AI Cost Attribution
AI cost attribution assigns every model call's token spend to the user, team, project, or feature that triggered it.
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AI cost attribution is the practice of tagging every LLM request with the dimensions finance and platform teams care about — user, team, project, session, feature, and cost center — so the token spend from that request can be traced back to an owner. Without attribution, an AI provider bill is a single opaque number; with it, that number becomes an itemized breakdown.
Behest captures model, token counts, and cost on every completion and records the attribution dimensions alongside it. Because the data is collected in the request path rather than reconstructed from logs after the fact, attribution is accurate in real time instead of estimated at month-end.
What attribution unlocks
Accurate attribution is the foundation for everything downstream in AI Token FinOps: chargeback and showback to the teams that incurred the cost, per-project budgets and forecasts, and clean unit economics for products that resell AI. It answers the first question every CFO asks about AI spend — "who is actually using this, and for what?"
Frequently asked questions
How is Behest different from tracking AI spend in spreadsheets or the provider bill?
Spreadsheets and the monthly provider invoice tell you what you already spent, in aggregate, after the money is gone. Behest is real-time AI Token FinOps: every model call is attributed to a user, project, and session as it happens, and hard budgets block overruns before they reach the invoice. You move from reconciling AI spend to controlling it.