AI Strategy and Advisory
Know what AI is worth building. Before you invest.
The decision to build the wrong thing is the one that costs the most.
Our Approach
We won't recommend a build until we know whether it should be built.
10+ years as one of Databricks' most experienced partners in Europe taught us something blunt: the next wave of AI success will come from organisations that get the foundations right, meaning modern infrastructure, robust pipelines, and capable internal teams.
Grounded in delivery
Every recommendation comes from teams who have built and governed the systems they are recommending, on the platform they are recommending them for. When we say a use case is feasible in one quarter, that estimate comes from comparable delivery rather than from a benchmark in a vendor deck.
Structured to produce a decision
Engagements are short and deliberately constrained. The output is decision-ready: a ranked list, a cost model, and a sequence, in a form you can present to leadership without translating it first.
Honest about what not to build
The most valuable output of a strategy engagement is often the initiative you stop. We will tell you when a use case your organisation is attached to is not the right starting point, and we will show you the evidence.
From AI opportunities to an actionable plan.
Half-day to multi-day sessions that bring your business stakeholders and technical teams into the same room, often for the first time on this topic. We facilitate structured discovery that surfaces where AI could plausibly help, what is actually blocking your teams today, and what data you have to work with. The output is not a wishlist. It is a shared, validated understanding across the people who will fund the work and the people who will build it.
Most organisations either overestimate or underestimate where AI can help, usually because nobody has mapped it against what their data actually supports. We run a structured inventory across your business functions, cross-referencing operational pain points against data availability, system maturity, and regulatory constraints, so the use cases on your list are real candidates rather than aspirational ones.
Not every valid use case deserves to be built first. We apply a structured scoring framework across business impact, technical feasibility, data readiness, and implementation risk, then rank the list to surface the opportunities that combine high value with achievable delivery. This is where internal AI strategy efforts usually break down, because enthusiasm replaces rigour. We keep the rigour.
Strategy without sequencing is just a list. We build phased roadmaps that pair early, lower-risk wins, which build organisational confidence and internal AI literacy, with the larger, higher-value initiatives that take longer to land. The goal is momentum: a programme that shows value in the first quarter, not the third year.
Weeks, not quarters. And it ends with a decision.
Common questions before getting in touch.
How do you identify which AI use cases are worth investing in?
We evaluate potential use cases against four key factors: business impact, technical feasibility, data readiness, and implementation risk. Through stakeholder workshops, technical assessments, and structured scoring, we identify opportunities that are both valuable and achievable. The result is a prioritised list backed by evidence, not assumptions or enthusiasm for the latest technology.
How long does an AI Strategy and Advisory engagement take?
Our strategy engagements are designed to take weeks, not quarters. The exact timeline depends on your organisation's size, the number of stakeholders involved, and how much groundwork has already been completed. We define the scope upfront and keep the process focused on delivering actionable recommendations without unnecessary delays.
Do you only recommend AI solutions built on Databricks?
Databricks is our core area of expertise, and our technical recommendations are grounded in what can realistically be delivered on the platform. However, we don't assume every business problem needs AI in the first place. Our priority is helping you make the right investment decision.
Are we expected to work with Datapao on implementation afterwards?
No. Our AI Strategy and Advisory engagements are standalone services, with no obligation to continue into implementation. You'll leave with a clear, actionable roadmap your team can use independently. If you decide to move forward with Datapao, we can also support the next steps, from building production-ready AI applications to establishing the governance and infrastructure needed to run them reliably.
