Hewlett Packard Enterprise (NYSE: HPE) and NVIDIA Corporation have unveiled a unified strategy to redefine artificial intelligence infrastructure through an expanded partnership that places sovereign control, high-performance computing, and scalable interconnection at the core of the AI lifecycle. Revealed during HPE Discover Barcelona 2025, the collaboration introduces Europe’s first AI Factory Lab in Grenoble, France, along with several architectural breakthroughs that could enable enterprises to scale AI not just up or out, but across geographic boundaries through an interconnected AI Factory Grid.
By integrating HPE’s Private Cloud AI capabilities and Juniper Networking platforms with NVIDIA’s full-stack accelerated computing and Spectrum-X Ethernet technologies, the two companies are enabling enterprises to build secure, sovereign-ready data centers tailored for complex AI workloads. With the introduction of these solutions, HPE and NVIDIA are responding directly to the growing demand for local data control, regulatory alignment, and long-distance high-throughput networking to power next-generation generative AI and large language model deployments across regulated sectors.
The announcement reflects a shift away from legacy data centers toward purpose-built AI factories that behave as intelligent, high-speed processing plants. These facilities are now being connected into a unified architecture that enables model training, inference, and data movement at global scale, while meeting local compliance and operational sovereignty mandates.
Why the AI Factory Lab in Grenoble represents a breakthrough for sovereign AI in the EU
The AI Factory Lab in Grenoble is a critical asset in the broader strategy of enabling sovereign AI infrastructure within the European Union. It provides a live, production-grade testing ground where customers can validate workload performance on physical infrastructure located entirely within the EU. This approach directly supports enterprise and government clients facing increasing scrutiny around data sovereignty, GDPR compliance, and AI safety regulations.
Housed within the air-cooled facility are HPE Alletra storage systems, NVIDIA Spectrum-X Ethernet switches, HPE Juniper Networking MX and PTX series routers, and NVIDIA’s government-ready AI Enterprise software. By bringing together these components in a tightly integrated environment, the lab offers real-time benchmarking and refinement for workloads that must adhere to strict jurisdictional and sector-specific standards. The Grenoble initiative is complemented by a new Private AI Lab in London, developed in partnership with Carbon3.ai and designed to accelerate sovereign AI adoption within the United Kingdom using the same core architecture.
Executives from both companies emphasized the strategic importance of these labs. Antonio Neri, president and chief executive officer of HPE, stated that the partnership continues to deliver secure AI factories at any scale, with innovations targeting the most complex and diverse workloads emerging in enterprise AI today. Jensen Huang, founder and chief executive officer of NVIDIA Corporation, described the AI Factory Lab as a foundry for transforming data into intelligence, powered by a full stack of accelerated computing, data networking, and sovereign-grade security.
How the AI Factory Grid model redefines scalability for next-generation AI workloads
Traditional methods of scaling AI infrastructure, including vertical integration using denser servers and horizontal expansion via additional nodes, are reaching the limits of efficiency and manageability. The AI Factory Grid architecture introduces a third dimension: scaling across distributed geographies. This approach connects multiple AI factories through a high-performance networking fabric, enabling them to operate as a unified computational grid.
Inside each AI factory, NVIDIA ConnectX-8 SuperNICs and Spectrum-X Ethernet switches deliver GPU-to-GPU communication with low latency and RDMA awareness. These intra-factory connections are extended across metro regions and multicloud environments using HPE Juniper PTX series routers equipped with Express 5 silicon, which support long-haul 800G ZR+ coherent optics and IP/MPLS protocols optimized for AI workloads.
This grid architecture allows geographically distributed AI workloads to run as one system. It supports model training across borders, high-speed data movement across clouds, and inference pipelines that require regulatory isolation and data localization. The AI Factory Grid eliminates performance trade-offs and creates a backbone for futureproofed global-scale AI.
What innovations are driving HPE’s upgraded Private Cloud AI capabilities in 2026
To meet the rising demand for secure and compliant AI infrastructure, HPE has upgraded its Private Cloud AI portfolio with a suite of new capabilities. Organizations can now deploy NVIDIA RTX PRO 6000 Blackwell Server Edition GPUs, as well as NVIDIA Hopper chips, within air-gapped environments that offer added security.
The inclusion of STIG-hardened and FIPS-enabled NVIDIA AI Enterprise software provides an additional layer of protection, especially for defense, healthcare, and financial services clients. GPU fractionalization through NVIDIA Multi-Instance GPU technology allows for better workload flexibility and cost efficiency by enabling partitioning of compute power across tasks. This ensures optimal utilization of hardware investments, particularly for organizations running diverse AI workloads simultaneously.
A key enhancement includes the introduction of HPE Alletra Storage MP X10000 Data Intelligence Nodes, which now function as active data layers capable of processing, classifying, and optimizing information in real time. These nodes bring NVIDIA accelerated computing into the data pipeline itself, enabling inline inference as data is ingested, thus supporting faster AI training and improved model accuracy.
HPE also announced new Datacenter Ops Agents, developed in partnership with World Wide Technology, NVIDIA, and HPE engineering teams, to simplify multi-cloud AI operations and integrate observability into sovereign environments. These agents are designed to automate routine AI infrastructure management, helping customers ensure consistent performance while complying with jurisdictional constraints.
How high-performance networking from HPE and NVIDIA powers the AI Factory backbone
The seamless integration of three critical silicon platforms—NVIDIA Spectrum-X Ethernet, HPE Juniper Express 5, and HPE Juniper Trio 6—underpins the networking layer of the AI Factory Grid. Each component serves a unique role.
NVIDIA Spectrum-X and ConnectX-8 SuperNICs provide high-speed, low-latency, RDMA-aware fabric within individual AI factories, optimized for model training and inference. HPE Juniper PTX routers enable secure and scalable inter-factory transport using IP/MPLS protocols, advanced routing, and 800G optics. These long-distance links support coherent optical networking with MACsec encryption at line rate for secure dark-fiber and DWDM deployments.
At the edge, HPE Juniper MX series routers facilitate massive-scale tenant onboarding. These routers, including the MX301, MX304, and modular MX10000, offer programmable logic that supports advanced routing, workload-aware traffic engineering, and segmentation for multi-tenant enterprise AI use cases. Their ability to handle millions of secure tunnels makes them ideal for organizations seeking to onboard thousands of customers, endpoints, and AI workloads without intermediate gateways.
The 3-2-1 integration strategy, that is three silicon engines from two companies into one fabric, forms the physical and logical foundation of the AI Factory Grid and unlocks new levels of speed, compliance, and operational visibility for large-scale AI deployments.
What does the NVIDIA GB200 NVL4 by HPE offer for inference-heavy AI applications?
HPE is also making AI inference more accessible and energy-efficient with the introduction of the NVIDIA GB200 NVL4 by HPE. This compact system combines two NVIDIA Grace CPUs with four Blackwell GPUs to deliver dense, power-conscious performance for large language models and generative AI applications.
With up to 136 GPUs per rack and support for sovereign deployment standards, the NVIDIA GB200 NVL4 is being positioned as a mid-tier alternative to hyperscale GPU clusters. It is particularly attractive for enterprises seeking to deploy high-performance inference capabilities without committing to the capital intensity or power consumption of full AI supercomputing platforms.
This system is now available to order globally, with sovereign AI factory solutions expected to be widely available in the first half of 2026.
How HPE, CrowdStrike, and Fortanix are securing the sovereign AI lifecycle
Cybersecurity remains a central pillar of the HPE and NVIDIA sovereign AI blueprint. HPE has selected CrowdStrike as the primary AI security layer for its Private Cloud AI deployments. This includes unified protection for endpoints, identities, and data in both hybrid and multi-cloud environments.
CrowdStrike’s threat protection suite is designed to work seamlessly with NVIDIA’s always-on AI agents, enabling continuous monitoring and rapid incident response across LLM pipelines and sensitive data flows.
Additionally, HPE has teamed up with Fortanix to support confidential AI workloads through NVIDIA Confidential Computing. Fortanix Armet AI can now be deployed on HPE ProLiant DL380a Gen12 servers with NVIDIA Blackwell GPUs to enable secure, agentic AI operations in heavily regulated sectors such as government, defense, and finance. These solutions offer organizations the tools to operationalize AI safely and compliantly across a range of edge, private, and hybrid environments.
What are the key takeaways from HPE and NVIDIA’s AI Factory Grid announcement?
- HPE and NVIDIA Corporation have expanded their collaboration to launch sovereign AI factories, beginning with a new AI Factory Lab in Grenoble, France.
- The AI Factory Grid model enables organizations to scale AI workloads across geographies by interconnecting multiple AI factories using high-speed, secure, and intelligent networking.
- NVIDIA Spectrum-X Ethernet switches and ConnectX-8 SuperNICs deliver RDMA-aware intra-factory GPU networking optimized for AI model training and inference.
- HPE Juniper PTX and MX series routers enable high-scale, long-distance, and multi-cloud connectivity with 800G ZR+ optics, MACsec encryption, and advanced IP/MPLS routing.
- HPE Private Cloud AI has been upgraded with Blackwell GPUs, MIG-based GPU fractionalization, FIPS-compliant AI Enterprise software, and inline data intelligence nodes for real-time inference.
- The NVIDIA GB200 NVL4 by HPE introduces a compact, energy-efficient platform for LLM and generative AI inference with up to 136 GPUs per rack.
- Cybersecurity integrations include CrowdStrike for unified threat protection and Fortanix Armet AI with NVIDIA Confidential Computing for secure agentic AI in regulated industries.
- HPE and NVIDIA’s 3-2-1 integration strategy combines three silicon platforms from two companies into one unified AI networking fabric.
- The initiative positions Europe as a key hub for sovereign AI infrastructure, supporting data localization, compliance, and operational autonomy.
- Enterprises and hyperscalers can now build scalable, secure, and sovereign-ready AI infrastructure aligned with regional regulations and future AI governance frameworks.
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