Real-Time Billing Explained: How It Works for AI Products

Real-time billing calculates and records charges as usage events arrive, keeping spend, balances, and customer-facing billing state close to current activity rather than waiting for scheduled batch processes. It typically involves metering events, normalizing usage into common units, applying versioned pricing and contract rules, updating balances or accrued charges, and reconciling records against invoices. This approach is especially relevant to AI products, where a single request may trigger multiple model calls, tool uses, retries, and other variable-cost actions, making delayed financial data less useful for budgets and controls. However, real-time billing alone does not prevent overspending, since charges may be recorded only after compute has run; request-time enforcement must instead check entitlements, limits, and balances before protected work begins, often using atomic debits or reservations. Reliable systems must also address concurrent requests, duplicate and late events, historical pricing changes, stale cache data, and replayable audit trails. The text presents Stigg as a usage-runtime layer that can provide synchronous entitlement, credit, and spend checks alongside existing billing platforms, which remain responsible for invoices, payments, tax, and accounting.

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