Rack-Scale Performance. Open by Design.
SkyHammer is designed to deliver deterministic, low-latency scale-up networking for synchronized AI workloads. Built from the ASIC up, it reduces communication bottlenecks across accelerators, memory, and storage — enabling large-scale training and inference to run faster, more efficiently, and with more predictable performance.
Everything AI Scale Demands. Nothing It Doesn't.
SkyHammer 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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Silicon, systems, and software engineered together from the ground up for AI scale-up workloads.
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Silicon, systems, and software engineered together from the ground up for AI scale-up workloads.
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Silicon, systems, and software engineered together from the ground up for AI scale-up workloads.
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Silicon, systems, and software engineered together from the ground up for AI scale-up 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 Up Advantage
See how SkyHammer stacks up against the legacy architectures holding AI infrastructure back.
Scale Up Advantage 1
Open by Design
Silicon, systems, and software engineered together from the ground up for AI scale-up 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 Up 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 Up 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 Up 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
