DeepCube Raises Series A Funding to Realize Real-World Deployments of Deep Learning on Edge Devices, at Scale

New investment will fuel adoption of the industry’s only software-based inference accelerator that dramatically improves deep learning performance on intelligent edge devices

DeepCube, the award-winning deep learning pioneer, announced that it has closed $7 million in Series A funding. The round, led by Canadian VC Awz Ventures with participation from Koch Disruptive Technologies (KDT) and Nima Capital, brings the total invested in DeepCube to $12 million. The funding will enable DeepCube to advance, productize, and expand the footprint of its patented software-based inference accelerator in new markets, while fueling additional research, commercialization, and growth of the DeepCube team in its offices in Tel Aviv and the US.

DeepCube’s Series A funding follows the launch of its industry-first, software-based inference accelerator: the only technology that allows efficient deployment of AI models on intelligent edge devices. Until now, deep learning deployments have remained limited due to the size and speed of neural networks, and the need for specialized hardware, resulting in significant cost, memory, and computing requirements. DeepCube’s proprietary framework can be deployed on top of any existing hardware (CPU, GPU, ASIC) in both datacenters and edge devices, enabling over 10x speed improvement and memory reduction. This delivers the most advanced form of deep learning to edge devices, which has previously been unattainable at scale.

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“Deep learning has accelerated in recent years. However, the ability to deploy and scale deep learning on edge devices, with a light footprint and efficient memory and processing power, is a significant challenge that has hindered adoption,” said Yaron Ashkenazi, Founder and Managing Partner, Awz Ventures. “DeepCube is the only company that has been able to demonstrate the necessary paradigm shift to change this. DeepCube’s technology has the power to unlock truly autonomous decision making in semiconductors, datacenters, and on edge devices, while improving speed and memory reductions. This is absolutely critical to the future of deep learning, and because of this, we are confident that the company will be a critical driver of the future of AI and deep learning.”

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“Enabling deep learning on edge devices will drive innovation across countless sectors, allowing us to realize new, critical capabilities in applications such as autonomous cars, agricultural machines, drones, and even medical diagnostic tools,” said Eli Groner, Managing Director, KDT. “But none of that will be possible without significant technical advancements at the neural network level. That is why we are so impressed with DeepCube’s approach, and with the company’s unique ability to take the vision and theoretical promise of AI and convert that to reality.”

DeepCube’s innovative approach and technology have recently gained recognition in industry awards programs. DeepCube won a Silver Stevie Award for “Tech Startup of the Year – Software” in the 2020 International Business Awards, was selected as the “Best Deep Learning Company” in the 2020 AI Breakthrough Awards, and was a winner in the 2020 AI Excellence Awards.

“DeepCube is proud to be at the helm of innovation in AI and deep learning, allowing for efficient and cost-effective implementation of the most advanced neural networks on edge devices,” said Dr. Eli David, Co-Founder, DeepCube. “We are grateful for our investors’ vote of confidence in DeepCube and for their belief in our vision. With the new funding, we can deliver on the promise of deep learning to customers in new markets – having an impact not only on their businesses, but also, on the deep learning industry at large – far beyond what’s previously been possible.”

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