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. The partnership leverages Intel's 5th Generation Xeon processors together with Bud Ecosystem's inference optimization engine, Bud Runtime, to lower the total cost of ownership (TCO) for GenAI solutions without compromising performance or accuracy.
Riding the shift to SLMs on commodity hardware
As Generative AI gains mainstream traction, organizations are prioritizing cost-efficient AI deployments. The industry is shifting toward domain-specific Small Language Models (SLMs) running on commodity processors, away from reliance on expensive large language models powered by GPU infrastructure.
The collaboration is designed to help businesses capitalize on this trend — democratizing access to GenAI by eliminating the financial barriers that have hindered widespread adoption.
A proof of concept on Azure
The MoU outlines a Proof of Concept (PoC) that will test the performance of Bud Runtime on Intel-powered Azure Virtual Machines. The collaboration lets all three partners evaluate the scalability and flexibility of combining Bud Runtime and Intel-powered Azure VMs, ensuring 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. 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."
Jithin V.G — CEO, Bud EcosystemWhat Bud Runtime delivers
Bud Runtime is a GenAI serving and inference stack that significantly reduces both capital and operational expenditure for enterprises adopting Generative AI. Benchmark results show Bud Runtime can deliver up to 130% better inference performance in the cloud and 12× better performance on client devices, while reducing total cost of ownership by up to 55×.
It empowers enterprises to move to production-ready GenAI while ensuring compliance with AI guidelines and regulations, including those of the European Union and the White House's responsible AI framework.