Red Hat and NVIDIA launch an innovative infrastructure specially designed for artificial intelligence agents

In 2026, the technological landscape evolves at a frantic pace, and artificial intelligence is now established as an essential pillar of business strategies. To respond to this transformation, Red Hat and NVIDIA have joined forces to launch an innovative infrastructure dedicated to artificial intelligence agents. This deep partnership aims to go beyond experimental stages to offer businesses a complete and secure solution capable of operating autonomous AI agents in demanding and regulated environments. This advance marks a major turning point in the industrial adoption of AI, with a technical foundation designed to combine power, governance, and compliance.

Autonomous AI agents represent the new frontier of business applications: these systems no longer just respond to specific queries but interact with various systems to accomplish complex tasks over time. Thus, the Red Hat AI Factory offering with NVIDIA combines Red Hat’s open-source software expertise with NVIDIA’s accelerated computing power to reshape IT infrastructures, particularly in hybrid cloud environments. The alliance addresses both performance and security issues, notably thanks to the integration of OpenShell and confidential computing technologies.

This redesigned infrastructure model is a targeted response to current business challenges, which seek to deploy agentic AI on a large scale while meeting increasing regulatory requirements. This collaboration reflects a vision where technological innovation is driven by open standards, centralized governance, and strong commitment to data protection.

A strategic partnership at the heart of the evolution of enterprise artificial intelligence

For several years, Red Hat and NVIDIA have collaborated to support the digital transformation of businesses through artificial intelligence. In 2026, their partnership reaches a new milestone with the launch of a specialized infrastructure for agentic AI. Autonomous AI agents, capable of making complex decisions and carrying out actions over time, require a platform adapted both in terms of performance and security.

This evolution is set within a context where traditional AI technologies are no longer sufficient to meet business needs, whether in advanced automation, personalized recommendations, or management of critical operations. The collaboration between Red Hat and NVIDIA opens an unprecedented path with a combined offering, integrating the Red Hat Enterprise Linux (RHEL) operating system optimized for NVIDIA architectures, deployment in hybrid cloud environments, as well as accelerated computing via NVIDIA’s high-end GPUs.

The Red Hat Summit 2026 was the opportunity to present these innovations, illustrating the deep integration of technologies such as NVIDIA Vera Rubin, a next-generation processor coupled with Rubin GPUs, designed to boost agentic AI and advanced reasoning. This hardware platform revolutionizes the way AI infrastructures are designed in enterprises. It also relies on open standards to ensure optimal compatibility and the flexibility required by organizations of all sizes.

To better understand the impact of this alliance, one must consider the very nature of artificial intelligence agents, which continuously evolve, massively exploit real-time data, and interact with a multitude of business applications. Raw performance must therefore be accompanied by fine governance and advanced security mechanisms, aspects at the core of the combined solutions offered by Red Hat and NVIDIA.

Autonomous artificial intelligence agents: deployment and operational challenge

Autonomous artificial intelligence agents differ from traditional conversational assistants by their ability to independently manage complex tasks, often interacting with multiple systems. These agents operate over extended periods, make decisions based on diverse data, and adapt in real time to their environment.

In the professional world, these agents become essential to automate processes, improve decision-making, or anticipate critical events. For example, in finance, they can continuously analyze stock market data flows to suggest or execute trading operations. In industry, they monitor production lines and react instantly to anomalies to minimize interruptions.

Red Hat AI Factory with NVIDIA thus relies on an architecture designed to meet this complexity. The introduction of OpenShell, an open-source execution environment developed by NVIDIA, paves the way for strict and transparent management of agents’ activities. OpenShell provides a framework that isolates each agent, clearly defines its access rights to resources and tools, and oversees all its interactions. This approach facilitates not only security but also regulatory compliance.

A crucial point is the ability to finely control agents through centralized governance. Companies can thus ensure that every action taken by an agent is traceable, controlled, and aligned with internal policies. This control is vital to meet new international standards and particularly European expectations regarding AI accountability and transparency.

This new execution model integrates seamlessly within hybrid infrastructures, allowing organizations to deploy AI agents both on their own data centers and in the cloud. This mix offers increased flexibility while ensuring that sensitive data remains under strict control. It is a pragmatic response to the digital sovereignty challenges faced by modern businesses.

Focus on OpenShell: the key to secure and governed agentic AI

OpenShell represents a significant advance for Red Hat and NVIDIA, as it offers a secure and isolated execution environment. This technology relies on an open-source base, allowing companies to adopt a transparent and adaptable model tailored to the specific needs of their sector.

Among its key features, OpenShell allows:

• Customized definition of access and resource usage rules for each AI agent.
• Precise routing of inferences, ensuring data flows are processed optimally and securely.
• Continuous monitoring of agents’ actions to prevent abnormal or non-compliant behaviors.

This scalable platform will soon integrate natively into the Red Hat ecosystem, offering simplified management of security policies directly at the infrastructure level, a critical point for large-scale deployment in complex hybrid cloud environments.

Technical advances at the heart of the Red Hat-NVIDIA AI infrastructure

The realization of this innovative infrastructure relies on a harmonious combination of hardware and software components designed to maximize performance while ensuring robustness and security. Red Hat Enterprise Linux (RHEL) for NVIDIA 26.01 is one of the software pillars of this infrastructure.

Optimized for NVIDIA Blackwell architectures, this operating system is crafted to fully exploit the capabilities of Rubin GPUs and the Vera Rubin processor. It guarantees rock-solid stability to enable production deployment of agentic AI while providing immediate support for the latest technologies (“Day 0 support”).

On the other hand, the platform incorporates advanced lifecycle management mechanisms for AI models through MLflow, which offers visibility over every step: from the user query to the agent’s final reasoning stage, allowing exhaustive auditing and tracing of their actions.

The Model as a Service (MaaS) service integrated into this new infrastructure allows developers easy access to a catalog of models, including those jointly validated such as NVIDIA Nemotron. This feature facilitates the rapid and flexible integration of AI models into business processes, significantly reducing the time between experimentation and deployment.

Comparative table of key technologies in the Red Hat-NVIDIA AI infrastructure

Component	Description	Main advantage
Red Hat Enterprise Linux 26.01	Operating system optimized for NVIDIA Blackwell architectures	Immediate support for advanced hardware for maximum stability and performance
GPU NVIDIA Rubin	Next-generation GPU specially designed for agentic AI	High computing power for simultaneous processing of thousands of agents
NVIDIA Vera Rubin Processor	Processor dedicated to advanced reasoning and AI agent management	Optimization of complex calculations and reduction of latency times
OpenShell	Isolated and secure execution environment for autonomous AI agents	Centralized governance and strict control of agents’ activities
MLflow	Tool for managing the lifecycle of AI models	Complete traceability, auditability, and visibility of AI processes

Enhanced security and governance adapted to regulatory requirements

With the exponential development of artificial intelligence agents, infrastructure security becomes a major priority. Protecting sensitive data and guaranteeing system integrity are unavoidable imperatives, especially in regulated sectors such as finance, healthcare, or public administrations.

The common platform from Red Hat and NVIDIA addresses these challenges with the integration of confidential computing via NVIDIA Confidential Computing. This technology, still in preview, allows confidential containers to run within Red Hat OpenShift, providing active protection to agents during their execution, even in case of compromise of other system components.

The so-called “zero trust” architecture underpins the entire security approach. It relies on several major components, such as SELinux for enhanced access control, compliance with FIPS standards, and NVIDIA DOCA hardware and software protections. Together, they create a hermetic environment where every interaction is validated and every access is controlled.

This secure infrastructure is also designed to facilitate regulatory compliance, particularly in light of the European regulation on artificial intelligence. Centralized governance, combined with the traceability offered by integrated tools, enables companies to audit all agents’ actions, thus ensuring full transparency towards authorities and stakeholders.

Main security levers in the Red Hat-NVIDIA AI infrastructure

• Complete isolation of AI agents thanks to OpenShell and confidential containers
• Zero trust architecture ensuring integrity even in case of breach
• Strict access controls reinforced by SELinux and FIPS policy
• Hardware protection of data during computation thanks to NVIDIA DOCA
• Continuous monitoring and full auditability of agents’ lifecycle interactions

Accelerating production deployment and maximizing AI return on investment

Beyond technical aspects, Red Hat and NVIDIA are also committed to facilitating the realization of AI projects in enterprises. Deploying autonomous AI agents in real environments indeed requires a high level of reliability, security, and compliance, but also a reduction in implementation timeframes.

To support these objectives, the two partners offer jointly validated AI models, as well as practical guides dedicated to advanced use cases – whether for Model as a Service, RAG (Retrieval-Augmented Generation) architectures, or RAFT (Reinforced Agent Fine Tuning) with proprietary data. These resources help technical teams structure, deploy, and efficiently maintain their AI workflows.

This results-oriented approach is also strengthened by the progressive standardization of tools embedded in Red Hat AI Factory with NVIDIA, simplifying integration into existing information systems and CI/CD pipelines. This standardization not only accelerates production deployment but also improves adaptability in the face of future technological evolutions.

For organizations, this translates into rapid access to proven technologies, reduced risks related to deployment, and better cost predictability. In a context where AI is a major source of competitiveness, these factors represent decisive strategic assets.

Key benefits for businesses adopting the Red Hat-NVIDIA infrastructure in 2026

Adopting this innovative infrastructure dedicated to artificial intelligence agents offers many advantages, summarized below:

• Increased performance: Optimal exploitation of NVIDIA Blackwell architectures to handle intensive AI workloads.
• Enhanced security: Data protection and isolation of operations even in sensitive environments.
• Simplified governance: Centralized rule management and full auditability thanks to OpenShell and MLflow.
• Hybrid flexibility: Deployment in cloud, on-premise, or addressing hybrid architectures.
• Accelerated time-to-market: Validated models and practical guides to reduce development cycles.

These advantages transform the approach to agentic AI, often perceived as complex and risky, into a mastered opportunity to quickly generate business value. They also make this type of AI agent accessible to the widest range of organizations, regardless of their size or sector.

Development prospects and expected innovations in enterprise AI

With this 2026 initiative, Red Hat and NVIDIA set the bar very high in building an infrastructure capable of supporting the next generation of AI agents. However, the innovation momentum continues, notably around several promising areas.

The next phases will focus on:

1. Extending confidential computing capabilities to cover new use cases and further strengthen security.
2. Improving isolated execution environments to optimize performance while maintaining full protection.
3. Expanding integrated MaaS models with an enriched catalog responding to specific sector needs.
4. Developing intelligent orchestration tools to facilitate multi-cloud deployment automation.

This roadmap reflects the firm will to make agentic AI a central component of enterprise computing, combining speed, security, and ease of use. For digital transformation actors, this vision is an invitation to integrate this technology into their medium- and long-term strategies, relying on strong partnerships like the one offered by Red Hat and NVIDIA.