Bud Ecosystem, Intel, and Microsoft have entered into a Memorandum of Understanding (MoU) to enable cost-effective Generative AI deployments accessible to everyone through the Azure cloud. This partnership will leverage Intel’s 5th Generation Xeon processors along with Bud Ecosystem’s innovative inference optimization engine, Bud Runtime, to lower the total cost of ownership (TCO) for GenAI solutions without compromising performance or accuracy.

As Generative AI continues to gain mainstream traction, organizations are prioritizing cost-efficient AI deployments to meet their objectives. Consequently, the industry is shifting towards domain-specific Small Language Models (SLMs) running on commodity processors, moving away from the reliance on expensive large language models (LLMs) powered by GPU infrastructure. This collaboration is designed to help businesses easily capitalize on this trend, democratizing access to Generative AI by eliminating the financial barriers that have hindered its widespread adoption.

The MOU outlines a Proof of Concept (PoC) that will test the performance of Bud Runtime on Intel-powered Azure Virtual Machines (VMs). The collaboration will allow all three partners to evaluate the scalability and flexibility of combining Bud Runtime and  Intel-powered Azure VMs, ensuring that AI workloads benefit from the optimized hardware and inference software combination on a trusted cloud infrastructure.

“We are thrilled to collaborate with Intel and Microsoft in this collaboration,” said Jithin V.G, CEO of Bud Ecosystem. “Our mission is to democratize access to GenAI by commoditizing it. With Intel’s cost-effective hardware and the power of Azure cloud, we are confident this collaboration will empower businesses worldwide to harness the full potential of AI through Bud Runtime”

Bud Runtime is a GenAI serving and inference stack that significantly reduces both capital and operational expenditures for enterprises adopting Generative AI. Benchmark results show that Bud Runtime can deliver up to 130% better inference performance in the cloud and 12x better performance on client devices for GenAI applications, while reducing total cost of ownership by up to 55X. It empowers enterprises to transition to production-ready GenAI solutions, all while ensuring compliance with AI guidelines and regulations, including those set by the European Union and the White House’s responsible AI framework.