What Does Astera Labs Make? The Chips Wiring Every AI Server Rack
Astera Labs doesn't make GPUs. It makes the connectivity chips that let hundreds of GPUs, CPUs, and memory modules talk to each other inside an AI server rack. Here's what that means and who's buying it.
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An AI server rack isn't one chip, it's hundreds of them: GPUs, CPUs, network cards, and memory modules that all need to move data between each other fast enough to keep an expensive GPU from sitting idle. Astera Labs makes the retimer and fabric-switch chips that handle that job, and its silicon now ships inside NVIDIA's flagship AI platforms.
The short answer
Astera Labs occupies a specific niche in AI infrastructure:
- What it makes: PCIe and CXL smart retimer and fabric-switch chips that connect GPUs, CPUs, and memory inside a server rack.
- Who buys it: NVIDIA uses Astera Labs' Aries retimers and Scorpio fabric switches in its HGX and Blackwell platforms; AMD uses similar chips in its EPYC and Instinct lines.
- Who builds the silicon: TSMC fabricates Astera Labs' chips, and Synopsys supplies the design software used to create them.
The full interactive map is on Astera Labs's supply chain page.
Why connectivity chips matter in an AI rack
A GPU is only as fast as the data it can access. If the connection between a GPU and its memory or its neighboring GPUs is too slow or unreliable, an expensive accelerator ends up waiting instead of computing. Astera Labs' retimers clean up and extend high-speed PCIe and CXL signals over the physical distances inside a rack, and its Scorpio fabric switches route that data between components. It's unglamorous plumbing, but AI racks don't work without it.
Who's buying it
NVIDIA deploys Astera Labs' Aries retimers and Scorpio switches inside its HGX and Blackwell AI server platforms, putting Astera Labs' silicon directly in the path of the most in-demand AI hardware on the market. uses the same category of connectivity chips across its EPYC server processors and Instinct AI accelerators, giving Astera Labs exposure to both of the leading AI compute platforms rather than a single customer.
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