Utilize GPU Compute and Accelerate Your AI Development

Gain Control and Visibility of Your GPU Cluster, Lower Your AI Infrastructure Costs, and Streamline Your ML Development

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Filling the Gap between Your AI Infrastructure and ML Stack

GPUs are scarce and expensive, and yet, AI/ML teams struggle to fully utilize their AI Compute resources and streamline their model development

Run:ai sits between your ML stack and AI compute, making the scheduling of GPUs and scaling your AI Cluster painless

Manage Your AI Cluster
from One Place

Utilize your AI Cluster with Run:ai's Dynamic MIG and GPU Fractioning

Schedule workloads and assign GPU resources by teams, models and instance type— all while providing your AI teams on-demand access to compute

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Connect to our Experiment Tracking or any ML tool of your choice

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Friendly UI

Experience seamless environment provisioning with no worries about remote connection security or cumbersome CLIs

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Efficiently provision compute and data pipelines using pre-defined environments

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GPU Scheduler

Gain on-demand access to GPUs so you don't need to worry about getting a GPU slot

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Quota Management

Make sure each of your Data Scientists get their fair-share of access to compute

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Bin Packing

Combine compute resources for memory-intense Jobs like HPO and Batch Training

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Node Pools

Configure predefined collections of compute types and data sources for your teams to use

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GPU Fractioning

Run multiple Jupyter Notebooks and Inference workloads on the same GPU

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Access control and IAM

Sync your AI/ML environments with your organization's LDAP directory and SSO platform

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Multi-Cluster Support

Scale and manage your infrastructure on multi/hybrid clusters all from one place

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Configure team and role access to projects and compute nodes effortlessly using just a few clicks

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Audit Log

Historical workloads and usage logs designed to meet compliance and  audit requirements

Trusted by the Best. Secure by Design.

Run:ai is a state-of-the-art, secure, compliant platform, trusted by industry leaders

Our strong technological and business alliance with NVIDIA, extensive portfolio of commercial clients, and leading research institutions utilizing Run:ai, as well as our global market recognition, enables us to enable the people powering AI innovation

“Our experiments can take days or minutes, using a trickly of computing power or a whole cluster. With Run:ai we’ve seen great improvements in speed of experimentation and GPU hardware utilization”
Dr. M Gorge Cardoso
CTO of the AI Centre
Kings College London
“Rapid AI development is what this is all about for us. What Run:ai helps us do is to move from a company doing pure research, to a company with results in production”
Siddharth Sharma
Sr. Research Engineer
“With Run:ai, we take full advantage of our on-prem cluster, and scale to the cloud we need to. Run:ai helps us do that out of the box.”
Andrea Mirabelle
Sr. Manager, Computer Vision
Zebra Technologies
“Run:ai enables us to harness the power of Deep Learning, and continue to innovate through the use of next-generation computational tools for uncovering insights hidden in biological data.”
Talmo Pereira
Fellow & Principal Investigator
Salk Institute

The 2023 State of AI infrastructure

We surveyed 450 AI Infrastructure, DevOps and IT managers to learn about their plans and challenges for the coming year

Read Now