Strategy
AI strategy and frameworks
Working out where AI genuinely helps your organisation and where it does not, then putting the frameworks and ways of working in place so your teams actually use it rather than politely ignoring it.
Consultancy
Make AI work inside the business you already run.
AI consultancy for organisations that already run on serious systems. Strategy and frameworks your teams will actually use, straight answers on which technology to buy, custom tools built where nothing off the shelf fits, operations that stop eating your team's week, and enablement built around your business rather than a stock course. Work to date spans banking, family offices and recruitment firms, alongside the brands SurgeLab runs.
What the work is
Five things, depending on what you need
Most engagements start with one of these and grow into another. You are not asked to buy all five.
Decisions
Choosing the right technology
Six suppliers, six demos, and every one of them promises the same thing. A straight answer on which one fits, what it truly costs, and what it takes to live with once the sales team has gone.
Building
Custom tools, and a layer over what you have
Building the thing that does not exist off the shelf, and putting an intelligent layer over the systems you already run, so the data and software you have already paid for become something you can simply ask questions of.
Operations
Streamlining operations
Finding the work that quietly eats your team's week, then handing the repeatable parts to AI with a person still deciding anything that counts. This is usually where the hours come back.
Enablement
Enablement built for your business
Not a stock course. Enablement built around your own tools, your own data and the work your teams actually do, from the leadership team down, so the change outlives the engagement. This is usually the difference between AI that gets used and AI that gets quietly abandoned.
What changes
Before, and after
Today
Twenty years of documents, and no way to ask them anything.
After
Ask a question in plain English. Get the answer, with the source it came from.
Today
A database of people that only pays off if someone remembers who is in it.
After
The right match surfaces before anyone goes looking. A human still decides.
Today
You already pay for AI. Almost nobody in the business uses it.
After
The work worth handing over, set up properly, and measured so you know it saved something.
Today
Six suppliers, six demos, and every one of them promises the same thing.
After
A straight answer on which one fits, what it truly costs, and what it takes to live with.
Who this suits
Where it has worked
The pattern is the same in every case: a business with good people, a lot of accumulated information, and no obvious way to get AI into the middle of it without breaking what already works.
Years of documents, correspondence and holdings sitting in places nobody can search properly. The work is making all of it answerable, without any of it leaving where it should be.
A database full of people and roles that only pays off if someone remembers who is in it. The work is matching, drafting and follow-up done in the background, with a human making every decision that counts.
The clearest example. A team of AI specialists with a manager keeping them honest, running marketing for real businesses every week. Built from scratch, and the reason any of this advice is worth taking.
A recent engagement
An advisory engagement with Investec, working with their teams on where AI fits inside the way the bank already operates.
The work streamlined a range of tasks and saved countless hours across the business. Established teams, a great deal of accumulated information, and a need to put AI to work inside it without disturbing what already runs.
Countless hours saved across the business, on work that used to be done by hand.
A range of everyday tasks reshaped around AI, with people still deciding anything that matters.
Who you are dealing with
Twelve years in tech,
then this
Our founder spent more than twelve years in technology at some of the largest companies in the world, running partnerships with the likes of IBM, BT and Vodafone. That work was about getting big organisations to actually adopt something, which turns out to be most of the job here too.
We then built SurgeLab: an AI platform that measures how ChatGPT, Gemini, Perplexity and Claude describe a business, fixes what they get wrong, and runs that business's marketing every week. It is a working product with paying customers, not a slide deck.
The consultancy is the same thinking applied directly to your company instead of through a product. It is deliberately a small number of engagements at a time.
Before you book
Questions
What kind of companies do you work with?
Established businesses that hold a lot of information and want AI working inside it rather than alongside it. So far that has meant banking (including an advisory engagement with Investec), family offices and recruitment, plus the brands the SurgeLab platform runs.
Do we have to replace our existing systems?
No. The work is a layer on top of the CRM, database and documents you already have, so your systems stay where they are and your team keeps working the way it works.
Is this the same as the SurgeLab product?
No. SurgeLab is a subscription platform that runs marketing for small and mid-sized businesses. The consultancy is us working directly with your company, on your systems, and is a separate engagement.
How does an engagement start?
A thirty minute call, then one scoped piece of work priced before it starts. If that first piece pays for itself there is usually an obvious next one, and if it does not, it is a clean place to stop.
Start with a conversation
Thirty minutes, no charge, no deck. Then one scoped piece of work, priced before it starts. Only more if the first one paid for itself.