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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.

What is Mistral Compute?

Mistral Compute is a dedicated AI infrastructure platform that offers a full private stack, which includes GPUs, orchestration, APIs, products, and services, available in a range of configurations from bare-metal servers to completely managed PaaS solutions. The platform aims to expand access to cutting-edge AI technologies beyond a select few providers, empowering governments, businesses, and research institutions to design, manage, and optimize their entire AI ecosystem while training and executing various workloads on a wide selection of NVIDIA-powered GPUs, all supported by reference architectures developed by experts in high-performance computing. It addresses specific regional and sectoral demands, such as those in defense technology, pharmaceutical research, and financial services, while leveraging four years of operational expertise and a strong commitment to sustainability through decarbonized energy, ensuring compliance with stringent European data-sovereignty regulations. Moreover, Mistral Compute’s architecture not only focuses on delivering high performance but also encourages innovation by enabling users to scale and tailor their AI applications according to their evolving needs, thereby fostering a more dynamic and responsive technological landscape. This adaptability ensures that organizations can remain competitive and agile in the rapidly changing world of AI.

Media

Media

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

Integrations Supported

Mistral AI
Mistral Forge
NVIDIA virtual GPU

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided

Pricing Information

Pricing not provided

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Standard Support
Web-Based Support

Customer Service / Support

Standard Support
Web-Based Support

Training Options

Documentation Hub
Online Training

Training Options

Documentation Hub
On-Site Training

Company Facts

Organization Name

Rafay

Date Founded

2017

Company Location

United States

Company Website

rafay.co

Company Facts

Organization Name

Mistral

Date Founded

2023

Company Location

France

Company Website

mistral.ai/news/mistral-compute

Categories and Features

AI Infrastructure

Not specified

Cloud GPU

Not specified

Container Management

Not specified

Categories and Features

AI Cloud Providers

Not specified

AI Infrastructure

Not specified

Cloud GPU

Not specified

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