AI workloads are bursty by nature. A team can spend nothing for a week and then run a thousand parallel jobs in an afternoon. Usage-based pricing makes that affordable, as long as you have the right guardrails.

Pay only while code runs

Codexa bills per second of CPU, GPU and memory actually used. Idle sandboxes that are snapshotted cost only storage, which is a fraction of compute.

Quotas for every team

Set limits on concurrent sandboxes, GPU hours or monthly spend per team or project. When a quota is reached, new work queues instead of failing, and the team owner gets notified.

Budgets and alerts

• Alerts at 50%, 80% and 100% of a monthly budget.

• Daily cost breakdowns by project, endpoint and model.

• Anomaly detection that flags unusual spikes within minutes.

A simple policy to start with

Give every developer a small personal quota for experiments, every production service its own project with a hard budget, and review the top five cost drivers once a week. Most teams cut spend by 20 to 30 percent in the first month.