We help leadership teams pick the few AI bets that move the business, and drop the ones that won't. The advice is costed by the people who would build it, so the plan survives contact with delivery.
Most organisations do not lack AI ideas. They lack a clear view of which ideas are worth the money, which ones their data can support and what it would really take to get one into daily use. Strategy work that ignores delivery tends to produce a deck. We aim to produce decisions.
We have designed and built software for businesses since 2016, and today we build AI agents, models and LLM features that run in production. When we advise, the estimates come from that experience. If a use case looks attractive on paper but would take a year of data work before it could run, we will say so.
We assess four things together. Value: what changes in cost, revenue, risk or service if the use case works. Feasibility: whether your data, systems and skills can support it. Risk: what happens when the AI is wrong, and how that would be controlled. Time to impact: how quickly the business would see a result. The output is a ranked portfolio with the reasoning written down, so you can challenge it and revisit it as things change.
A roadmap is only useful if the first step is clear. For the top opportunities we write business cases, make the build or buy call, and plan the first delivery with you: scope, team, timeline and cost. Whether you build it with us, with your own team or with another partner, you start with a plan that has been tested against delivery.
Every department has an AI wish list. We rank the opportunities by value, feasibility and time to impact so you can say yes to a few and no to the rest.
We look at why earlier pilots stalled, whether it was data, ownership, security or the use case itself, and what it would take to get one live.
Vendors, platforms and models change monthly. We compare the options against your needs and make the call on evidence, not demos.
When the board asks what the AI plan is, you need an answer with numbers behind it. We help you build that answer.
An honest view of whether your data, platforms and skills can support the use cases you care about, and what to fix first.
Who owns AI, how it is funded and how risk is managed, set up so that teams can move quickly inside clear rules.
We interview leaders and the teams closest to the work, review your data and platforms, and look at what has already been tried.
We build a portfolio of use cases and score each one on value, feasibility, risk and time to impact, with the assumptions written down.
For the top opportunities we estimate cost, benefit and effort, and set out the build or buy decision for each.
You get a plan for the first delivery, with scope, team, timeline and cost agreed with you. If you want us to build it, the same people stay on.
Interviews with leadership and the teams closest to the work, a review of your data and platforms, and a ranked portfolio of use cases with business cases for the top picks. The scope is agreed with you based on what you need to decide.
The people who advise you are the people who build. That means every recommendation is costed against real delivery effort, and the roadmap is one we would be willing to deliver ourselves.
No. The roadmap, business cases and plans are yours to use with your own team or any partner. Many clients do continue with us, because the same people already know the context.
We are independent of AI vendors and model providers. We compare options against your requirements on quality, cost, latency, data residency and lock in, and explain the reasoning behind each call.
That is a common finding and a useful one. We show which use cases your data can support today, which need work first, and what that work would involve.
Tell us what you are trying to fix. A senior member of the team replies within one business day.
Book a discovery call →