Engineering depth! Finance fluency!
One practice.
AI Financial Management was built at the intersection of AI, Cloud architecture and finance — not a pivot from one toward the other.
Overages are an incentive problem, not an engineering failure.
Engineers provision for velocity. Finance tracks line items quarterly. Neither group has the full picture — and the bill lands three months after the decisions that caused it.
We exist to close that gap: making every cloud resource traceable to a decision, a team, and a dollar amount.
FinOps for cloud and AI. Nothing else.
Dual-domain practice
AI spend scope
Optimization, not reduction
Founded by practitioners who held cloud architecture and financial planning roles — not one then the other. The translation layer is structural, not learned on the job.
Our scope covers compute, storage, network egress, and AI inference costs across major cloud providers. We account for the full bill — including the GPU charges showing up now.
We do not cut engineering capacity. We make spend intentional — connecting every resource allocation to a business decision so the next bill is a choice, not a surprise.
If your AI bill is surprising you, the gap between your engineering team and your finance function is the problem. We close it.