AI performance is decided by how fast accelerators talk to each other, to the network, and to the dies beside them. SNOVA designs, integrates and verifies that connectivity: engineering services and custom semiconductor IP for high-speed Ethernet, UALink, UCIe, PCIe and the silicon around them.
SNOVA works with semiconductor and system companies whose products depend on interface performance:
AI accelerator and fabless silicon companies building accelerators, DPUs, NICs and switches.
In-house silicon teams at cloud and AI infrastructure companies.
Semiconductor IP and EDA vendors expanding protocol coverage or validating their own portfolios.
Networking and data-center equipment OEMs navigating the transition to higher Ethernet speeds.
If verification is what stands between your interface subsystem and tape-out, that is the work we take on.
Model training and inference at scale are no longer bounded by raw FLOPS alone. They are bounded by how efficiently compute, memory and accelerators exchange data across three distinct layers:
Ethernet-based networking across racks and clusters, moving toward higher per-lane rates and UEC-aligned transport for AI traffic patterns.
Low-latency, memory-semantic fabrics connecting accelerators within a pod.
UCIe and Custom Chip-to-Chip & Die-to-Die links connecting chiplets inside a package.
Each layer has different protocols, different physical constraints and different failure modes. SNOVA works across all three.
What we cover, and what we do with it.
Single-channel 800G scaling down to 100G over 8 SerDes lanes. Dedicated 4-engineer team delivered full verification in 2.5 months.
Refactored DL environment, built UPLI and TL environments from scratch. Scaled to 6 engineers across 3 port configurations.
Two generations of interconnect up to 4 x 112G lanes with switchable Tx/Rx splits and multiple FLIT modes, verified by 6 to 7 engineers.
| Layer | Technology | Primary Problem | Typical Silicon | SNOVA Role |
|---|---|---|---|---|
|
Scale-out
|
Ethernet & UEC | Bandwidth, latency, reliability at scale | NICs, Switches | Design Verification |
|
Scale-up
|
UALink · UEC · ESUN · SUE-T | Efficient accelerator-to-accelerator links | AI Accelerators, Switch ASICs | Verification & Integration |
|
Die-to-die
|
UCIe · Custom Chip-to-Chip & Die-to-Die | High-density chiplet connectivity | Chiplets, Advanced SoCs | PHY Integration · Custom Chip-to-Chip & Die-to-Die verification |
|
Host I/O
|
PCIe (PCI-SIG) | High-performance host connectivity | CPUs, SoCs, controllers | Protocol & compliance verification |
|
Compute
|
RISC-V | Open, scalable compute architecture | CPUs, SoCs, accelerators | SoC integration & enablement |
| Edge AI | Real-time inference at the edge | Edge devices, NPUs | Optimization & integration |
RTL design, micro-architecture and optimization.
Custom IP architecture, RTL and IP hardening.
SystemVerilog, UVM, VIP and compliance testing.
Hardware validation, bring-up and real-traffic testing.
A defined deliverable, fixed scope, milestones and acceptance criteria. SNOVA owns delivery from requirements to completion.
Named engineers embedded in your workflow, tools and standups. Sustained engineering capacity to support your roadmap without adding permanent headcount.
IP architected and built around your specifications, with development, verification and integration support. Purpose-built for your silicon and application requirements.
When to use which fabric, and how memory-semantic load/store fabrics pair with loss-tolerant network transport.
Read Article →
What drives next-gen Ethernet and the physical-layer verification challenges across 224G-class signaling.
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Design trade-offs, verification strategies, and why compliance frameworks leave partner-die interop open.
Read Article →Tell us what you’re building and where the schedule risk is. Your first conversation is with an engineer who works on these protocols, not a pitch.
