Token Billing Architecture for AI Companies
How to meter LLM token consumption in real-time and bill customers accurately without losing money on inference costs.
Token billing is deceptively hard. Inference costs fluctuate with model choice, prompt caching, and batching — so your customer-facing meter must be both accurate and explainable.
Report usage the moment a request completes. Attach a stable customer and agent identifier so you can attribute cost and enforce per-agent spend caps before the next request runs.
Prepaid credits smooth cash flow and prevent abuse. A wallet with burn-down and expiry rules means you are never left holding uncollected inference spend.
Orvlin meters tokens in-request and enforces caps in under 10ms, so you can offer generous limits without risking overdraft.