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Products & documentation Red Hat AI
A platform of products and services for the development and deployment of AI across the hybrid cloud.
Red Hat AI Enterprise
Build, develop, and deploy AI-powered applications across the hybrid cloud.
Red Hat AI Inference
Optimize model performance with an integrated stack for fast, consistent, and cost-effective inference at scale.
Red Hat Enterprise Linux AI
Develop, test, and run generative AI models to power enterprise applications.
Red Hat OpenShift AI
Build and deploy AI-enabled applications and models at scale across hybrid environments.
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AI partners
Use case
Agentic AI with Red Hat AI
Intelligent automation for the enterprise
Agentic AI describes software systems capable of independent reasoning, planning, and tool execution. With the goal of carrying out complex tasks with limited supervision, it acts as an intelligent orchestrator of the tools you already use.
Red Hat® AI enables organizations to control how their agents behave, what they can access, and how they interact with data, tools, and enterprise systems in production environments.
Scale governed and observable AI agents across your enterprise with Red Hat AI.
Augment your workflow by automating repetitive or time-consuming tasks at scale.
Control agent behavior in production with guardrails, identity, and Human-in-the-Loop checkpoints.
Connect your agent to APIs, data, and enterprise systems with controlled access and policy enforcement.
What is AgentOps?
AgentOps (agent operations) provides the framework to monitor the “brain” of an AI as it makes decisions in real time. It makes sure your autonomous agent remains an asset rather than a liability by providing:
- Identity and control: Make sure agents operate with clear identities and permissions to access tools.
- Safety guardrails: Keep autonomous agents on track, within budget, and running efficiently.
- Real time insights: Gain transparency into how agents think and act with observability tools.
- Managed creativity: Balance inventive problem solving with the oversight needed for stability.
- Lifecycle management: Manage the full agent lifecycle with isolated sandboxes and deep tracing.
What you can do
Agentic AI uses large language models (LLMs) and tools to build on the power of generative AI (gen AI). It works by connecting to and communicating with tools to perceive, decide, and orchestrate a whole automated task to achieve a defined goal.
Each use case relies on controlled access to data, tools, and decision-making, so that agents operate within defined policies.
Financial watchdog
Agents monitor thousands of daily transactions and flag for fraud or policy violations. They ingest data, cross-reference it with internal rules, and alert human reviewers to suspicious activity.
Autonomous helpdesk helper
Agents reproduce bugs in a sandbox, write potential fixes, and run tests. Once a solution is verified, a human developer steps in to review code and approve deployment.
Supply chain supervisor
An agentic system monitors weather, strikes, and port congestion. It alerts teams to potential delays and calculates the financial impact of re-routing.
Content researcher
Agents scan news stories, academic papers, and social trends to compile daily briefings. Key insights are summarized to help teams stay ahead of industry shifts.
Personalized onboarding guide
An agent guides new hires through documentation, setup, and training. It answers specific questions and schedules introductory meetings based on the employee’s role and department.
Regulatory compliance monitor
Agents continuously track changes in global trade laws and environmental regulations. They analyze how new rules affect current operations and flag specific areas where the company needs to adapt.
Pricing strategist
Agents monitor competitor pricing and market demand in real time. They suggest price adjustments to maintain a competitive edge while protecting profit margins.
Healthcare records coordinator
Agents assist staff by organizing patient data and flagging missing lab results or conflicting medication.
Sentiment responder
Agents track brand mentions across platforms and synthesize a summary to gauge public mood. They escalate crisis-level complaints to the PR team for immediate action.
233% ROI with Red Hat AI
A Forrester Consulting study, commissioned by Red Hat, found that a composite organization—based on current Red Hat AI customers—realized an ROI of 233% by deploying Red Hat AI.1
Learn how it works
You choose the model, infrastructure, and cloud. We bring optimized performance, cost-efficiency, and built-in control over how models and agents are deployed and used.
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Deploying Agentic AI in production. Video duration: 2:14
Features
Learn how Red Hat simplifies the journey to intelligent automation.
Safeguard your ecosystem with end-to-end visibility
Gain end-to-end visibility and control over agent behavior, data access, and system interactions. Monitor how agents act across tools, enforce policies, and maintain traceability in production environments.
Govern with confidence using powerful control mechanisms
Build confidence in autonomous agents with robust monitoring, explainability, and control mechanisms. Take charge of how agents operate with identity-based access, policy enforcement, and guardrails.
Manage the complete agent journey from start to finish
Operationalize, control, and manage each step of an agent’s lifecycle, from initial development to retirement.
Scale your AI fleet with optimized performance
Use tools like distributed inference, llm-d, and vLLM to help manage the memory and compute requirements necessary to run a fleet of agents.
Connect agents to your data with standardized frameworks
Create a 2-way connection and standardized form of communication between AI agents and your data with Model Context Protocol (MCP) and retrieval-augmented generation (RAG) components.
Accelerate production using a centralized tool registry
Discover, share, and reuse vetted models, tools, and connectors with a centralized catalog and registry while maintaining consistency and reducing friction from development to production.
Your vendors are your choice
We work with software and hardware vendors and open source communities to offer a holistic AI solution.
Access partner products and services that are tested, supported, and certified to perform with our technologies.
What's next?
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Talk to a Red Hatter
1 Forrester Consulting study, commissioned by Red Hat. “Forrester Total Economic Impact™ Of Red Hat AI." February 2026.
