We get whole companies working properly with AI, with numbers your board can trust. Run entirely remotely by the two of us, who hold these exact jobs inside companies today: one with the developers, one with the business.
We also build and run the software for a licensed financial operator: the Manx Credit Union platform, live at mcu.im.
The call costs nothing. The consultation is £2,500 and comes off the programme price. If you don't need us, we say so.
Maybe you haven't started: no licences, no policy, a dozen vendor pitches you can't referee, and a quiet sense that your competitors are moving. Maybe you bought the licences and they sit unused, because nobody senior has said out loud that using them is allowed and expected. Or three developers live in Claude, five have never opened it, and code review has quietly become the bottleneck. Wherever you are on that line, the shape is the same: the technology is ready before the organisation is.
We watch this happen from the inside. Both of us hold staff roles that were invented for exactly this problem: companies that knew AI mattered, had no idea who should own it, and created the job on the spot when they found someone who could. This consultancy is that job, offered as an engagement instead of a hire.
That last number is the whole business case. Adoption is the easy half. Deciding what the freed capacity is for, and giving the team the confidence to use it on platform and infrastructure work, is the half that pays for itself.
Four hours with both of us, senior level, on your architecture, your team and what you actually want: the workflow, the tooling, who uses what and where the hours go. You leave with a straight recommendation and the business case, costed. Start the programme within 90 days and the full £2,500 comes off its price.
Book the free call first →We embed in your Slack two days a week, on one track or both: Corey with the developers, George with the business side. Workshops set the floor; one-to-one sessions on real work, everyone in rotation, raise it. Your sponsor gets a short written note each Friday, everything lands in a private portal your team keeps, and week twelve ends with adoption, cycle-time and capacity figures, plus a plan for the hours you got back.
Talk about dates →Office hours for the team, a monthly briefing on what changed in the tooling and what to ignore, and a quarterly re-measure so the numbers stay honest as models and prices move.
Available after a programmeThe path in: a free 30-minute call, then the consultation. Because the £2,500 is credited in full when a programme starts within 90 days, teams that go ahead get the diagnosis for nothing; teams that don't still own the recommendation.
AI adoption fails when it stops at the dev team. So the engagement runs as two tracks: Corey lives with your developers, George lives with your operations, and the same Friday note covers both. Yes, that includes the CEO's own week.
One track starts at £30,000; both together at £50,000, because the sponsor, the measurement and the report are shared. Every engagement is quoted once, sized to the team, the tracks and the value at stake: bigger teams carry bigger scopes, and the price scales to match. Either way there is one Friday note and one final report covering everything we touched. And if AI is in your product as well as your process, the assurance harness joins the same quote: everything together from £70,000.
Adoption is half the job. The other half is knowing which ideas are worth building, because the expensive failures are the ones that work beautifully in a demo and die on contact with your real data volume.
The tell: if serving one request gets dearer as your data grows, it's a demo. If the AI cost is paid once per item at ingestion, it's a system. What dazzles across forty documents behaves differently across a hundred thousand.
Cost is the recoverable half. Quality is the other: prompting cannot conjure data the retrieval never found, so months go into better prompts and bigger models when the right document was never in front of the model. That road ends in a worse product, not the same one late.
We triage this in the consultation, on your own list of ideas, before anyone commits a roadmap to one. Verdicts come in three flavours: it scales, it scales with architecture we'll name, or it's theatre and we'll show you the arithmetic. There's a ten-minute test on this site that tells you which problem you have, free, no email wall.
Most of what we find isn't strategic. It's a specialist searching the same library by hand for the fourth time this week, a month-end pack assembled by copying figures between systems, the same two hundred tender questions answered slightly differently every time.
Searching study libraries and regulatory inventories by hand. Pulling structured data out of PDFs. Assembling dossiers from documents that already exist.
Invoice and PO matching, coding and chasing. Month-end packs built by copying figures between systems. Reconciliation.
Tender responses answering the same questions with slight variations. Proposals rebuilt by hand from work you have already done.
Reading inbound forms and email to route them. Data entry between two systems that don't talk. Reports that are copy this into that.
Policy questions answered by whoever has been there longest. Contract review against a checklist. Dates and obligations into a register.
First-response drafting and triage. Turning solved tickets into the documentation that stops them recurring.
We teach the person who owns the work, on their own work, and they keep doing it after we leave. Nothing to buy, nothing to maintain, no dependency on us.
Occasionally no amount of training helps, because the work genuinely needs something built. The new part is that your own people can now build those, and we teach them with the rails on: which tools are safe to self-build, which need engineering, and which shouldn't exist at all.
That last distinction is the one that matters. Letting staff build their own software without it becomes a graveyard of things nobody can maintain, which is how every previous version of this ended. When a tool does graduate into something the company depends on, there's an engineering practice next door: Future Proof Solutions builds and operates a banking platform, so it can build yours. Quoted separately, and only when the answer is genuinely a tool.
AI-assisted development is async by nature. An engagement that happens in your Slack, your repos and your ticket queue teaches the team in the exact medium they'll work in after we leave. It also means every session survives us.
Every engagement gets its own private portal: session recordings and notes, the governance pack, the Friday notes and the final report, all in one place your team signs into. It stays yours, and new starters learn from it years later.
Pairing happens on the sprint board, in rotation, so the sceptics get the same attention as the enthusiasts. Nobody hides on a group call.
Progress, per-person uptake, blockers. Short enough to read, written so the person paying never wonders what happened this week.
An AI usage policy your team will actually follow, a data-handling briefing for the board, and an access agreement covering us before we read a line of your code.
A mid-level developer costs around £60,000 a year. The AI tooling that changes how they work costs around £1,000. Once a team adopts properly, the same roadmap needs fewer hands, or the same hands carry a bigger roadmap. Which of those you choose is a management decision. Our job is to hand you numbers solid enough to make it.
Every engagement ends with usage and adoption data per developer: who uses the tools, on what work, and what happened to their cycle times. The AI spend justifies itself on the same page. Boards fund what they can see.
Want to see the standard we work to? The AI usage policy template from our governance pack is free to copy, no email wall.
Future Proof Consulting is the advisory arm of Future Proof Solutions, the Isle of Man engineering practice behind the Manx Credit Union platform: loans, treasury, audit and a member portal, live in production at mcu.im. When we talk about AI-assisted delivery, we're describing how that system gets built.
Nine years building production financial systems at Backbase, Credit Suisse and UBS, across the UK, Italy, Spain, Japan and Australia, to Associate Director. Built the component library that shipped to every bank and credit-union client at Backbase, then led the Java delivery for the consolidated EMEA wealth platform through the largest banking merger in Swiss history, running its monolith-to-microservices migration single-handed. Designed and built the core banking platform behind an IoMFSA-regulated credit union, live since July 2026, and now delivers product engineering for a regulatory-software firm entirely through agentic workflows.
"The shift that mattered was moving from builder to driver. The agent writes the code; I own the architecture, the judgement and the direction. The trap is becoming a passenger."
Founder and chief executive of Future Proof Solutions, and the delivery lead on the credit union platform: he owned the client relationship end to end, turned what non-technical staff actually needed into workflows and screens across onboarding, KYC, lending, cashier and treasury, and when the incumbent provider withdrew he ran the three-week emergency go-live as single point of accountability. He is also lead developer on a manufacturing ERP under hazardous-goods regulation, where he authored 73% of three years of commits and took a wholly untested system to 639 passing tests in nine weeks. He runs the company too: board proposals, pricing, and the client's all-staff training day.
"AI raises throughput. The senior engineer still owns the judgement."
Both of us hold these exact roles inside other companies right now, which is the only reason we can tell you what actually happens rather than what should.
Product companies and internal software teams with five to thirty developers, in the UK, Ireland, the Isle of Man, or anywhere remote-friendly. Big enough that the capacity question is worth real money; small enough that a decision takes one meeting.
If you have two developers, book a call anyway; it'll be short and probably free. And if you're considerably bigger than that, we don't sell you a transformation: we take one division, prove it on one team, then train your own champions to run it. That shape has its own page. We're two people and we keep the client list short on purpose.
One more shape: AI is already inside your product (a chatbot, an extraction pipeline, a scoring model), and the question has stopped being adoption. It's now who measures it, and what failure rate you chose. That's AI assurance, and it has its own page too.
Thirty minutes, no charge, no deck. Tell us the size of the team and what prompted the question, and we'll reply within one working day with times.
