GMI Cloud

About GMI Cloud

GMI Cloud provides instant access to NVIDIA H100 GPUs for training and deploying generative AI applications, utilizing a Kubernetes-based cluster engine for efficient workload orchestration. This platform addresses the need for rapid GPU provisioning and management, enabling developers to focus on building AI models without the complexities of infrastructure setup.

```xml <problem> Training and deploying generative AI models requires significant computational resources, particularly access to high-performance GPUs. Acquiring and managing this infrastructure can be complex and time-consuming, diverting developer focus from model development and deployment. Traditional cloud GPU provisioning often involves long wait times and intricate setup procedures. </problem> <solution> GMI Cloud provides on-demand access to NVIDIA H100 and H200 GPUs, streamlining the process of training and deploying generative AI applications. The platform utilizes a Kubernetes-based cluster engine to efficiently orchestrate workloads, enabling developers to quickly allocate, deploy, and monitor GPU resources. GMI Cloud offers pre-configured containers with popular machine learning frameworks, as well as the option to use custom Docker images. The platform aims to reduce infrastructure management overhead, allowing users to concentrate on building and refining AI models. </solution> <features> - Instant access to NVIDIA H100 and H200 GPUs - Kubernetes-based cluster engine for workload orchestration and resource management - Pre-configured containers with TensorFlow, PyTorch, Keras, Caffe, MXNet, and ONNX - Support for custom Docker images - High-performance inference capabilities - Integration with NVIDIA NIMs - Global data centers for low latency and high availability - Automatic scaling options for cost and performance optimization </features> <target_audience> GMI Cloud targets AI developers, machine learning engineers, and data scientists who require scalable GPU resources for training and deploying generative AI models. </target_audience> <revenue_model> GMI Cloud offers on-demand GPU access starting at $4.39 per GPU-hour and private cloud instances starting at $2.50 per GPU-hour. </revenue_model> ```

What does GMI Cloud do?

GMI Cloud provides instant access to NVIDIA H100 GPUs for training and deploying generative AI applications, utilizing a Kubernetes-based cluster engine for efficient workload orchestration. This platform addresses the need for rapid GPU provisioning and management, enabling developers to focus on building AI models without the complexities of infrastructure setup.

Where is GMI Cloud located?

GMI Cloud is based in San Jose, United States.

When was GMI Cloud founded?

GMI Cloud was founded in 2023.

How much funding has GMI Cloud raised?

GMI Cloud has raised 142000000.

Who founded GMI Cloud?

GMI Cloud was founded by Alex Yeh.

  • Alex Yeh - CEO
Location
San Jose, United States
Founded
2023
Funding
142000000
Employees
46 employees
Major Investors
Headline Asia (formerly Infinity Ventures)
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GMI Cloud

Score: 100/100
AI-Generated Company Overview (experimental) – could contain errors

Executive Summary

GMI Cloud provides instant access to NVIDIA H100 GPUs for training and deploying generative AI applications, utilizing a Kubernetes-based cluster engine for efficient workload orchestration. This platform addresses the need for rapid GPU provisioning and management, enabling developers to focus on building AI models without the complexities of infrastructure setup.

gmicloud.ai2K+
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Crunchbase
Founded 2023San Jose, United States

Funding

$

Estimated Funding

$142M+

Major Investors

Headline Asia (formerly Infinity Ventures)

Team (40+)

Alex Yeh

CEO

Company Description

Problem

Training and deploying generative AI models requires significant computational resources, particularly access to high-performance GPUs. Acquiring and managing this infrastructure can be complex and time-consuming, diverting developer focus from model development and deployment. Traditional cloud GPU provisioning often involves long wait times and intricate setup procedures.

Solution

GMI Cloud provides on-demand access to NVIDIA H100 and H200 GPUs, streamlining the process of training and deploying generative AI applications. The platform utilizes a Kubernetes-based cluster engine to efficiently orchestrate workloads, enabling developers to quickly allocate, deploy, and monitor GPU resources. GMI Cloud offers pre-configured containers with popular machine learning frameworks, as well as the option to use custom Docker images. The platform aims to reduce infrastructure management overhead, allowing users to concentrate on building and refining AI models.

Features

Instant access to NVIDIA H100 and H200 GPUs

Kubernetes-based cluster engine for workload orchestration and resource management

Pre-configured containers with TensorFlow, PyTorch, Keras, Caffe, MXNet, and ONNX

Support for custom Docker images

High-performance inference capabilities

Integration with NVIDIA NIMs

Global data centers for low latency and high availability

Automatic scaling options for cost and performance optimization

Target Audience

GMI Cloud targets AI developers, machine learning engineers, and data scientists who require scalable GPU resources for training and deploying generative AI models.

Revenue Model

GMI Cloud offers on-demand GPU access starting at $4.39 per GPU-hour and private cloud instances starting at $2.50 per GPU-hour.

GMI Cloud - Funding: $100M+ | StartupSeeker