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What is hosted·ai?

hosted·ai is an all-encompassing neocloud platform aimed at revolutionizing servers and GPUs into a highly productive and profitable AI cloud infrastructure and service solution. The platform seamlessly merges GPU orchestration, monetization, and neocloud management, creating a software-defined environment for GPU resources that promotes true multi-tenancy, dynamic scheduling, capacity sharing, and tailored overcommitment. Its GPU pools are designed to support both shared and dedicated configurations, employing isolated workloads in conjunction with adaptive scheduling and flexible allocation methods to enhance utilization rates to nearly 100%, thereby enabling a larger number of clients to be serviced per GPU. The system is proficient in delivering elastic GPU as a Service (GPUaaS), bare metal GPU servers, GPU-optimized virtual machines, AI as a service, model libraries, bring-your-own-model options, tokenized AI workloads, along with traditional CPU, storage, and networking services. In addition, the innovative GPU Mesh feature provides on-demand wholesale capacity, thereby creating an additional revenue stream for infrastructure owners while simultaneously improving overall service availability. This forward-thinking strategy not only maximizes resource use but also ensures that AI functionalities can be more effectively harnessed across a diverse range of applications and sectors. As a result, hosted·ai stands out as a versatile platform that meets the evolving needs of businesses in the AI landscape.

What is Rafay?

Rafay provides an AI infrastructure platform for organizations that need to operate GPU and CPU environments as governed, consumable services. Built for enterprises, neoclouds, telcos, sovereign AI providers, and service providers, Rafay helps turn complex compute estates into production-ready platforms that developers, data scientists, internal teams, and external customers can use on demand. The platform gives operators a centralized way to manage infrastructure across data centers, public cloud, hybrid deployments, and sovereign or air-gapped environments. Users can access GPU capacity, Kubernetes, virtual machines, SLURM, AI workspaces, inference endpoints, and curated application catalogs through self-service workflows, while platform teams retain control over policy, identity, quotas, auditing, and cost visibility. Rafay is especially useful for organizations running shared infrastructure across many teams, tenants, regions, or customers. It supports secure multi-tenancy, lifecycle automation, chargeback, usage tracking, and standardized service delivery, helping improve GPU utilization and reduce operational burden. For GPU cloud providers and neoclouds, Rafay enables compute and AI offerings to be packaged as services, delivered through catalogs, and monetized through usage-based models. The result is a faster path from infrastructure investment to AI adoption, operational scale, and revenue-generating services.

Media

Media

Integrations Supported

Integrations Supported

Amazon EKS
Amazon Web Services (AWS)
Azure Kubernetes Service (AKS)
Cisco CX Cloud
Google Cloud Platform
Google Kubernetes Engine (GKE)
Kubernetes
Microsoft Azure
Rancher
VMware Tanzu

API Availability

Has API

API Availability

Has API

Pricing Information

$750 per month

Pricing Information

Pricing not provided

Supported Platforms

SaaS
On-Prem

Supported Platforms

SaaS

Customer Service / Support

24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
Web-Based Support

Training Options

Documentation Hub
Online Training

Training Options

Documentation Hub
Online Training

Company Facts

Organization Name

hosted·ai

Date Founded

2024

Company Location

United States

Company Website

www.hosted.ai/

Company Facts

Organization Name

Rafay

Date Founded

2017

Company Location

United States

Company Website

rafay.co

Categories and Features

Cloud GPU

Not specified

Categories and Features

AI Infrastructure

Not specified

Cloud GPU

Not specified

Container Management

Not specified

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