AI continues to fuel demand for new networking technology and the vendors that build it.
Upscale AI, which emerged from stealth in September 2025 with a $100 million seed round, has raised an additional $190 million in a Series A-1 extension. Total funding now stands at $500 million, and its current valuation is $2 billion. The round was led by Premji Invest and includes new investors Nvidia, Salesforce Ventures, Seligman Ventures, and Temasek. Existing backers — Maverick Silicon, Mayfield, Prosperity7 Ventures, StepStone Group, and Tiger Global — also participated.
The Santa Clara-based company describes itself as a pure-play AI networking company focused on the backend networks that connect GPUs and XPUs for hyperscalers and neoclouds. Upscale builds AI networking hardware across two tracks. Scale-up networking connects GPUs and XPUs within a cluster. Scale-out networking extends connectivity across nodes.
Since the company emerged from stealth it has expanded its efforts, inking a partnership with Nvidia on SpectrumX Ethernet. Upscale has also announced that it is developing its own custom scale-up switch ASIC, code-named Skyhammer.
“The world that we see is going to be a heterogeneous AI compute, and we want to be a player in that heterogeneous AI compute by providing a network that supports Nvidia-based infrastructure as well as … other GPU and XPU vendors,” Rajiv Khemani, co-founder and executive chairman of Upscale AI, told Network World.
Skyhammer: Upscale’s purpose-built scale-up silicon
Skyhammer is Upscale AI’s flagship effort on the scale-up side of AI networking: a purpose-built switch silicon designed to connect GPUs and XPUs at very high speed inside AI systems.
Khemani said that unlike commodity data center chips repurposed for AI, Skyhammer is being developed specifically for AI scale‑up use cases and is tightly coupled to Upscale’s broader full‑stack strategy, which spans silicon, systems and software.
Khemani declined to share detailed timelines, but he said Upscale expects to reveal product details on Skyhammer later this year, with actual deployment synced to when GPU and XPU vendors are ready. “The Skyhammer product doesn’t work by itself,” he explained. “It works in conjunction with XPUs and GPUs, and so for us to be deployed, the XPUs and GPUs need to incorporate scale‑up capabilities to interoperate with us.”
Nvidia, Spectrum X, and strategic capital
Nvidia sits at the center of Upscale AI’s story, both as a technology partner and now as a strategic investor.
On the product side, Upscale has aligned its scale-out roadmap with Nvidia’s Spectrum X Ethernet platform to build AI‑optimized network fabrics that connect GPU and XPU nodes across the data center. The Spectrum X–based systems are expected to reach the market later this year, with Khemani noting that products are already in customer labs and are booked for early deployments.
That technical collaboration expanded into a capital relationship, with Nvidia joining Upscale’s latest funding round.
Software, token efficiency and what comes next
The goal for many organizations today is to optimize AI token usage. That’s a topic that is often referred to as ‘tokenmaxxing,’ and it’s an area where Khemani noted that networking has a role to play.
Upscale is building a full-stack offering that includes software for both large hyperscalers and emerging neocloud providers. Khemani emphasized that there is not a single right answer to the challenge of token efficiency. He sees it as workload-dependent, and changing as the industry moves from simple prompts to agents onto more complex loops and multi-step applications.
“I don’t think we have a choice other than to make sure that AI infrastructure is used in as optimal a fashion as it can,” Khemani said. “So, you have to build an infrastructure that is somewhat flexible to adapt to whatever AI applications require.”