Speed Into the AI Era with Run:ai’s Foundation for AI Infrastructure
Run:ai helps organizations accelerate their AI journey – from building initial models to scaling AI in production. Using Run:ai’s Atlas software platform, companies streamline the development, management and scaling of AI applications across any infrastructure (on-premises, edge, cloud). Researchers gain on-demand access to pooled resources for any AI workload. An innovative, cloud-native operating-system helps IT manage everything from fractions of GPUs to large-scale distributed training. Learn more at www.run.ai.
By using Atlas resource pooling, queueing, and prioritization mechanisms, researchers are removed from infrastructure management hassles and can focus exclusively on data science. Run as many workloads as needed without compute bottlenecks. Run:ai delivers real time and historical views on all resources managed by the platform, such as jobs, deployments, projects, users, GPUs and clusters.
Run:ai can support all types of workloads required within the AI lifecycle (build, train, inference) to easily start experiments, run large-scale training jobs and take AI models to production without ever worrying about the underlying infrastructure. The Atlas platform allows MLOps and AI Engineering teams to quickly operationalize AI pipelines at scale, and run production machine learning models anywhere while using the built-in ML toolset or simply integrating their existing 3rd party toolset.
Run:ai’s unique GPU Abstraction capabilities “virtualize” all available GPU resources to maximize infrastructure efficiency and increase ROI. The platform pools expensive compute resources and makes them accessible to researchers on-demand for a simplified, cloud-like experience.