
Ask a CFO what the company spent on AI last quarter and you will get a number. Ask which product line it belonged to, whether anyone approved it, or what it earned, and the room goes quiet.
FinOpsly was built for that second set of questions.
It is an AI Cost Governance platform. AI does not run in isolation, so FinOpsly does not price it in isolation either. A model call pulls warehouse queries, GPU time and storage behind it, and the engineers building the feature are burning licensed seats the whole time. All of that lands in one cost model, mapped to the company's own structure: owner, team, product, business unit, customer.
What teams use it for:
Pricing a workload before anyone provisions anything. Describe the architecture, get a cost estimate across the stack, and see which assumptions drove it. Compare model options using consumption you have already paid for.
Making chargeback something finance trusts. Hierarchies run nine levels or deeper. Tags get standardized across providers that never agreed on a convention. API keys and resources are labeled in bulk from instructions written in ordinary English. Anything still unowned shows up as a dollar figure.
Holding the line during the month. Budgets by team, project or key. Anomalies flagged with a root cause and sent to the person responsible. Waste that provider consoles do not catch, found by FinOpsly's own detection models. Idle compute parked on schedules the customer approved, and reversible.
Proving the outcome. One chargeback run covering AI, cloud, data and SaaS together. Savings measured against the base-line along with cost-to-serve metrics: cost per active user, per customer served.
Customers have moved attributable spend from 68% to 99% inside 90 days and taken a chargeback cycle from 12.4 days down to under one.
Built for CIOs, CTOs, FinOps practitioners and the finance teams who sign off on the bill.
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