Your company runs a customer-facing chat application on Azure AI Foundry that peaks at thousands of concurrent requests per minute during business hours. The team currently uses a standard (pay-as-you-go) deployment of a GPT model but is experiencing throttling (429 errors) and inconsistent latency during peak load. Leadership requires predictable, reserved capacity with stable latency for this high-volume workload. Which deployment approach should you configure?