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DeepSig Raises $5M Series A Financing to Advance AI in 5G Radio Access Networks
Saturday, March 7, 2020
With their Series A Financing round complete, DeepSig looks to continue furthering the development of their technology that harnesses Artificial Intelligence to revolutionize waveform identification and transmission.
ARLINGTON, Va., Feb. 28, 2020 /PRNewswire-PRWeb/ -- DeepSig, a company developing AI to transform wireless for 5G, IoT, and security, raised $5M in its Series A Financing, adding to the $3.5M previously raised. Leawood Venture Capital led the Series A round with participation by Scout Ventures, Blu Venture Investors, and Lockheed Martin Ventures. The additional funding will accelerate DeepSig's AI and machine learning (ML) software development and deployment to improve performance and security while reducing power consumption and cost in 5G and other wireless systems.
"We are excited to include DeepSig as a portfolio company in our Fund. Their proven leadership team, combined with their groundbreaking patented technology will have a significant impact across wireless access, 5G networks, and defense markets," said Brendan Fallis, Co-Founder and Managing Partner of Leawood Venture Capital.
"The advanced technology developed by DeepSig can optimize communications within a wide spectrum environment," said Chris Moran, vice president and general manager of Lockheed Martin Ventures. "Applying deep learning and artificial intelligence to the application of real-time signal processing is an impressive capability. We are pleased to be a part of this endeavor and work to integrate the software into programs."
DeepSig's AI software replaces decades old wireless algorithms with machine learning in wireless communications and sensing systems. When applied to 5G, DeepSig's OmniPHY(TM) software learns the local conditions of a radio base station to improve user data rates and dramatically reduce the amount of hardware and hence power, cutting both CAPEX and OPEX. DeepSig participates in the Telecom Infra Project and the O-RAN Alliance that are working to radically reduce the costs of 5G through virtualization onto commodity hardware.
"DeepSig has developed a truly disruptive technology harnessing Artificial Intelligence to revolutionize waveform identification and transmission bringing massive efficiencies to power consumption and signal fidelity", said Brad Harrison, Managing Partner Scout Ventures.
In security and defense markets, DeepSig's OmniSIG(TM) detects and classifies wireless signals 100s of times faster than convention techniques allowing detection of wireless cyber intrusions or threatening forces. OmniSIG has been deployed both at the network edge and in cloud infrastructure from Microsoft Azure and Amazon Web Services and can be trained to recognize new signals in a matter of hours versus weeks of engineering needed for current technology.
"DeepSig's revolutionary approach using AI/ML/DL in next generation learning-driven radios is truly an enormous departure from the status quo in signal processing-based communications systems, representing a revolutionary approach to the physical layer technology used today which provides significant performance benefits", said Pradeep Kaul, BVI principal Blu Venture Investors.
"As wireless companies and governments deploy 5G, DeepSig will continue to lead AI innovation in this sector. The performance advantages that AI & ML enable are enormous, and we are excited to be leading the field in realizing and bringing to market these unique software performance enhancements. We are very pleased to receive backing from industry veterans that share our vision" said Jim Shea, CEO of DeepSig.
About DeepSig:
Located in Arlington, Virginia, DeepSig develops deep learning software on Cloud, Edge, and embedded devices. Their OmniSIG(TM) product provides visibility into wireless spectrum activity 100s of times faster than current technology to find interference, wireless/cyber threats, and anomalies. OmniPHY(TM) replaces key conventional baseband signal processing technology with machine learning to dramatically improve system performance.
SOURCE DeepSig
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