MaaS: Move from a token consumer to sovereign AI

As organizations move AI workloads into production, the cost and complexity of serving large models at scale quickly become critical concerns. Traditional model-serving stacks are often tied to specific hardware, frameworks, or proprietary platforms, creating expensive lock-in and limited flexibility. Model-as-a-Service (MaaS) with the Red Hat® AI platform solves this by providing an open, modular, and vendor-neutral way to deploy and operate models across hybrid cloud environments. In this live demo session, our Red Hat experts will walk through how to: - Serve and scale models with virtual large language models (vLLM), llm-d, and Red Hat AI’s Model-as-a-Service. - Run any model on any accelerator or cloud with efficient throughput and intelligent routing. - Standardize deployment workflows for platform teams. - Optimize GPU utilization and reduce serving costs. - Expose models as secure APIs while maintaining full operational control. Join us to gain a clear understanding of how to run models cost-effectively and at scale—without vendor lock-in.