Hewlett Packard Enterprise
Enterprise IT company providing servers, AI compute and rugged edge systems for real-time, autonomous decision-making in industrial environments.
Hewlett Packard Enterprise (HPE) is an American multinational enterprise information-technology company headquartered in Spring, Texas. It was founded on November 1, 2015, when the former Hewlett-Packard Company split into HPE and HP Inc., and it trades on the NYSE under the ticker HPE. The company delivers hardware, software and services spanning servers and compute, hybrid-cloud infrastructure, data storage, networking, AI and supercomputing for enterprise and industrial customers worldwide. Of particular relevance to robotics and autonomous systems is HPE's edge-computing portfolio. The HPE Edgeline converged edge systems and the Edgeline OT Link Platform enable distributed, real-time decision-making and autonomous operations at the edge by automating the interplay between operational-technology data acquisition and standard IT applications. HPE has expanded its rugged, AI-ready edge line, including ProLiant Compute EL2000 and Gen12 edge servers built for harsh, space-constrained and remote environments, targeting national security, telecom, defense and industrial automation customers that require high compute at the point of data.
The company has also introduced AI-native, self-driving network capabilities across HPE Aruba Networking and HPE Mist for autonomous network operations. Through ProLiant compute, edge platforms and AI infrastructure, HPE supplies the compute, edge and networking foundation used for AI inferencing, machine vision, sensor fusion and real-time control in industrial and autonomous-system deployments, positioning it as an enabling compute supplier rather than a robot manufacturer.
Primary type & automation activities this supplier delivers:
HPE Edgeline Converged Edge System
Converged edge compute platform for real-time decision-making and autonomous operations at the edge.
HPE ProLiant Compute EL2000
- Model: EL2000
- Launch Year: 2026
Rugged AI-ready edge server for high compute in harsh, space-constrained and remote environments.
Contact Hewlett Packard Enterprise
WEBSITE
https://www.hpe.comHEADQUARTERS
United States
Company Facts
Founded
2015
Primary Role
Component Supplier
Company Size
-
Primary Region
North America
Annual Sales
-
Funding Stage
-
Funding Total
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Certifications & Memberships
The AI Data Centers That Fit on a Truck
In response to the growing demand for rapid deployment of AI hardware, companies like Duos Edge AI and LG CNS are shifting towards modular data centers. Traditional data centers, which require extensive construction of steel and concrete shells, can take years to build, posing challenges for organizations eager to implement AI solutions. Duos Edge AI, led by CEO Doug Recker, has developed modular compute pods that can be deployed in about six months, significantly faster than conventional setups. Each 55-foot pod houses racks of GPUs and can operate independently or in conjunction with others, with a recent deal to deploy four pods containing a total of 2,304 GPUs, expandable to 4,608. Similarly, LG CNS is launching its AI Modular Data Center in Busan, South Korea, featuring 576 Nvidia GPUs per unit, with plans for an expanded version supporting over 4,600 GPUs. Both companies emphasize the advantages of modular systems, which require only a concrete pad for installation, allowing for quicker site readiness and reduced permitting complexities. The modular approach not only accelerates deployment but also offers cost savings, with Duos estimating a 5-megawatt modular deployment could be built for around $25 million, significantly lower than traditional facilities. As the market for modular data centers is projected to double by 2030, other tech giants like Hewlett Packard Enterprise and Schneider Electric are also exploring similar solutions. The modular design allows for incremental expansion, enabling facilities to grow in capacity as demand increases, positioning them as a viable alternative to traditional data centers.
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