The engineering side of billing — metering pipelines, idempotency, ledger design, and infrastructure.
AI billing broke the billing stack. You're charging per token, per inference, per GPU millisecond — and your billing system is rounding most of it to zero. Here's the fix.
Idempotency ensures that processing the same event multiple times produces the same result. In billing, this prevents double-charging when events are retried. Implement it with unique event IDs and deduplication at the ingestion layer — every metering event needs an idempotency key.
AI inference generates transactions so small (fractions of a cent) that traditional billing systems round them to zero. Solutions: aggregate into hourly/daily buckets before rating, use high-precision decimal types (not floats), and design your ledger for sub-cent granularity.
Event ingestion (API or streaming), deduplication (idempotency keys), buffering (handle burst traffic), aggregation (time-window rollups), rating (apply pricing rules), and storage (append-only ledger). Each component needs monitoring — silent metering failures are the most expensive bugs in billing.