Optimize AI

Build Your AI Infrastructure on Solid Foundation

Start your AI journey right on infrastructure that's built to serve your AI practice from a single cluster to super pods.

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Take your AI Infrastructure from zero to one, and beyond

Delivering robust, scalable and accessible AI Compute resources is a challenge both on single-pod and HPC environments.

Run:ai’s Atlas delivers simple, on-demand access to compute resources to AI Practitioners while giving Engineering teams peace- of-mind. Atlas assures GPU resources are constantly optimized, accessed, and utilized to their fullest on any infrastructure architecture and size.

Gain Visibility
& Control

Run:ai Atlas offers dashboards and analytics giving IT insight across all resources and workloads. Align resource allocation to business goals by setting policies and priorities across departments, projects or users.

Automated Resource
Management

Dynamically allocate resources using a Smart Scheduler built as a simple Kubernetes plug-in, built from the ground up to work with containers and cloud-native architectures.

Improve ROI > 2x

Advanced technology for sharing and optimizing GPUs improves utilization by more than 2X, and significantly increases ROI on existing GPU and CPU infrastructure.

One platform for
Building, Training, and Deploying

AI practitioners can easily consume resources in a self-service model using native Run:ai workflows to build, train and deploy models; or by using 3rd party integrations, such as MLflow, Kubeflow and more.

IT & MLOPS

AI Infrastructure made simple

Build your AI infrastructure with cloud-like resource accessibility and management, on any infrastructure, and enable researchers to use any ML and DS tools they choose.

Run:AI’s platform builds off of powerful distributed computing and scheduling concepts from High Performance Computing (HPC), but is implemented as a simple Kubernetes plugin. 

Our AI Cloud Platform speeds up data science workflows and creates visibility for IT teams who can now manage valuable resources more efficiently, and ultimately reduce idle GPU time.

Gain Visibility & Control

Simplify management of GPU allocation and ensure sharing between users, teams, and projects according to business policies & goals.

Run:AI brings a cloud-like experience to resource management wherever your resources are: cloud, on-premises or hybrid cloud.

Built for Cloud-Native

Super-powerful scheduling built as a simple Kubernetes plug-in, built from the ground up to work with containers and cloud-native architectures.

Make use of fractional GPUs, integer GPUs, and multiple-nodes of GPUs, for distributed training on Kubernetes.

Improve ROI >2x

Improves utilization by more than 2X, and significantly increases ROI on existing GPU and CPU infrastructure.

Run workloads on fractions of GPUs, converting spare capacity to speed and increasing infrastructure efficiency.

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