Run:ai's platform revolutionizes AI and machine learning operations by addressing key infrastructure challenges through dynamic resource allocation, comprehensive AI lifecycle support, and strategic resource management. By pooling resources across environments and utilizing advanced orchestration and accelerators, Run:ai significantly enhances GPU efficiency and workload capacity. Its policy engine and open architecture foster strategic alignment with business objectives, enabling seamless integration with external tools and systems.

This results in significant increases in GPU availability, workloads, and GPU utilization, all with zero manual resource intervention, accelerating innovation and providing a scalable, agile, and cost-effective solution for enterprises.

Key Challenges Driven By
AI Transformation

Growing data science teams and rapidly evolving ecosystems

Distributed compute resources with no / limited centralization

Strategically aligning resources to dynamic business requirements

Diverse AI workloads patterns and resource requirements

GPU starvation / overprovisioning

Solution - AI
Infrastructure Management

AI Infrastructure Management represents a transformative approach to managing and optimizing AI resources and operations within an enterprise. It is an ecosystem designed to overcome the inherent challenges in traditional AI infrastructure by being dynamic, strategic, and integrally aligned with business objectives.

the Run:ai platform

Run:ai offers the leading infrastructure management platform that revolutionizes the way enterprises manage and optimize their AI and machine learning operations. This platform is specifically designed to address the unique challenges of AI infrastructure, enhancing efficiency, scalability, and flexibility.

Improved Productivity, Faster
Time to Market

Zero Touch resources

Zero touch resources

With features like GPU Scheduling, Quota Management, GPU Fractioning and Dynamic MIG (Multi Instance GPU) Run:ai's platforms can help you squeeze more from the same infrastructure, on-prem and in the cloud.

Tool flexibility

Real-time and historical metrics by job, workload, and team in a single Dashboard. Assign compute guarantees to critical workloads, promote oversubscription, and react to business needs easily.

Cloud-like elasticity

Our built-in Identity Management system integration, and Policies mechanism, allow you to control which team has access to which resources, create node pools, and manage risk.

Centralized Visibility and Control

Zero Touch resources

Fully-utilized compute

Promote practitioner productivity with the Run:ai GUI. Run:ai makes it simple for a practitioner to access compute and run workloads without being a technical expert. Workspaces and templates were built with end users in mind.

Enterprise visibility

Provide ultimate flexibility to practitioners to integrate experiment tracking tools and development frameworks. With Run:ai's rich integration options you can work with your favorite ML stack right away.

Central policy control

Our built-in Identity Management system integration, and Policies mechanism, allow you to control which team has access to which resources, create node pools, and manage risk.


Efficient Utilization of Compute Resources
Maximizes GPU efficiency, reducing additional hardware needs

Strategic Resource Management
Aligns resources with business objectives for operational efficiency and competitive advantage

Scalability and Agility
Enhances the ability to quickly scale AI initiatives, ensuring agility and competitiveness

Comprehensive AI Lifecycle Support
Accelerates innovation and shortens the path from idea to implementation

Integration and Collaboration
Fosters innovation through seamless integration with leading technologies

Operational Efficiency
Reduces operational costs, freeing up resources for strategic initiatives