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Average Ratings 0 Ratings

Total
ease
features
design
support

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Write a Review

Description

CambridgeNexus (CNEX), located in Boston, is an operator of AI Factory that provides exclusive leasing of bare-metal NVIDIA GB300 NVL72 racks, managing an inventory of over 350 racks housed in Tier III facilities across six US states and Taiwan, with installations typically completed within a timeframe of 75 to 90 days post-contract. Unlike traditional GPU marketplaces or virtualized cloud services, CNEX offers customers full racks that are bare metal, single tenant, and devoid of shared hardware or instances, underpinned by seven operational layers that encompass power, cooling, networking, compute, orchestration, compliance, and customer workload planning. Customers benefit from leasing complete systems, including NVIDIA GB300 NVL72 and NVIDIA Vera Rubin setups, with flexible lease agreements spanning from six months to over five years. The company guarantees a rapid turnaround from contract to installation, achieving a 99.95% uptime SLA, and adheres to stringent security and compliance standards, including SOC 2 Type I, GDPR, and HIPAA certifications, with ISO 27001 and FedRAMP statuses currently in progress. This unique approach not only ensures high reliability but also addresses the specific needs of businesses looking for dedicated AI computing resources.

Description

NVIDIA Run:ai is a cutting-edge platform that streamlines AI workload orchestration and GPU resource management to accelerate AI development and deployment at scale. It dynamically pools GPU resources across hybrid clouds, private data centers, and public clouds to optimize compute efficiency and workload capacity. The solution offers unified AI infrastructure management with centralized control and policy-driven governance, enabling enterprises to maximize GPU utilization while reducing operational costs. Designed with an API-first architecture, Run:ai integrates seamlessly with popular AI frameworks and tools, providing flexible deployment options from on-premises to multi-cloud environments. Its open-source KAI Scheduler offers developers simple and flexible Kubernetes scheduling capabilities. Customers benefit from accelerated AI training and inference with reduced bottlenecks, leading to faster innovation cycles. Run:ai is trusted by organizations seeking to scale AI initiatives efficiently while maintaining full visibility and control. This platform empowers teams to transform resource management into a strategic advantage with zero manual effort.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

No images available

Screenshots View All

Integrations

HPE Ezmeral No 
Saturn Cloud No 

Integrations

HPE Ezmeral Yes 
Saturn Cloud Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

Web-Based Yes 
On-Premises Yes 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) Yes 
Online Support No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs No 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

CambridgeNexus, Inc.

Founded

2025

Country

United States

Website

cambridgenexus.com

Vendor Details

Company Name

NVIDIA

Founded

1993

Country

United States

Website

www.nvidia.com/en-us/software/run-ai/

Product Features

Infrastructure-as-a-Service (IaaS)

Analytics / Reporting No 
Configuration Management No 
Data Migration No 
Data Security No 
Load Balancing No 
Log Access No 
Network Monitoring No 
Performance Monitoring No 
SLA Monitoring No 

Product Features

Deep Learning

Convolutional Neural Networks No 
Document Classification No 
Image Segmentation No 
ML Algorithm Library No 
Model Training No 
Neural Network Modeling No 
Self-Learning No 
Visualization No 

Virtualization

Archiving & Retention No 
Capacity Monitoring No 
Data Mobility No 
Desktop Virtualization No 
Disaster Recovery No 
Namespace Management No 
Performance Management No 
Version Control No 
Virtual Machine Monitoring No 

Alternatives

Alternatives