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AI infrastructure startup Mueon raises 65 million dollar Series A

Hardware1 min read

In brief

US-based Mueon has raised 65 million dollars in a Series A round led by Maverick Silicon, with Intel Capital, Wellington Capital and IQT among the participants. The company will use the funding to grow its engineering team and develop its Cubelet system, which aims to cut energy use and cost in data center servers.

  • 65 million dollar Series A led by Maverick Silicon
  • Intel Capital, Wellington Capital, IQT and others participated
  • Cubelet: server architecture stacking compute and memory vertically
  • Integrates power delivery, interconnect and thermal control
  • Supports GPUs and Arm-based processors
  • Funding goes to engineering, design and software development

Mueon closes 65 million dollar round

US-based AI infrastructure company Mueon has closed a 65 million dollar Series A round. Maverick Silicon led the round, joined by Intel Capital, Geodesic Alliances Fund, Oregon Venture Fund, M-Ventures, Wellington Capital, IQT and Defined.

Founded in 2025 by Wilfred Gomes and Jack Hwang, the company said the new funding will go toward expanding its engineering team, advancing the design of its Cubelet system and building software that lets customers run AI applications on its hardware.

How Cubelet works

In conventional servers, compute and memory components sit side by side. Mueon's Cubelet system stacks them vertically. The goal is to shorten the data transfer distance between components, boosting processing speed while cutting energy consumption.

Cubelet is not just compute and memory; it also includes the power delivery, interconnect and thermal control hardware servers need. The system can support different chip types, including GPUs and Arm-based processors.

Why it matters

One of the biggest bottlenecks in AI systems is the heavy demand for compute power and the heat hardware generates. Mueon aims to address these problems with its architecture, making data center servers run more efficiently and at lower cost. Its systems are designed for AI applications and large-scale data center workloads.

Why it matters

As AI's energy and cost burden grows, a new player betting on data center hardware is worth watching to understand where the industry is heading.

Sources

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