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Average Ratings 0 Ratings

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ease
features
design
support

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Write a Review

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.

Description

UbiOps serves as a robust AI infrastructure platform designed to enable teams to efficiently execute their AI and ML workloads as dependable and secure microservices, all while maintaining their current workflows. In just a few minutes, you can integrate UbiOps effortlessly into your data science environment, thereby eliminating the tedious task of establishing and overseeing costly cloud infrastructure. Whether you're a start-up aiming to develop an AI product or part of a larger organization's data science unit, UbiOps provides a solid foundation for any AI or ML service you wish to implement. The platform allows you to scale your AI workloads in response to usage patterns, ensuring you only pay for what you use without incurring costs for time spent idle. Additionally, it accelerates both model training and inference by offering immediate access to powerful GPUs, complemented by serverless, multi-cloud workload distribution that enhances operational efficiency. By choosing UbiOps, teams can focus on innovation rather than infrastructure management, paving the way for groundbreaking AI solutions.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Amazon S3 No 
Amazon S3 Glacier No 
Amazon Web Services (AWS) No 
Arize AI No 
Google Cloud BigQuery No 
Google Cloud Platform No 
HPE Ezmeral Yes 
JupyterLab No 
MLflow No 
Microsoft Azure No 
Python No 
Terraform No 
WhyLabs No 

Integrations

Amazon S3 Yes 
Amazon S3 Glacier Yes 
Amazon Web Services (AWS) Yes 
Arize AI Yes 
Google Cloud BigQuery Yes 
Google Cloud Platform Yes 
HPE Ezmeral No 
JupyterLab Yes 
MLflow Yes 
Microsoft Azure Yes 
Python Yes 
Terraform Yes 
WhyLabs 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 No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook 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 

Customer Support

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

Customer Support

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

Types of Training

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

Types of Training

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

Vendor Details

Company Name

NVIDIA

Founded

1993

Country

United States

Website

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

Vendor Details

Company Name

UbiOps

Founded

2020

Country

The Netherlands

Website

ubiops.com

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