"OPEA is an open-source framework developed by the Linux AI & Data Foundation"
As Nutanix joins (OPEA), we’re opening new doors for our partners and customers to embrace the future of Generative AI with confidence
To better understand the impact of this partnership, here’s a quick Q&A highlighting what OPEA is, why it matters, and how it benefits our partner ecosystem.
What is OPEA?
On the technical side, OPEA is an open-source framework developed by the Linux AI & Data Foundation. It helps build and assess enterprise-level GenAI solutions that are flexible, work with different providers, and can scale as needed.
It includes reusable building blocks like language models, data sources, and prompt tools, along with ready-made blueprints for common AI tasks such as chatbots and document summarisation. It also offers a four-step process to check the system’s performance, features, trust, and readiness for enterprise use.
In simple terms, OPEA makes it easier and faster to create secure, cost-effective, and reliable AI solutions that can run anywhere, from the edge to private and public clouds.
Why is the Nutanix–OPEA partnership important?
The partnership between Nutanix and OPEA is important because it helps businesses build and run AI solutions more easily and cost-effectively.
By combining Nutanix’s cloud platform with OPEA’s open and flexible AI framework, customers and partners can speed up their AI projects, use existing hardware to save costs, and keep their data secure. It also makes it easier to manage AI systems after they’re up and running, with tools to monitor performance and ensure everything works smoothly across different environments, whether on the edge, in private data centres, or in the cloud.
How does Nutanix’s involvement in OPEA benefit our partners?
Nutanix’s involvement in OPEA brings real value to our partners by making it easier to build and deliver AI solutions that are ready for the enterprise.
With access to an open and flexible AI framework, partners can use pre-designed blueprints, reduce infrastructure costs by leveraging existing hardware, and ensure that data remains secure and private.
This collaboration also helps simplify the deployment and ongoing management of AI workloads, making it easier to support customers across hybrid and multi-cloud environments while speeding up delivery and reducing complexity.
