List of the Top 5 AI Infrastructure Platforms for VMware Cloud in 2025

Data Science Virtual Machines (DSVMs) are customized images of Azure Virtual Machines that are pre-loaded with a diverse set of crucial tools designed for tasks involving data analytics, machine learning, and artificial intelligence training. They provide a consistent environment for teams, enhancing collaboration and sharing while taking full advantage of Azure's robust management capabilities. With a rapid setup time, these VMs offer a completely cloud-based desktop environment oriented towards data science applications, enabling swift and seamless initiation of both in-person classes and online training sessions. Users can engage in analytics operations across all Azure hardware configurations, which allows for both vertical and horizontal scaling to meet varying demands. The pricing model is flexible, as you are only charged for the resources that you actually use, making it a budget-friendly option. Moreover, GPU clusters are readily available, pre-configured with deep learning tools to accelerate project development. The VMs also come equipped with examples, templates, and sample notebooks validated by Microsoft, showcasing a spectrum of functionalities that include neural networks using popular frameworks such as PyTorch and TensorFlow, along with data manipulation using R, Python, Julia, and SQL Server. In addition, these resources cater to a broad range of applications, empowering users to embark on sophisticated data science endeavors with minimal setup time and effort involved. This tailored approach significantly reduces barriers for newcomers while promoting innovation and experimentation in the field of data science.

Intel® Tiber™ AI Studio is a comprehensive machine learning operating system that aims to simplify and integrate the development process for artificial intelligence. This powerful platform supports a wide variety of AI applications and includes a hybrid multi-cloud architecture that accelerates the creation of ML pipelines, as well as model training and deployment. Featuring built-in Kubernetes orchestration and a meta-scheduler, Tiber™ AI Studio offers exceptional adaptability for managing resources in both cloud and on-premises settings. Additionally, its scalable MLOps framework enables data scientists to experiment, collaborate, and automate their machine learning workflows effectively, all while ensuring optimal and economical resource usage. This cutting-edge methodology not only enhances productivity but also cultivates a synergistic environment for teams engaged in AI initiatives. With Tiber™ AI Studio, users can expect to leverage advanced tools that facilitate innovation and streamline their AI project development.

Our solution is specifically crafted to enable the seamless deployment of AI across various data types, thereby unlocking the full potential of your unstructured information and allowing you to access, prepare, train, optimize, and implement AI without any limitations. By integrating our advanced file and object storage solutions like PowerScale, ECS, and ObjectScale with our PowerEdge servers and a modern open data lakehouse architecture, we provide you with the necessary tools to effectively utilize AI for your unstructured data, regardless of whether it’s located on-premises, at the edge, or within a cloud setting, ensuring exceptional performance and infinite scalability. Furthermore, our dedicated team of experienced data scientists and industry experts is available to assist you in deploying AI applications that can bring substantial advantages to your organization. In addition to this, you can protect your systems from cyber threats with comprehensive software and hardware security measures, which include immediate threat detection capabilities. A singular data access point facilitates the training and refinement of your AI models, maximizing efficiency wherever your data may be—whether on-site, at the edge, or in the cloud. This holistic strategy not only boosts your AI capabilities but also strengthens your organization's ability to withstand emerging security threats. Ultimately, this ensures that your organization remains agile and competitive in a rapidly evolving technological landscape.

HorizonIQ stands out as a dynamic provider of IT infrastructure solutions, focusing on managed private cloud services, bare metal servers, GPU clusters, and hybrid cloud options that emphasize efficiency, security, and cost savings. Their managed private cloud services utilize Proxmox VE or VMware to establish dedicated virtual environments tailored for AI applications, general computing tasks, and enterprise-level software solutions. By seamlessly connecting private infrastructure with a network of over 280 public cloud providers, HorizonIQ's hybrid cloud offerings enable real-time scalability while managing costs effectively. Their all-encompassing service packages include computing resources, networking, storage, and security measures, thus accommodating a wide range of workloads from web applications to advanced high-performance computing environments. With a strong focus on single-tenant architecture, HorizonIQ ensures compliance with critical standards like HIPAA, SOC 2, and PCI DSS, alongside a promise of 100% uptime SLA and proactive management through their Compass portal, which provides clients with insight and oversight of their IT assets. This unwavering dedication to reliability and customer excellence solidifies HorizonIQ's reputation as a frontrunner in the realm of IT infrastructure services, making them a trusted partner for various organizations looking to enhance their tech capabilities.

VMware Private AI Foundation is a synergistic, on-premises generative AI solution built on VMware Cloud Foundation (VCF), enabling enterprises to implement retrieval-augmented generation workflows, tailor and refine large language models, and perform inference within their own data centers, effectively meeting demands for privacy, selection, cost efficiency, performance, and regulatory compliance. This platform incorporates the Private AI Package, which consists of vector databases, deep learning virtual machines, data indexing and retrieval services, along with AI agent-builder tools, and is complemented by NVIDIA AI Enterprise that includes NVIDIA microservices like NIM and proprietary language models, as well as an array of third-party or open-source models from platforms such as Hugging Face. Additionally, it boasts extensive GPU virtualization, robust performance monitoring, capabilities for live migration, and effective resource pooling on NVIDIA-certified HGX servers featuring NVLink/NVSwitch acceleration technology. The system can be deployed via a graphical user interface, command line interface, or API, thereby facilitating seamless management through self-service provisioning and governance of the model repository, among other functionalities. Furthermore, this cutting-edge platform not only enables organizations to unlock the full capabilities of AI but also ensures they retain authoritative control over their data and underlying infrastructure, ultimately driving innovation and efficiency in their operations.