Multi-cloud Capacity Management (MCM) is an innovative orchestration layer designed to unify GPU resources across multiple cloud providers and regions into a single elastic pool, optimizing for high uptime, reliability, and low latency. MCM transforms traditionally siloed compute environments by treating disparate clusters and regions as a globally fungible resource pool, enabling seamless autoscaling and failover while mitigating single points of failure. Built over six months by an infrastructure team, MCM leverages Kubernetes for a global, self-healing scheduling system that adapts to real-time capacity needs, ensuring the consistent performance of AI models across different clouds. By forming partnerships with over 10 cloud providers, MCM offers virtually unlimited scalability and capacity, making it an essential tool for enterprises seeking to manage complex, high-demand workloads without the operational overhead of manual resource allocation. While MCM sets a new standard for AI infrastructure, its complexity and resource requirements suggest that similar solutions should be pursued by inference providers rather than being developed in-house by individual companies.