The infrastructure where AI grows and operates under your control

Develop and integrate AI projects on a composable technology stack: from GPU workloads to API-first and serverless services for inference, always with control over data, governance, compliance, and costs.

TALK TO AN EXPERT Find out more on the technology

From PoCs to production: the architectural requirements of AI

In recent years, companies have started experimenting with artificial intelligence within applications and platforms through proof of concepts and isolated prototypes. The transition to production, however, often proves more complex than expected, as critical issues emerge that must be addressed before reaching an operational release.

These critical issues include security in handling data processed by AI, economic sustainability in the medium and long term, and more generally, the ability to design an infrastructure capable of evolving over time, suitable for integrating different models and supporting high workloads. In Europe, these aspects are intertwined with requirements of jurisdiction, data localization, and regulatory compliance, requiring informed architectural choices from the earliest design stages.

High-performance compute

Scalable resources for training and inference of AI models, with consistent performance and control over processing.

Multi-model integration

A programmable layer through APIs to integrate AI models into applications and automate business processes.

Governance and compliance

Structured management of data and models, in line with regulatory requirements and security standards.

Control over costs and technologies

Transparent pricing models to plan spending and maintain flexibility to evolve over time.

The foundations for Artificial Intelligence under control

Adopting Artificial Intelligence means making decisions not only about the model to use, but about the entire technological ecosystem that supports it: infrastructure, application integration, security, and governance.

Aruba Cloud provides a European cloud infrastructure that enables the development of agile and scalable AI projects while maintaining control, compliance, and architectural flexibility.

Control and open stack

When AI enters business processes, maintaining control over data, models, and runtime is essential. With Aruba Cloud, you design hybrid or private architectures, integrating external components without constraints. The open and composable stack allows you to evolve models, deployments, and resources over time, without lock-in and without complex redesigns.

Data governance

Governing AI means controlling the data lifecycle: collection, access, processing, and storage. With Aruba Cloud, you can keep data residency in Italy or the EU, defining access and traceability policies aligned with business processes and current regulations.

Compliance by design

In both regulated and non-regulated contexts, compliance by design is not a final check but a design requirement. Aruba’s infrastructure is based on proprietary certified European data centers, enabling the creation of architectures compliant with regulatory and security requirements from the earliest stages of the project.

Predictable costs

AI projects can grow rapidly and make cost control complex. For this reason, Aruba Cloud offers a transparent and predictable pricing model, allowing you to plan and manage costs over time by choosing when to use dedicated resources and when to use consumption-based resources.

The Aruba stack for Artificial Intelligence

The Aruba Cloud offering is built on European infrastructure foundations (interconnected data centers, cloud, and connectivity) and is organized as a complete and modular technology stack, enabling companies to choose the level of control and integration best suited to their AI projects and to meet different requirements such as performance, scalability, data residency, and compliance.

Compute layer

On-demand GPUs for Kubernetes, dedicated GPU servers, and Private Cloud with GPUs to build scalable, high-performance AI environments.

Inference & integration layer (API-first)

Serverless AI endpoints to integrate pre-trained models into applications without directly managing GPUs or containers.

Tools layer

Services (text, translation, summarization, document classification) and components (Knowledge Base Assistant, RAG, and document intelligence) ready to use.

Deployment model

Private AI with dedicated environments for regulated workloads or those with isolation requirements.

AI-Ready Compute: GPU power for training and inference

The infrastructure layer (IaaS) provides direct access to the computational resources needed to design and manage high-performance AI environments, while maintaining full control over them.

GPU on-demand

Use computing power only when needed. Ideal for:

  • development and test environments;

  • experimentation on new models;

  • inference with intermittent workloads;

  • Kubernetes-orchestrated clusters.

Find out more on GPU on-demand

Dedicated GPU servers

If the workload is stable and continuous, variable capacity and costs can become a risk. Dedicated GPU servers ensure consistent performance and reserved resources, and are ideal for:

  • continuous training;
  • inference with constant 24/7 workloads;
  • ML pipelines in production.
Find out more on dedicated servers with GPU

Private Cloud with GPUs

In the presence of compliance, governance, or integration constraints with corporate policies, you can build AI environments on Private Cloud with GPUs, either with managed solutions or in full autonomy. Ideal for needs such as:

  • workload isolation;
  • structured access management;
  • integration with existing Enterprise infrastructures.
Find out more on VMware HPC Find out more on Metal Cloud Infrastructure

Open and multi-model Programmable AI Platform to integrate AI into applications

This layer (PaaS) represents the programmable layer of the stack. The platform enables the integration of AI functionalities into business applications through managed services and optimized APIs, while maintaining data governance and cost predictability.

AI Endpoints

AI Endpoints allow you to use AI models via APIs without directly managing runtime or GPU infrastructure, with the advantage of:

  • integrating AI into applications more quickly;
  • automatically scaling inference capacity;
  • controlling consumption with a pay-per-use model.

AI Tools

Pre-configured services to quickly integrate targeted functionalities into apps, chatbots, assistants, and business workflows, while still maintaining control over flows and data. Ideal for tasks such as:

  • text generation and summarization;

  • document classification;

  • automatic translation;

  • assistants based on RAG and knowledge bases.

AI applications integrated into Aruba services

The stack also includes an application layer (SaaS) where Artificial Intelligence capabilities are already integrated into Aruba services to enhance the experience and simplify operational activities in various areas, for example:

Intelligent features integrated into services such as Webmail, PEC, and Electronic Invoicing.

Tools for creating and managing digital presence supported by AI.

Features to assist with content generation and document management.

Private AI: dedicated environments for sensitive data and regulated sectors

This layer is designed for organizations that handle sensitive data and must comply with strict requirements for data residency, access control, and compliance without compromising performance and scalability. Aruba Cloud offers Private AI environments based on dedicated infrastructures with:

Isolated infrastructure

Reserved resources designed for workload separation and isolation of environments across tenants, teams, and application domains.

Governance and access control

Private AI environments integrate access policies and traceability systems aligned with business processes and audit requirements.

Custom architecture and deployment

Support in choosing the most suitable platform and deployment model for each workload, combining managed and self-hosted solutions.

Design your AI architecture with Aruba

Integrating Artificial Intelligence into business processes requires a solid and flexible technological foundation. At Aruba Cloud, we are ready to build the ideal AI architecture with you by selecting the technologies best suited to your project: on-demand GPUs or dedicated resources, inference services via APIs, private or hybrid cloud solutions, up to the design of a tailor-made infrastructure for your organization.

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Frequently asked questions about Artificial Intelligence for businesses

  • Aruba Cloud’s AI infrastructure offers GPUs for training and inference available on-demand or as dedicated resources. You can choose between shared environments or reserved GPU servers based on performance, workload continuity, and project requirements, from NVIDIA RTX 4070, RTX 4080, and L40S up to higher-end GPUs for custom projects.

  • AI APIs operate on European cloud AI infrastructure. All data remains in Aruba data centers located in Italy, under the control of the data-owning organization, and can be managed with access, traceability, and governance policies defined by the application architecture.

  • Yes. Aruba Cloud infrastructure supports on-demand GPU scalability, allowing you to increase or decrease computing capacity for training and inference based on the workloads of your AI environment.

  • Yes. Some Aruba Cloud services integrate AI features for automation, document management, and content generation, allowing you to use Artificial Intelligence without directly managing infrastructure or GPUs.