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Average Ratings 0 Ratings

Total
ease
features
design
support

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Write a Review

Description

Fluidstack is a high-performance AI infrastructure platform built to deliver scalable and secure compute resources for demanding workloads. It provides dedicated GPU clusters that are fully isolated, ensuring consistent performance without shared resource interference. The platform includes Atlas OS, a bare-metal operating system designed for fast provisioning, orchestration, and full control of infrastructure. Fluidstack also offers Lighthouse, a system that monitors, optimizes, and automatically resolves performance issues in real time. Its infrastructure is engineered for speed and reliability, enabling rapid deployment of GPU resources. The platform supports large-scale AI training, inference, and other compute-intensive applications. Fluidstack is designed for enterprises, AI research labs, and government organizations that require advanced computing capabilities. It provides strong security features, including compliance with standards like GDPR, SOC 2, and ISO certifications. The platform offers human support with fast response times to ensure operational stability. Fluidstack enables teams to scale infrastructure efficiently as their needs grow. Overall, it provides a robust and flexible solution for AI-driven computing at scale.

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 Yes 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Amazon Web Services (AWS) Yes 
CoreWeave Yes 
Google Cloud Platform Yes 
HPE Ezmeral No 
Kubernetes Yes 
Microsoft Azure Yes 
NVIDIA DGX Cloud Lepton Yes 
Oracle Cloud Infrastructure Yes 
Shadeform Yes 
Slack Yes 

Integrations

Amazon Web Services (AWS) No 
CoreWeave No 
Google Cloud Platform No 
HPE Ezmeral Yes 
Kubernetes No 
Microsoft Azure No 
NVIDIA DGX Cloud Lepton No 
Oracle Cloud Infrastructure No 
Shadeform No 
Slack No 

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 No 
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 Yes 

Customer Support

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

Types of Training

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

Types of Training

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

Vendor Details

Company Name

Fluidstack

Founded

2017

Country

United States

Website

www.fluidstack.io

Vendor Details

Company Name

NVIDIA

Founded

1993

Country

United States

Website

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

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