NetBird has developed the "Mega Mesh," a distributed AI inference infrastructure that links GPU resources across various cloud providers. Using Argo CD, MicroK8s, vLLM, and NetBird's peer-to-peer networking, this system circumvents the limitations of single cloud providers, allowing for a flexible platform to serve large language models. The aim was to demonstrate that multi-cloud networking can be simple and effective, avoiding the complexities of traditional setups that require extensive knowledge of each provider's tools. Initially conceived as a weekend project, the Mega Mesh evolved into a larger initiative when the idea of connecting multiple GPU providers gained traction. The architecture utilizes NetBird's relay system, which intelligently directs traffic based on geography to reduce latency. Each region operates its own vLLM on a MicroK8s cluster, ensuring efficient processing of AI inference requests. As the project progressed, NetBird discovered unexpected interest from AI companies that manage their own infrastructure rather than relying on cloud AI services, highlighting a demand for more control over GPU resources. Connecting infrastructure across multiple cloud providers is typically a logistical challenge, involving intricate VPN configurations and security settings. However, the team found that by focusing on a simpler, WireGuard-level architecture, they could streamline the connectivity process significantly. After working with nine providers, they demonstrated how networking can be remarkably straightforward. NetBird has shared the Mega Mesh setup and provided a guide for others to replicate the system, making private networking more accessible for those looking to leverage multi-cloud environments.