Flexible GPU Compute. On Demand.
Access high-performance GPUs through virtualised environments — enabling rapid deployment, scalable workloads, and efficient resource utilisation without dedicated infrastructure.
Core Capabilities
On-Demand GPU Access
Spin up GPU instances instantly and scale based on workload requirements
Flexible Resource Allocation
Allocate compute, memory, and storage dynamically for different AI workloads
Efficient Utilisation
Optimised virtualisation enables cost-effective usage without idle capacity
Rapid Deployment
Provision GPU instances in minutes with minimal setup
Use Cases for Virtualised GPUs
Flexible GPU infrastructure designed to support development, scaling, and deployment of modern AI workloads.
AI Development & Experimentation
Train, fine-tune, and test models in flexible GPU environments without long-term infrastructure commitments.
Scalable Inference Workloads
Run inference workloads that scale dynamically based on demand, optimising performance and cost.
Application Testing & Prototyping
Quickly deploy GPU instances for testing AI models, applications, and new features in development environments.
Application Testing & Prototyping
Quickly deploy GPU instances for testing AI models, applications, and new features in development environments.