Open Ethernet Fabrics
Upscale AI delivers open, interoperable Ethernet systems built on NVIDIA Spectrum-X switch silicon and a SONiC-based network operating system. Designed for heterogeneous AI clusters, these systems connect accelerators, memory, and storage into a high-performance fabric for distributed training and large-scale inference.
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Everything AI Scale Demands. Nothing It Doesn't.
Scale Out gives AI infrastructure teams the performance they need and the freedom to build without limits.
Open.
Build heterogeneous clusters with any hardware combination — no reengineering, no ecosystem constraints.
Performance .
As AI evolves, your network evolves with it — no costly overhauls, no starting over.
TCO
Open standards mean competitive hardware choices, reduced total cost of ownership, and infrastructure that grows without a full rebuild.
About the product
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Scale Out
Silicon, systems, and software engineered together from the ground up for AI scale-out workloads.
Scale Out 2
Silicon, systems, and software engineered together from the ground up for AI scale-out workloads.
Scale Out 3
Silicon, systems, and software engineered together from the ground up for AI scale-out workloads.
Performance That Speaks for Itself
SkyHammer is engineered for the performance demands of large-scale AI training, built to keep thousands of accelerators in sync with the precision and consistency modern AI infrastructure requires.
$300M
Total Funding Raised
100B
Projected AI Networking Market by 2030
The Scale Out Advantage
See how SkyHammer stacks up against the legacy architectures holding AI infrastructure back.
Scale Out Advantage 1
Open by Design
Silicon, systems, and software engineered together from the ground up for AI scale-out workloads.
Ecosystem Constraints
Legacy networking solutions were designed for a pre-AI world, forcing infrastructure teams to work around architectures never built for scale-up AI workloads.
Scale Out Advantage 2
Purpose-Built for AI
Silicon, systems, and software engineered together from the ground up for AI scale-up workloads.
Retrofitted Architecture
Legacy networking solutions were designed for a pre-AI world, forcing infrastructure teams to work around architectures never built for scale-up AI workloads.
Scale Out Advantage 3
Full Stack. Fully Integrated.
Silicon, systems, and software engineered together from the ground up for AI scale-up workloads.
Fragmented Stack
Point solutions from multiple vendors create integration challenges, specialized engineering requirements, and infrastructure that's hard to scale.
Scale Out Advantage 4
Shaping the Standards
As an active participant in UEC, UALink, and SONiC, Upscale AI isn't just compliant with open standards. We're helping define them.
Dependent on One Vendor
Proprietary ecosystems mean limited hardware choices, higher costs, and infrastructure tied to a single vendor's roadmap.
News, Insights, and
Industry Perspectives
High-Performance Open Standards-Based Networking Fabric to Drive Growth for Generative AI Datacenters
Generative AI training and inference workloads are becoming increasingly complex, involving enormous datasets and requiring significant computational resources to generate, fine-tune, and deploy AI models.
Nov 29, 2024
Questions & answers
