Red Hat announced on May 12 significant updates to its Red Hat AI portfolio, introducing new capabilities aimed at simplifying the development and deployment of agentic workflows for organizations looking to scale artificial intelligence across their infrastructure.
The company said these advancements are intended to help bridge the gap between experimental AI projects and production-grade operational control. By providing a unified platform, Red Hat aims to support both builders and operators with tools that maintain security, efficiency, and governance for modern enterprise needs.
Central to the announcement is Red Hat AI 3.4, which includes Model-as-a-Service (MaaS) for streamlined model access and tracking, as well as AgentOps tools designed for managing agents from development through production. The release also features prompt management and an evaluation hub powered by MLflow technology for experiment tracking and artifact management in both generative and predictive AI scenarios. Additional safety measures include automated testing using technology from Chatterbox Labs and the Garak project.
Joe Fernandes, vice president and general manager of the AI Business Unit at Red Hat, said: “The agentic era represents an evolution of our platform from running traditional applications to powering intelligent, autonomous systems. We are defining the open standard for how the enterprise executes AI. By providing a hardened, metal-to-agent foundation for AI inference, MaaS and AgentOps, Red Hat provides the operational assurance organizations need to innovate at scale while maintaining rigorous control.”
Other industry partners commented on their collaborations with Red Hat during this launch. Urvashi Chowdhary of CoreWeave said: “CoreWeave’s collaboration with Red Hat is grounded in a shared commitment to openness and delivering a high-performance inference foundation that allows enterprises to scale their most complex AI workloads.” John Fanelli of NVIDIA added: “Autonomous, long running agents in the enterprise demand a new level of infrastructure control and security to ensure trustworthy operations at scale…Red Hat AI Factory with NVIDIA provides a unified, open source-driven foundation that gives developers and operators the governance and confidence necessary for the agentic future.”
According to details provided by Red Hat during its Summit event in Atlanta, new features include advanced distributed inference capabilities supporting multiple Kubernetes services such as CoreWeave and Azure; identity-based governance using cryptographic identity management; multi-layered safety via adversarial scanning; production-ready observability through MLflow integration; hardware flexibility including support for NVIDIA Blackwell GPUs; automated experiences like AutoRAG; as well as availability on managed clouds including IBM Cloud.
Red Hat stated that version 3.4 will be available later this month.
