Evidence tier Source Confirmed · 4 captures on record
What the publisher says
As described on AWS Marketplace.
*** This offering is only available via private offer - please contact your NVIDIA sales representative to initiate the process ***
NVIDIA Run:ai delivers an enterprise-grade AI workload orchestration platform that maximizes the efficiency and scalability of your AWS GPU infrastructure. Purpose-built for Kubernetes environments and optimized for AI/ML workloads, Run:ai enables AWS customers to achieve greater throughput, improved utilization, and faster model development - all while maintaining tight control over resources and costs.
Show the rest of the publisher’s description (8 more lines)
Run:ai abstracts the complexity of managing GPU resources and accelerates time-to-insight for data science teams, while providing DevOps and IT stakeholders with robust tools for visibility, policy enforcement, and cost optimization. Run:ai ensures rapid deployment and integration with AWS-native services such as Amazon EKS and Amazon EC2 GPU instances, and AWS Identity and Access Management (IAM).
Key capabilities:
- Flexible GPU Scaling for AI Workloads: Seamlessly scale GPU resources up or down across AWS environments to match the dynamic needs of training, tuning, and inference.
- Automated GPU Orchestration: Ensure optimal resource allocation and scheduling for multiple workloads using intelligent policies that minimize idle time.
- Team-Based Resource Governance: Use role-based access control and team-level quotas to ensure isolation, compliance, and shared infrastructure visibility across AI teams.
- Integration with AWS Services: Deploy alongside Amazon EKS and integrate with services like Amazon S3, CloudWatch, and IAM for a unified operational experience.
- MLOps Workflow Compatibility: Native support for JupyterHub, Kubeflow, MLflow, and other AWS-hosted tools to support end-to-end machine learning pipelines.
With NVIDIA Run:ai, organizations can rapidly onboard AI teams, democratize access to GPU infrastructure, and accelerate innovation while keeping infrastructure flexible and cost-effective. The solution is ideal for enterprises looking to scale AI initiatives without the burden of managing complex infrastructure manually.
Highlights
Highlighted by the publisher on AWS Marketplace.
Optimize GPU Usage at Scale: Run:ai eliminates idle GPUs by enabling fractional sharing and dynamic allocation, maximizing hardware efficiency across teams and workloads.
Purpose-Built AI Scheduling: the Run:ai intelligent scheduler is designed specifically for AI workloads, using techniques like gang scheduling and preemption to efficiently manage complex training and inference jobs.
Centralized Hybrid Control: Manage all GPU resources - on-prem, cloud, or hybrid - from a single control plane with full visibility, policy enforcement, and multi-tenant support.
Agent build and provenance
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Compliance
- FedRAMPConfirmedNot listed90%, registry-checkedNo FedRAMP Marketplace entry matched this vendor's domain, checked 2026-08-27registry recordas observed 2026-08-27
Confirmed means matched to a public authoritative registry. Claimed means the vendor or its listing states it, not yet cross-checked. A framework not shown was not found in any source we hold, which is not evidence against it. Not listed means a scoped registry check found no match for this vendor's domain: a No is a scoped registry check, not a compliance judgment. Confidence bands: 95% domain-verified, 90% registry-checked, 80% self-attested, 70% weak signal. Self-attested items marked “vendor's site” are gathered from the vendor's own website and are not verified by us.
Vendor
External enrichment · as of 2026-08-10
Plans and pricing as listed
1 listed- Units
Refund terms
As stated by the publisher on AWS Marketplace.
NVIDIA Run:ai does not have a refund policy
Sources
Publisher resources
2 linksLinked repositories
Unknown means this listing does not publish a repository. It is not a statement that the code is closed, and a linked repository is not a claim that the publisher wrote it: the registry computes that relationship privately and does not publish it.
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