Red Hat AI 3.4 helps organizations develop, monitor and manage AI agents in enterprise environments. The platform provides model governance, AgentOps capabilities and security controls for data centers, cloud platforms and Kubernetes infrastructure.
Red Hat has announced Red Hat AI 3.4, a platform designed for organizations seeking to move from experiments and pilot projects to the controlled use of AI models and agents in production.
The platform introduces a unified Model-as-a-Service capability. Developers can access approved models, while administrators can monitor resource consumption, access rights and compliance with internal policies.
New AgentOps capabilities enable organizations to monitor the entire lifecycle of AI agents. They can track agent actions, reasoning stages and the tools used during each process. Cryptographic identity helps determine which entity performed a specific operation.
Red Hat AI 3.4 also includes tools for evaluating models and agents in terms of quality, accuracy and safety. The platform supports testing against prompt injection, jailbreak attempts and other unwanted behaviors.
The solution is designed to operate across on-premises data centers, cloud environments and Kubernetes infrastructure.
BTS PRO supports the implementation of Red Hat platforms in hybrid environments, including Red Hat OpenShift integration, operational automation and the preparation of infrastructure for AI applications. The focus is on data control, security and gradual scalability.
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