Broadcom and Cisco tie AI factory deployment to workload needs

Broadcom Inc. and Cisco Systems Inc. unveiled a validated design combining VMware Cloud Foundation and Cisco Unified Computing System infrastructure to align AI factory deployment with workload requirements, enabling enterprises to size infrastructure from edge inference to large-model training. Sabina Anja, chief technologist at Broadcom's VMware Cloud Foundation Division, and Jeff Nichols, technical leader at Cisco, said the approach lets customers receive fully configured AI factories on-site, ready for use on day one and two, rather than requiring IT teams to act as perpetual AI infrastructure architects.

Broadcom and Cisco tie AI factory deployment to workload needs AI factory deployment is becoming a workload-sizing exercise rather than a custom infrastructure project. Enterprises need infrastructure spanning edge inference and large-model training. Broadcom Inc. and Cisco Systems Inc. are addressing that challenge with a validated design combining VMware Cloud Foundation and Cisco Unified Computing System infrastructure. It maps workloads to hardware, from processors for smaller models to graphics processing unit-dense systems, according to Sabina Anja https://www.linkedin.com/in/sabinaanja/ pictured, right , chief technologist, VMware Cloud Foundation Division, Broadcom. “When we came up with the VMware Private AI Cloud, which has VMware AI Factory under that, the whole idea was: How can we give customers a solution to this massive systems problem?” Anja said. “How can you get something that’s bespoke to your outcome and integrates the best in the market for it?” Anja and Jeff Nichols https://www.linkedin.com/in/jeffnichols916/ left , technical leader at Cisco, spoke with theCUBE Research’s Christophe Bertrand https://www.linkedin.com/in/christophebertrand/ and co-host Alison Kosik https://www.linkedin.com/in/alison-kosik-cfei-13579215/ at VMware Explore https://www.thecube.net/events/vmware/vmware-explore-2026 , during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed reducing deployment complexity while preserving hardware and location choices. Disclosure below. AI factory deployment shifts IT from builder to consumer Sizing begins with requirements for latency, response time and concurrent users. Cisco’s portfolio spans Unified Edge for local inference, AI POD configurations https://www.cisco.com/c/en/us/products/collateral/servers-unified-computing/ucs-x-series-modular-system/ai-pods-ds.html and the eight-GPU UCS C885A M8 for demanding data-center workloads https://siliconangle.com/2026/08/25/nvidia-cisco-rack-scale-ai-factory-cisconvidiaaifactory/ , according to Nichols. “Typically, what we do with AI workloads is we start with the workload itself, not the system,” he said. “So what are the requirements? Is the end user going to be doing inferencing? Are they going to be doing retrieval-augmented generation, fine-tuning or training?” VMware Cloud Foundation virtualizes hardware so customers can allocate processors or accelerators according to demand. With validated Cisco systems, AI factory deployment can arrive fully configured rather than becoming a continuing integration assignment. “Really, the philosophy behind the AI factory is that the end user doesn’t have to be in there, and the IT department doesn’t have to be a perpetual AI infrastructure architect or builder,” Nichols said. “They become AI consumers. The AI factories are shipped on-site, fully built, fully configured and, with VCF on top, they’re ready to go on day one and two.” Here’s the complete video interview, part of SiliconANGLE’s and theCUBE’s coverage of VMware Explore https://www.thecube.net/events/vmware/vmware-explore-2026 : Disclosure: TheCUBE is a paid media partner for VMware Explore event. 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