# Upscale takes on AI networking silos with Token Fabric

> Source: <https://www.networkworld.com/article/4232707/upscale-takes-on-ai-networking-silos-with-token-fabric.html>
> Published: 2026-10-08 18:44:41+00:00

AI clusters depend on two types of networking. Scale-up networking connects accelerators inside a rack. Scale-out networking connects racks across the data center. A single AI job spans both, which is a challenge for many organizations that tend to treat the two as separate networks.

Networking startup Upscale today [introduced Token Fabric](https://upscale.com/blogs/upscale-introduces-token-fabric-the-industrys-most-comprehensive-standards-based-networking-portfolio-for-ai-factories) to bring the two together. The architecture combines the company’s own SkyFabriX scale-up silicon, scale-out systems built on Nvidia Spectrum-X Ethernet, and a common software layer for operations. General availability is planned for early 2027. Early-access and joint-validation programs are running now.

The announcement builds on two earlier milestones. Upscale, based in Santa Clara, Calif., [emerged from stealth in September 2025 with a $100 million seed round](https://www.networkworld.com/article/4060135/upscale-emerges-from-stealth-with-100-million-seed-and-plans-to-democratize-ai-networking.html). In June, it [raised an additional $190 million](https://www.networkworld.com/article/4188550/upscale-ai-readies-skyhammer-scale-up-networking-tech-raises-new-funding.html) and outlined plans for SkyHammer, its custom scale-up switch chip. SkyFabriX is based on that SkyHammer architecture. Nvidia, which supplies the Spectrum-X silicon, joined the June round. Upscale has now raised about $500 million and has more than 300 employees.

“If you look at compute, compute is ramping up on a rapid scale, and networking has fallen way behind,” Barun Kar, CEO of Upscale, told *Network World*.

Token Fabric is a combination of hardware and software for both scale-up and scale-out.

All three options draw on the same portfolio of silicon, systems and software. “Everything has to be integrated, so that’s where we come in,” Kar said. “We are vertically stacked.”

Token Fabric is built from the protocol layer up.

Upscale is extending existing protocols and does not replace them. Scale-up traffic uses ESUN and standard Ethernet/IP. Scale-out traffic uses standard Ethernet with RoCE, which carries remote direct memory access over Ethernet.

Upscale is also contributing to the open projects underneath the stack. They include SONiC, extensions of the Switch Abstraction Interface (SAI) for ESUN, the Ultra Ethernet Consortium (UEC) and UALink.

Software ties the two fabrics together. SkyOS abstracts the underlying hardware and provides a control plane across the cluster. SkyCMD exposes that control plane through one layer. Multiple network elements sit behind it, and any compute platform in a heterogeneous cluster can use it to control the network.

“Your operating system has to be lean, mean in order to be fast, flexible, and secure,” Kar said. “And then you have to have the orchestration layer on top to enable things like heterogeneous compute.”

Network teams have traditionally tracked packets, throughput, loss, and jitter. The question for an AI network is whether tokens are the right unit of optimization.

“I would say that’s the right thing,” Kar argued.

Kar noted that users pay based on tokens today. He named time to first token, tokens per second, tokens per dollar, and tokens per watt as the measures. Optimizing those measures requires networking, especially in clusters that scale to hundreds of thousands of accelerators.

There is, however, a bit of a gap with many networks today that makes it difficult to optimize for token operations. According to Kar, the main components of the gap are latency, bandwidth, and scale-up features in the silicon. On the software side, he said predictive analytics and telemetry keep machines running.

The other side of the challenge is optimizing the networking with agentic AI. To that end, Upscale has directly built agent-based operations into the platform.

“An agent is always looking at your network, trying to figure out whether your cables will fail or your optics will fail or if there’s congestion, and the agents are looking for ways around it,” Kar said.
