Know your AI gross margin per customer. Forecast next quarter within a stated band.
Four situations put AI spend on the CFO's desk: inference as cost of goods sold, forecast and accrual, commitment burn-down, and audit-grade chargeback. Tokenomy answers each from the metered ledger, with assumptions visible and the price record dated underneath.
Last updated . Model pricing is refreshed twice daily.
Inference is COGS
Contribution margin per account, per feature and per plan — ranked worst-first, so accounts priced below inference cost surface before renewal rather than after.
Forecast and accrual
Usage-driven spend is hard to budget and harder to accrue. Forecasts carry an explicit confidence band, month-to-date accrual comes with its method attached, and variance history shows whether the band earns its credibility.
Commit burn-down
Enter Azure, AWS or Anthropic commitment terms once. Track burn against required pace, see the projected exhaustion or shortfall date, and the dollars at risk if nothing changes.
Audit-grade chargeback
Allocation to business units with method, assumptions and source records attached to every line — exportable, reproducible and dated, so last quarter's number can be regenerated this quarter.
Metered, reconciled or modeled
Every figure carries its provenance. Nothing is presented as measured that was not measured, and no savings percentage appears on the finance surface at all.