NeuReality, an Israeli startup that develops high performance AI computers for cloud data centers and edge nodes, raised $35 million in a Series A funding round led by Samsung Ventures, Cardumen Capital, Varana Capital, OurCrowd, and XT Hitech. The raise brings the company’s total funding to date to $48 million.
NeuReality was established in 2019 by CEO Moshe Tanach, VP of Operations Tzvika Shmueli, and VP VLSI Yossi Kasus.
“This investment is another sign of confidence in the talent and innovation that NeuReality and the Israeli tech industry offer the world,” stated Moshe Tanach. “The high-profile investors in our Series A fundraising prove that NeuReality’s value proposition, architecture, and flagship product are a viable reality that will transform the AI market.”
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Prior to founding NeuReality, Tanach served in several executive roles as Director of Engineering at Marvell and Intel, and AVP R&D at DesignArt-Networks (later acquired by Qualcomm). Tzvika Shmueli served as VP of Backend at Mellanox Technologies and VP of Engineering at Habana Labs. Yossi Kasus served as Senior Director of Engineering at Mellanox and the head of VLSI at EZChip.
NeuReality’s boasts that its “novel” approach exponentially enhances ultra-scale inference for AI applications by doing away with the current CPU-centric model.
The company says enterprises are facing the limits of today’s solutions and experiencing spiraling costs with their growing deep learning demands on-premises and in the cloud.
Despite huge advances in deep learning, hyperscalers such as Amazon, Facebook, and Microsoft are facing scalability challenges with recommendation systems, digital assistants (such as Alexa and Siri), language-based applications (such as translations and natural language processing), and computer vision use cases.
One segment that will find NeuReality’s solution relevant is healthcare. Due to the growing scale challenges related to COVID-19 research and vaccine development, NeuReality will enable customers to easily scale their AI utilization while significantly cutting costs, lowering energy consumption, and shrinking the overall computing-infrastructure footprint.