- ML/AI team productivity – 10X faster iteration, less infrastructure friction
- GPU utilization – 80% higher availability, and better ROI
- Real-time resource visibility and autonomous cost optimization
Future of AI Orchestration:
Software Defined GPUs™
Request Early Access
What is Software Defined GPU™?
Exostellar’s Software-Defined GPU (SDG) is a multi-vendor, smart GPU slicing technology based on Kubernetes DRA (Dynamic Resource Allocation). It enables dynamic, fractional GPU resource allocation across workloads—transforming static GPU infrastructure into flexible, on-demand compute.
With SDG, AI engineers can request and orchestrate GPU resources in granular increments (e.g., by GB of memory), just in time and across different vendors—without any code or container changes.
Heterogeneous GPU
Pooling
Abstract away underlying GPU hardware, allowing seamless access to GPUs from different vendors.
Dynamic AI Workload
Right-Sizing
Dynamically resize GPU resources based on workload needs and fluctuating demand, maximizing utilization and performance.
Autonomous AI
Infra Optimization
Intelligent, fair scheduling and optimization of GPU resource allocation to maximize efficiency.
Peak performance for your AI workloads
20X
GPU
Efficiency
Zero
Vendor
Lock-in
<1 min
From Resource Request
to Allocation
3X
Faster AI
Development Cycles
Mehdi Tantaoui
CPO OmniOps
“Exostellar’s SDG™ helped us push our optimization software capabilities further with its ability to provision slices of the GPUs dynamically on k8s. It fits well with our GPU sizing capabilities and NN layer optimizations. This combination drives a compounded value of up to 14x GPU efficiency, driving the operational cost down significantly.”
testing
Powered by Software Defined GPU™
GPU Flex
Run AI workloads in minutes— anywhere, anytime.
AI Developers
- Instant setup, no code/container changes
- Fractional GPU orchestration for multi-agent workflows
- Works on any infra: bare-metal or Kubernetes
GPU IQ
Right-size your AI workloads
— in real-time.
AI Teams
- AI-aware partitioning of compute & memory
- Just-in-time GB-level allocation
- Real-time GPU telemetry & right-sizing
GPU ClusterOps
Optimize every GPU dollar
with FinOps intelligence.
Infra Admins, CFO
- Centralized cluster management, K8s-friendly
- Hardware agnostic, portable across MLOps
- Smart dashboards with agentic decision support
10X
Productivity Gains
5X
Memory Utilization
75%
Cost Savings
Exostellar Architecture: Intelligent Orchestration Across the AI Stack
Exostellar sits at the core of your AI infrastructure — seamlessly integrating across all layers of the modern ML/AI stack. From GPU hardware to orchestration and developer environments, our architecture is purpose-built to optimize every step of the AI lifecycle.
Request Early Access Today!
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1. Fine-grained slicing across vendor GPUs
Smart partition and allocation of GPU memory in GBs [and compute units] purpose-built for agentic workflows.
2. Kubernetes-native integration
Non-intrusive, drop-in AI infra middleware, built on K8s DRA, with support for non-DRA clusters.
3. Just-in-time integration
Request GPU resources as needed for AI development, training, or inference—no more static allocation or overprovisioning.
