Beyond financial services
Most of our work is in regulated finance, but we do also work with a number of sectors that face similar challenges – broadly, where a decision is expensive to undo, and where the value of the business rests on something a machine shouldn’t be left to decide on its own.
SECTORLuxury goods and premium drinks
We work with several whisky brands, where filling a cask this year means finding out whether you were right in eighteen. It is the most literal version of a decision you cannot unmake, and it makes every assumption in a forecast a commitment rather than an estimate.
The value of these brands also rests on provenance, craft and restraint, which are the first qualities automation erodes if nobody has decided where it is not allowed to go. That decision is the work.
Where automation is safe, and where it is not. Separating the operational load nobody is paying for from the craft and provenance they are.
Long-cycle stock and inventory judgement. Reaching buyers directly without cheapening what they are buying into.
Marketing and content operations inside strict codes. Alcohol advertising rules, age statements and geographical designations apply to AI-generated material exactly as they apply to everything else.
SECTORLife sciences
Where the evidence has to survive an inspection years later
In Life Sciences, validated systems, traceable evidence and documented human oversight are conditions of operating. A decision has to be defensible to an inspector long after the people who made it have moved on.
Evidence and documentation load. Designing systems which let scientific and clinical experts invest their time in interpreting the evidence rather than assembling and formatting it.
Validated by design. When an inspector asks why a system behaved the way it did, the answer has to come from detailed requirements and process documentation, not get reconstructed on the spot.
Where human oversight must stay. We help you decide where oversight must remain, based on the consequences when something goes wrong, and how easily it can be undone.
SECTOREarly-stage ventures and research commercialisation
Designing the business before the legacy exists
Knowing what your AI-powered startup solves, and for who, is the key difference between a good technology and a great business. We work with the University of Edinburgh's AI Accelerator, helping founders do the thinking most startups skip.
We help them ask the right questions before there’s any process debt to work around.
Strategic foresight. Understanding where your customers and industry are heading so you can design an informed business strategy, before early product decisions harden into constraints.
Business model design. Deciding where AI actually changes the unit economics, based on evidence from delivery rather than founder assumptions.
Implementing AI in a small team. Helping your team select the right platform, design a data estate and implement a governance function that will stand you in good stead for future growth.
Defensibility. We guide you to a clear picture of what your venture knows that a competitor with the same models can’t – a question early-stage AI businesses risk answering far too late.
The problems we solve for regulated banks aren't unique to regulated banks. Any organisation making decisions that matter – to a customer, an employee, a market – needs the same discipline: pause, consider, then act. That's not a compliance requirement. It's just good design.
“
Jamie Spratt, Principal Consultant
