We work with owners and VC-backed CEOs to put AI where it earns a measurable return, cost it honestly, and check every number before it drives a decision. We operate at board level and we get into the detail. AI drafts. Code calculates. A person signs off.
CEOs who reach out to us aren't looking for a report. They're at a moment — an AI bill that keeps growing, a board asking hard questions, a finance function that isn't keeping pace — and they need someone who can lead, not just advise.
"Everyone is talking about AI. I tried ChatGPT. I'm not sure how to move from experimenting to actually improving our business."
We don't hand you a list of 100 AI tools and leave you to figure it out. We start with your specific business outcome — revenue, efficiency, a one-time project — and identify the AI approach that delivers it. We apply AI where it creates the most value, building on what your business already has rather than recommending a wholesale replacement of systems that are working. We scope everything to your actual budget and team — not what a large enterprise would spend. And we're honest: what works well today will work even better in the months ahead.
"We have AI subscriptions, usage charges and an AI project or two. I can't tell you what any of it is actually returning."
AI costs are easy to start and hard to see. Subscriptions multiply, usage-based charges scale quietly, and AI projects rarely get a proper business case. We put a number on each AI cost, test it against the time, revenue or risk it's meant to address, and tell you plainly what to keep, fix, or stop. Example: a $3,000-a-month tool earns its place if it saves more than about 25 staff hours a month at a $120 loaded rate — and its outputs hold up when checked.
"My directors and investors keep asking what we're doing with AI and what it's costing us. I don't have a clear answer."
Boards and investors want more than enthusiasm. They want to know where AI is used, what it costs, what it returns, and who checks its work. We build that picture with you and put it in a form a board can act on — and keep it current, so the next question has an answer ready.
"We're hitting targets but I don't have clear visibility into where our money is going or whether we can sustain this."
You need a senior financial leader — not a bookkeeper, not a software tool — who can build the reporting infrastructure, cash flow discipline, and strategic oversight your business needs at this stage. We embed alongside your team to build this with you, not hand you a report.
"Growth has slowed and our cost base hasn't adjusted. I know something needs to change but I'm not sure where to start."
When revenue softens and costs keep climbing, the instinct is to cut — but cutting the wrong things makes the problem worse. We identify where the real pressure is coming from, separate structural cost issues from cyclical ones, and help you make decisions that protect margin without damaging the business you've built.
"We have an audit coming up and I'm not confident our records and processes will hold up under scrutiny."
Whether it's an external financial statement audit, a bank covenant review, a vendor or customer due diligence request, or an internal controls assessment — the time to prepare is before the review arrives. We work with your team to organise documentation, tighten controls, and present a clear, well-supported position from the start.
Each one is built around a question a CEO actually needs answered — where AI can improve how you already work, what it's costing, and whether it's delivering. Every engagement has a defined scope and a clear deliverable.
"Is this idea worth doing — and did it actually work?"
You receive: one use case taken from idea to measured result.
"What is our AI spend returning — and where should it go next?"
You receive: a prioritised plan your leadership team or board can act on.
"Is our AI still earning its keep?"
You receive: a standing answer to the AI question, kept current.
Defined projects are usually priced as a fixed fee; ongoing work can be fixed or hourly. Either way, you'll know the scope and the cost before any work starts.
We don't know everything, and we don't pretend to. When a question needs deeper expertise — in AI security or another specialist area — we bring in trusted specialists as needed.
Some engagements are intensive at the front and then shift to ongoing oversight. Others are defined projects with a clear end. We don't have one way of working — we have one standard: that the work we do is the right work for your situation, done at the right level.
We start with a focused conversation about what's going on. This isn't a free consulting session — it's a mutual assessment of fit. Good advice requires context, and real context takes an engagement. What we can do upfront is tell you clearly whether we're the right partner for what you need.
Before anything starts, we agree on what the work looks like, what we're trying to achieve, and how we'll know we're making progress. We also agree how it's priced — a fixed fee or hourly, whichever suits the work — openly, before you commit to anything.
We engage at the level the situation requires. Sometimes that means being in the model. More often it means directing and upskilling your existing finance team — so they grow through the engagement, not around it. You're not paying for us to do work a junior person could do. You're paying for the judgment that makes the work matter.
Some clients want heavy upfront engagement followed by lighter ongoing oversight. Others need a defined project with a clean end date. We hold ourselves to the quality of advice we give and the decisions we help you make — and we're transparent about what we can and can't control. The engagement ends when it should, not when it's convenient for us.
Mid-sized businesses don't have time for AI experiments. We work with you to identify where AI creates the most value, apply it with a defined business outcome — revenue, efficiency, or a specific project — and do it in a way that builds on what you already have, not what an enterprise with a nine-figure IT budget would do.
You've heard the noise. Maybe you've tried ChatGPT. You're not sure what's real, what's risky, or where to begin safely.
You've started using AI tools here and there. The results are inconsistent. You're not sure how to systematise what's working.
AI is already part of your operations. You're ready to go deeper — specific revenue-generating or cost-reducing applications with measurable ROI.
Non-negotiable standards we bring to every AI engagement — because your data, your clients, and your reputation are on the line.
Every AI initiative starts with a specific business outcome — not a technology experiment. If we can't show what it will cost and what it should return, we won't recommend it.
Your data stays yours. We establish data classification, access controls, and privacy safeguards before any AI tool touches your business information.
AI drafts. Code calculates. A person signs off. Every number an AI produces is recomputed from the source before it reaches a decision-maker.
We work with your actual budget and team, not an enterprise IT department's. The right AI tool is often not the most powerful one — it's the one that does the job at a cost the result justifies. We build on what you have and add where it matters.
We don't form our AI views from vendor marketing or conference keynotes. We actively follow the work of leading hands-on AI practitioners and researchers, and we apply what's genuinely proven — filtered through the judgment of someone who has sat in the CFO chair. Our clients get AI thinking that is current, field-tested, and calibrated to what a mid-sized business can realistically deploy and benefit from. Not recycled theory. Not enterprise case studies that don't translate. What works, at your scale.
Last reviewed: September 2026
Recent thinking on how finance teams can use AI well — and how to know when its numbers can be trusted.
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