Enfabrica Unveils Cost-Cutting EMFASYS to Revolutionize AI Data Centers with Nvidia's Backing

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Tuesday, Jul 29, 2025 10:00 am ET1min read
Aime RobotAime Summary

- Enfabrica launched EMFASYS, a cost-cutting AI data center solution backed by $260M in VC funding led by Nvidia.

- The system uses proprietary network chips to connect AI processors with cheaper DDR5 memory, reducing reliance on expensive HBM.

- Custom software optimizes data routing between chips and low-cost memory, enabling scalable AI capabilities without performance loss.

- Three major AI cloud clients already use the system, aiming to provide a sustainable alternative to HBM without full replacement.

Silicon Valley-based chip startup Enfabrica has unveiled a novel chip and software system aimed at tackling the memory cost issues plaguing AI data centers. On Tuesday, the company introduced EMFASYS, a solution designed to optimize memory cost efficiency within these centers.

Enfabrica has successfully raised $260 million in venture capital with the backing of tech giant

. The challenge it addresses lies in the high expenses associated with flagship AI chips from Nvidia and its competitors, such as . A significant portion of these costs arises not just from the computational chips themselves but from the expensive high-bandwidth memory (HBM) necessary for maintaining the data flow essential for high-speed computation. Companies like SK Hynix and supply these HBM chips.

The innovative Enfabrica system employs a proprietary network chip that facilitates direct connections between AI compute chips and devices equipped with DDR5 memory chips. Although DDR5 is slower than HBM, it offers a substantially more affordable option for data centers.

Enfabrica's co-founder and CEO, Rochan Sankar, emphasized that their custom software efficiently routes data between AI chips and abundant low-cost memory. This enables tech firms to expand chatbot and AI agent capabilities without compromising data center performance or facing prohibitive costs.

Sankar disclosed that the system is currently in use by three major "AI cloud" clients, whose identities remain confidential. He clarified that the aim is not to replace HBM entirely but to provide a cost-effective alternative, thereby preventing an unsustainable rise in expenses as AI technologies scale up.

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