What is Metered Utilization? Measuring AI Token Usage

Metered utilization is the measurement layer that records customer consumption by feature and time period, supplying usage data for credits, limits, reporting, rating, and invoicing without itself determining charges. AI products may meter tokens, inference units, API calls, agent actions, compute time, or customer-facing credits, but multi-model workflows and concurrent requests complicate attribution, event identity, and aggregation. Reliable metering requires durable event ingestion, stable IDs for deduplication, normalized data, aggregation, raw-event storage, append-only credit ledgers, and reconciliation to address missing, duplicate, late, or incorrectly windowed events. It differs from metered billing and pricing models by focusing solely on measuring consumption. Runtime enforcement is a separate request-time function that uses current usage, entitlements, credits, and limits to allow or deny further activity, requiring atomic debits, idempotency, tenant isolation, and policies for hard or soft limits. Stigg is presented as a platform that combines metering, credit balances, entitlements, and low-latency runtime checks while integrating settled usage with external billing systems.

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