Token shock and the case for flat-rate inference

Per-token AI pricing is great when you call a model occasionally. It becomes a problem when a multi-agent system reasons in loops, calling models thousands of times per task. That is token shock: a bill nobody forecast.

The industry rule of thumb is simple: above roughly 30% sustained GPU/LPU utilisation, per-minute or flat-rate pricing beats per-token. Agent fleets blow past that threshold quickly.

Citadea Neural sells a dedicated, flat-rate slice. You size it to your throughput, and the bill stops moving. Predictable for engineering, predictable for finance.