FinOps advisory
Cloud spend isn't a utility bill. It's an investment.
We help growing companies govern cloud, technology and AI spend as an investment. Independent and vendor agnostic: we recommend practices and tools, and sell neither. Tools measure the spend; decisions change it.
Fifteen quick statements to agree or disagree with, ten minutes, an honest read on where you stand. No call required.
Across AWS, Azure, Google Cloud, and hybrid estates.
What we see
The gap between spend and value
None of these are engineering failures. They are what happens when nobody treats the spend as an investment.
The bill is explained, never predicted.
Month end produces a narrative for the variance and no number anyone will commit to in advance. A working forecast turns the cloud line into an input finance can plan against.
Two versions of the same bill.
Engineering reads the invoice by service and account; finance reads it by team and product, and the two never reconcile. Proper allocation gives both sides one number and retires the monthly translation exercise.
The return is taken on faith.
The cost of every workload is tracked in detail while its value rests on a business case written before launch. Unit economics puts a return beside every material line of spend.
Every cloud conversation becomes a cost conversation.
Engineering builds the platform the business runs on, yet the only question that reaches it is why the bill went up. Treat the spend as an investment and the same conversation covers what it earned.
Too big to ignore, too lean to staff.
The spend is large enough to matter, and there is no team to give it. The work falls to engineers between sprints, where it loses to every deadline.
The AI line has no owner.
AI spend is growing inside the cloud bill with no named owner, no budget of its own and no answer on what it returns.
Our services
We build the operating model, not the report.
Designed for organisations large enough that cloud, technology and AI spend matter, and too lean to carry a full FinOps department.
Cloud economics baseline
A ground-up assessment of what the estate costs, what drives that cost and what the business gets back for it, built on business context rather than rate cards alone. It produces a view of cloud spend you can put in front of investors and defend line by line.
FinOps maturity assessment
A structured assessment of how cloud, technology and AI spend is governed today, and a sequenced order of work: what to fix first, what can wait and why.
FinOps strategy & enablement
The decision structure for cloud and AI spend, shaped around how the company already plans and budgets: who owns which call, on what cadence, with which numbers. Designed with the people who will run it, so it holds after we leave.
FinOps for AI
AI spend is still spend.
Model APIs, GPUs and tokens arrive on the same bill as everything else, and they answer to the same standard. The number that matters is cost per outcome, in units a CFO recognises. Cost per token is an engineering number.
Spend visibility & attribution
Every model call, GPU hour and token is traced to the product and team that consumed it, so the AI line reads like any other governed line of spend.
Unit economics & value
Cost per outcome for each AI workload: what a resolved ticket, a generated document or a served recommendation costs, and what it returns.
Investment governance & guardrails
Thresholds and review points that preserve the programme's licence to spend, set to catch drift early rather than ration experimentation.
GPU & token commitment planning
Commitment decisions sized to real usage patterns, with no reseller in the room taking a margin on the advice.
Organisations we've worked with
Across retail, recruitment, education and digital platforms.
The diagnostic
Know where you stand before we ever speak.
Fifteen statements to agree or disagree with, across five dimensions and ten minutes end to end. Answered honestly, it maps where the fundamentals hold and where they fall short. Your lowest dimension is where the work starts.
statements
dimensions
Insights
The thinking behind the practice.
FinOps Stalls When Decision Rights Stop at the Dashboard
FinOps has run on partly informal authority: reputation and a record of good calls. An agent cannot be authorised by any of that, so tacit authority has to become written policy before an autonomous identity acts. A client request queued 16 working days shows the gap before any agent arrives.
Who in the Room Is Paid to Tell You to Stop Cutting?
Your cost tools, and some of your advisers, are paid to push the bill down. Before you let an agent act on your spend, get three answers in writing: what it is optimising for, what must not get worse, and who owns the setting.
The AI FinOps Practitioner Is Starting to Look Like an Economist
You can see more AI consumption than ever, yet 56 per cent of CEOs report no significant financial benefit. Measuring AI expenditure and establishing its economic value are separate disciplines, and most organisations have only built the first.
Your Cheapest AI Model Might Be Your Most Expensive Decision
A lower price per million tokens can hide a higher cost per outcome. Jan Iłowski argues token pricing is meaningless, and he is right. It is the same mistake cloud finance made with the utility bill, and it is worth learning to measure AI by the cost of a decision instead of the price of a token.