Artificial intelligence (AI) at Red Hat

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Develop and deploy AI solutions across the hybrid cloud.
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Implement enterprise-wide automation.
Discover resources and tools to help you build, deliver, and manage cloud-native applications and services.
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Thousands of innovators, working together, accelerate AI possibilities faster than any one vendor ever could. With our open source approach, you get both rapid innovation and complete control over every layer of your AI strategy. Your data stays yours, your models serve your specific needs, and your deployment decisions remain entirely in your hands.
Introducing Red Hat® AI Factory with NVIDIA
Deep dives, demos and an unveiling of Red Hat AI 3.6
Automate AI red teaming: Large language model risk identification and mitigation
Open telco AI: Training a model for an industry
llm-d flow control: Priority queuing for shared GPU inference
How AI observability works with MLflow
More Developer blogs
Offer ends December 31, 2026.
Red Hat commissioned Forrester Consulting to conduct a Total Economic Impact™ (TEI) study and examine the potential return on investment (ROI) enterprises may realize by deploying Red Hat AI.
After interviewing Red Hat AI customers, the analysis found that a composite organization realized an ROI of 233% over 3 years, representing a total value of more than triple their initial investment.1
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What’s new and what’s next
Upcoming Livestream: December 10 at 11 AM EST
Join Red Hat AI leaders to hear the latest advancements in Red Hat AI. Catch our next livestream and access previous episodes on demand.
Hear the latest developments in vLLM from the team at UC Berkeley and Red Hat.
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Build your AI skills with hands-on resources for practitioners, or strengthen your decision making with AI knowledge resources.
See how LLM Compressor increases inference efficiency.
Run AI models in cloud development environments.
Build a simple agentic AI server with MCP.
See what open source AI looks like for developers.