. Proposed approach. Success metrics. Risks. Data and technical requirements. A first estimate of scope. This is what the Sprint is built from.
The thing we catch that others miss
Before recommending a build, we ask what trust looks like for the people using the system. We ask whether AI is actually the right tool — or whether a more deterministic approach would be faster, more reliable, and easier to maintain. We ask what happens to the data if the answer is no.
These questions are not in most diagnostic frameworks. They are in ours because we have seen what happens when they are skipped.
Pricing
Fixed fee. Agreed before work begins.
A founding client rate is currently available for a small number of early engagements. If you are interested in working together, it is worth getting in touch now.
Common questions
What does an AI diagnostic actually involve?
Three weeks of structured work across two levels of your organisation — practitioners who know the operational ground truth, and executives who hold the strategic context. We run discovery workshops, assess your technical environment and data landscape, analyse external competitive forces, then bring findings back in a full-team alignment session. You leave with an AI Opportunity Audit, a Prioritised AI Roadmap, and a Product Brief for your highest-priority opportunity.
How long does it take to develop an AI strategy?
The Diagnostic runs two to three weeks from kick-off to final alignment session. That timeline is deliberate — long enough to go deep, short enough that decisions do not get deferred. The output is a strategy and roadmap ready for leadership and ready to build from.
How do I know if my company is ready for AI?
Readiness is not binary, and that is exactly what the Diagnostic maps. We assess data quality and availability, technical infrastructure, team capability, and organisational risk tolerance — alongside the business case. Many companies discover they are more ready than they thought in some areas, and less ready in others. The Diagnostic gives you an honest picture before anyone commits budget.
What is the difference between an AI consultant and an AI product partner?
A consultant runs a framework and produces a report. An AI product partner runs discovery — on your organisation itself. We ask what trust looks like for the people using the system. We surface misalignments between long-term objectives and short-term team incentives. We tell you when AI is not the right answer. And we stay through implementation rather than handing over a deck.
How much does an AI strategy engagement cost?
The Diagnostic is a fixed fee, agreed before work begins. A founding client rate is currently available for a small number of early engagements. The Sprint is scoped and priced after the Diagnostic. The Partnership runs at £8,000 per month. If you are unsure whether your budget fits, reach out anyway.
We already have an AI project underway. Can we still start with the Diagnostic?
Yes — and this is one of the most common situations we see. A project that has stalled, or delivered technology that nobody adopted, often needs a clear-eyed review before deciding whether to continue, reset, or redirect. The Diagnostic is designed to handle this: we assess what is actually true about the current state, where the problems originated, and what the right path forward looks like.