Jungle Grid

Jungle Grid executes your AI workloads whether from your CLI, app, or agents across global GPU infrastructure. It automates placement, scaling, and failover, allowing you to run inference requests with balanced routing and strict VRAM-fit checks. You can submit jobs, get estimates, logs, and results, and trigger processes from apps or agents to automate pipelines. The system features inference routing and scheduler logic in one control plane, enabling you to describe the workload, model size, and optimization goal from the CLI. Jungle Grid turns that request into a scored placement decision without requiring manual hardware selection. You can choose cost, speed, or balanced routing behavior, and track job state from the CLI or the portal. Placement decisions consider price, reliability, latency, queue depth, VRAM fit, and thermal state before dispatching requests onto provider-backed capacity, rejecting requests that cannot fit current VRAM.