Across the public sector, agencies are investing heavily in compute — standing up CPUs and GPUs across cloud, on-prem, and hybrid environments. Yet despite this spend, leaders still lack a single source of truth to understand where resources are underutilized or wasted. Workloads are manually shuffled across clusters, quotas remain rigid, and optimization is complex. The result: idle infrastructure, runaway costs, and limited operational agility.
Exostellar solves this challenge with an AI-powered control plane that makes compute infrastructure truly elastic.
By delivering global visibility into every CPU and GPU, Exostellar dynamically matches real-time workload demand with available capacity. Its Multi-Cluster Operator (MCO) federates resources across environments so agencies can automatically borrow, preempt, and reallocate GPUs where they’re needed most — ensuring no asset sits idle. GPU Optimizer continuously rightsizes GPU-intensive workloads and intelligently packs them for maximum efficiency.
Workload Optimizer (WO) extends optimization to CPU-based applications, autonomously scaling resources based on changing demand. By eliminating overprovisioning and intelligently allocating capacity, WO empowers agencies to use only what they need — reducing waste while improving performance.
The result? Higher utilization, lower spend, and dramatically improved ROI on existing infrastructure investments. Exostellar transforms fragmented compute environments into a single, smart, self-optimizing fabric — enabling public sector agencies to deliver on their missions with greater speed, and efficiency.