Client: RedHat UK
Format: E-Book
Size: 531 KB
Language: English
Date: 11.02.2026
Maximize AI innovation with open source models
From personalized customer experiences and automated content creation to enhanced decision support, generative AI helps businesses streamline processes, increase productivity, and explore new possibilities. By investing in innovative AI solutions, enterprise organizations can strengthen their ability to navigate complexity, respond to shifting demands, and achieve strategic goals.
However, for many enterprises, realizing the full potential of generative AI technologies presents challenges. Proprietary large language models (LLMs) come with high license costs and require extensive hardware resources for both training and inferencing, making them expensive to deploy and maintain within enterprise IT environments. Training and tuning LLMs for specific customer and industry use cases can be difficult when developers and organizational subject matter experts—who fully understand the application and business requirements—lack the necessary specialized data science expertise. And proprietary, confidential data stored across complex hybrid cloud environments—including private datacenters, public cloud resources, and edge deployments—can make it hard to train generative AI models effectively, especially when regulatory requirements limit data movement between locations.
Red Hat offers a simplified approach that makes generative AI accessible to developers and domain experts across enterprise organizations. With Red Hat® AI, you can efficiently train and run generative AI models on production server deployments, so your teams can progress rapidly along their AI journeys without unnecessary complexity
However, for many enterprises, realizing the full potential of generative AI technologies presents challenges. Proprietary large language models (LLMs) come with high license costs and require extensive hardware resources for both training and inferencing, making them expensive to deploy and maintain within enterprise IT environments. Training and tuning LLMs for specific customer and industry use cases can be difficult when developers and organizational subject matter experts—who fully understand the application and business requirements—lack the necessary specialized data science expertise. And proprietary, confidential data stored across complex hybrid cloud environments—including private datacenters, public cloud resources, and edge deployments—can make it hard to train generative AI models effectively, especially when regulatory requirements limit data movement between locations.
Red Hat offers a simplified approach that makes generative AI accessible to developers and domain experts across enterprise organizations. With Red Hat® AI, you can efficiently train and run generative AI models on production server deployments, so your teams can progress rapidly along their AI journeys without unnecessary complexity
