Unlocking the next layer of AI adoption in the UK

Unlocking the next layer of AI adoption in the UK About the author Jonny Williams More like this Blog post Blog post Original podcast Original podcast Browse by channel Automation Artificial intelligence Open hybrid cloud Security Edge computing Infrastructure Applications Virtualization Share Red Hat has formed a collaboration with Great Wave AI to make AI more usable for organisations of all sizes. Red Hat has a bold vision to help enterprises bridge their existing world and the new world of AI: supporting any model, on any accelerator, on any cloud, powered by open source. At this year’s Red Hat Summit , we made dozens of announcements extending our AI portfolio and ecosystem partnerships. Since then, we are excited to have formed a collaboration with Great Wave AI, a UK-based provider of an agentic generative AI (gen AI) platform. Together we aim to combine the scale, security features and flexibility of Red Hat AI with Great Wave’s “consumption layer” for multi-agent orchestration, making AI more usable for organisations of all sizes. This collaboration provides Red Hat customers with the ability to add an agentic layer on top of our enterprise-ready open source AI platforms, making it easier for them to tailor AI capabilities to their organization. Why AI orchestration? I recently had the opportunity to catch up with Jack Perschke, co-founder and chief executive officer of Great Wave AI, and discuss some of the trends shaping AI at the moment and what the collaboration means for both our companies. According to Jack, large language models (LLMs) are “like crude oil” in that they’re valuable, but need refinement to become usable products. Great Wave acts as the refinery turning raw model capability into fit-for-purpose tools, using their choice of hosting provider or LLM vendor. Jack explains, “Our platform makes it easier to switch between models, test applications with new models and host your own to meet specific security needs. In an era where prompts and responses can’t be encrypted inside the model itself, the safest option is often running it in your own environment. Red Hat makes this possible.