Integrated hardware and software stacks for running AI on your own terms — fifteen vendors from turnkey systems to storage, silicon and platform software.
A turnkey private AI stack for building, running and scaling enterprise AI agents with unified control, governance and observability across data, models, tools and workflows. HPE reports it was named a Leader in the IDC MarketScape for Private AI Infrastructure Systems.
Visit siteIBM’s portfolio of AI products for bringing generative AI into core business workflows. For on-premises deployments, IBM pairs watsonx with IBM Fusion HCI for tightly integrated private AI.
Visit siteAn end-to-end enterprise AI offering that combines Dell compute, storage, networking and services with NVIDIA accelerated computing and enterprise AI software, from desktop to data center to edge. *Dell reports it was named a Leader in the same IDC assessment.
Visit siteInfrastructure vendors that package compute, networking and software into deployable AI systems.
A full-stack architecture built on Cisco AI PODs — UCS compute, Nexus networking, GPUs and software — with Cisco security and Splunk observability layered in.
Visit siteFull-stack AI capabilities across workstations, servers, networking and storage, built on NVIDIA Enterprise Reference Architectures, with a library of ready-to-customize AI use-case solutions.
Visit siteModular servers, storage, networking, racks and liquid cooling packaged as AI factory cluster solutions based on NVIDIA Enterprise Reference Architectures.
Visit siteVendors that keep GPUs fed and turn enterprise data into AI-ready datasets.
AIPod consolidates analytics, training and inference compute into a single system, while the AI Data Engine prepares unstructured data into AI-ready datasets with a built-in vector database and data guardrails.
Visit siteAn AI infrastructure stack built on NVIDIA HGX, with the iQ M Series pairing VSP One storage and optional NVIDIA AI Enterprise software to keep GPUs saturated with data.
Visit siteCompute vendors whose accelerators and reference designs underpin private AI systems.
The DGX platform, including DGX SuperPOD, combines NVIDIA infrastructure, software and expertise into a unified AI development solution. Many other vendors on this page build on NVIDIA reference architectures.
Visit siteOpen, flexible compute for AI across data center, edge and cloud, led by the Instinct GPU line aimed at frontier AI, HPC and sovereign AI workloads.
Visit siteGaudi 3 accelerators and Xeon processors, plus an open-source LLM serving stack with OpenAI-compatible APIs that deploys on Kubernetes, on premises or in the cloud.
Visit siteAn AI inference platform built on its own reconfigurable dataflow chips, available as SambaCloud or as SambaRack, a turnkey on-premises rack of 16 SN40L chips. Intel announced a partnership and investment in 2026.
Visit siteSoftware and cloud-in-your-data-center options that sit on top of the hardware.
A hybrid cloud platform that combines MLOps, GenAIOps and AgentOps capabilities to develop and deploy AI applications across datacenter, cloud and edge on OpenShift.
Visit sitePrivate AI services for VMware Cloud Foundation, run in your own data center. VMware’s earlier Private AI Foundation with NVIDIA page now leads here.
Visit siteBrings Oracle Cloud Infrastructure’s AI and cloud services into customer data centers or partner-run regions, with NVIDIA’s full-stack AI platform, for control over data, operations and location.
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