From zero to AI hero in eight hours

[JoannStarke]

Deploy secure, accessible AI in under 8 hours with HPE Private Cloud AI. Control your data and empower your team. Download the analyst report today. 

It's tough to find an enterprise not exploring the possibilities of artificial intelligence (AI), especially the transformative potential of generative AI (GenAI). From automating complex tasks and accelerating research to creating entirely new products and services, these technologies promise to revolutionize how we do business.

While AI adoption is essential for competitiveness, implementing it, especially generative AI (GenAI), presents significant challenges. These often center on data security, control, and the need for tailored solutions as AI evolves and handles increasingly sensitive data. This is driving the growing appeal of private clouds.

Although public cloud platforms offer a convenient entry point, they may not be the best fit for every organization, particularly those requiring dedicated, secure environments to support their AI initiatives. Therefore, once the decision to utilize a private cloud is made, the next key consideration becomes the implementation strategy: should the organization build its own solution or leverage a pre-existing offering?

Build versus buy

Protecting corporate IP and sensitive data requires careful consideration of the build-versus-buy decision when implementing a private cloud. While a DIY approach, leveraging proprietary and open-source tools, can be tempting for engineering teams with the relevant expertise, it's crucial to assess the long-term implications.

The total cost of a DIY private cloud goes beyond the initial hardware outlay. Building and maintaining this type of platform necessitates a dedicated team, which can often be too small to effectively manage the expanding complexity of the tools involved. Hidden costs emerge in scaling efforts, unpredictable maintenance, and the ongoing challenge of seamless integration. Before choosing this path, carefully consider the risks associated with these uncertainties.

Streamline your AI deployments with the ease of a public cloud, but with the control and predictability of a private cloud. Avoid vendor lock-in and unpredictable costs.

Driving business outcomes with AI

Unlock the long-term value of your AI investments with HPE Private Cloud AI, a turnkey private cloud solution co-developed with NVIDIA. This pre-integrated platform simplifies deployment with automated processes that take you from shipping crate in under eight hours, on average.[1] From this foundation, innovation takes off.

Read the Futurum report: HPE Private Cloud AI with NVIDIA AI Computing by HPE: Essential to Accelerating GenAI Industrial Transformation​

HPE Private Cloud AI's integrated software ecosystem empowers users of all skill levels. It provides no-code/low-code tools and automated accelerators for rapidly developing AI solutions, such as generative AI chatbots and productivity tools, as well as APIs, notebooks, and other advanced tools for experienced  developers. The platform streamlines the entire AI lifecycle, eliminating delays associated with resource acquisition and provisioning.

Figure 1. Low-code capabilities enable you to quickly build a generative AI chatbot using LLMs in just three steps with drag-and-drop components and pre-built templates.

Key capabilities

Accelerate your AI and generative AI initiatives with HPE Private Cloud AI's unified data platform. The integrated data lakehouse and global namespace provide a single point of access to all your data, simplifying data access and management. Effortlessly connect to a wide range of data types and sources with a single click, eliminating the complexity of custom integrations. With built-in security, governance, and access controls, your teams can focus on rapidly developing and deploying AI/ML solutions.

Figure 2. Unified Data Lakehouse accelerates AI/GenAI uses cases. Simplified access, broad data source connectivity, and built-in governance empower rapid development and deployment.

Empower your developers with a comprehensive AI platform. Experience instant access to a comprehensive suite of tools and services that streamlines the entire enterprise AI workflow, from development to deployment. Pre-configured notebook environments, featuring production-ready frameworks, streamline the development process for both experience and less experienced developers. Robust compliance, explainability, and security tools protect both data and models allowing your teams to build and deploy AI solutions with confidence.

Figure 3. Private Cloud AI offers streamlined role-based experience with pre-configured NVIDIA software and a rich selection of open-source AI/analytics tools, accessible instantly.

Reduce the risk and complexity of managing AI infrastructure. Automated processes across the AI lifecycle minimize manual effort and accelerate your time-to-value. Dynamic scaling ensures optimal performance and cost, automatically adjusting resources to meet your growing AI needs. Automated patching and updates bolster security and reliability, while built-in backup and recovery protect your critical AI assets and ensure business continuity.

 Figure 4. Automated patching and updates bolster security and reliability.

Ensure the smooth and efficient operation of your AI workloads with built-in AIOps and OpsRamp IT observability. This integrated approach provides a holistic view of your AI environment, with advanced monitoring and analytics delivering real-time insights into system performance and resource utilization. Intelligent automation proactively identifies and resolves potential issues before they impact production, minimizing disruptions and maximizing efficiency.

Empower your IT team with the self-service cloud experience of HPE GreenLake. Our centralized control plane simplifies AI infrastructure and workload management, while integrated IT Ops and AIOps automate routine tasks and enable predictive maintenance. This frees your team to focus on innovation and strategic initiatives that advance your business goals.

Summary

From data integration headaches to scaling challenges, building your own private cloud for AI can be costly and complex. HPE Private Cloud AI offers a turnkey solution, simplifying deployment and accelerating time-to-value. But is it the right choice for your organization? Our new analyst report, Unlocking the power of private cloud with NVIDIA AI Computing by HPE: A smarter approach, provides a comprehensive analysis of HPE Private Cloud AI versus the DIY approach. Download the report to make an informed decision.

Joann Starke
Hewlett Packard Enterprise

twitter.com/HPE_Ezmeral
linkedin.com/showcase/hpe-ezmeral
hpe.com/software

[1] Based on initial customer deployments from September through December 2024.