Net AI uses new artificial intelligence (AI) and cloud computing techniques to provide real-time insights into network demand, telling mobile network operators exactly what services are being used at any location at any given moment, and in what amount.
The company’s Microscope software will provide more accurate and timely information than what is currently available from expensive hardware installed at different points in a network, and will eliminate the need for expensive computing resources that are required to process raw data offline.
Net AI, supported by Edinburgh Innovations, the University’s commercialisation service, aims to capture a significant share of the global network automation market, which is forecast to be worth more than £20 billion by 2024. The company has been launched with significant seed investment from a group of venture funds.
The company’s technology is based on more than five years of research at the intersection of AI and mobile networking led by Dr Paul Patras, Associate Professor at the University’s world-leading School of Informatics. Dr Patras is co-founder and CEO of Net AI.
Dr Patras said; “Entering into an exclusive licence agreement with the University of Edinburgh is a major steppingstone for Net AI and we are grateful for the support we received from numerous people and organisations, who helped us take the research out of the lab.
Having a unique AI technology such as Microscope puts us on the world 5G map and will enable us to engage with confidence with leading players in this space. We now seek to attract top talent to join our team and accelerate market introduction. Ultimately, we aim to develop a market-leading platform for mobile traffic decomposition and deep analysis.”
Mobile network operators face ever-growing demands for diverse data services from their customers and need to support new applications with unprecedented requirements, such as autonomous vehicles and industrial automation.
Current resource management systems rely on ‘deep packet inspection’ (DPI) equipment installed at different points in the network. This DPI technology is expensive, difficult to upgrade, it may slow down the network and does not work with encrypted data, which accounts for a growing share of today’s traffic.
Net AI’s software uses new AI techniques to provide accurate breakdowns of data demand on an application-by-application basis, allows data to be collected in the cloud, works with encrypted traffic, is non-intrusive and scales with network expansion independently of infrastructure.
Net AI’s target customers will be the current hardware/software solution providers to mobile network operators and those operators themselves, as well as professional services companies that specialise in analytics.
Dr Patras has been working with Edinburgh Innovations since 2019. He and his growing team have been supported to secure an ICURe grant to conduct a preliminary market validation and engage with potential customers, followed by a Scottish Enterprise High Growth Spinout grant to fund development of both the technology itself and a commercialisation pathway.
The team has also received support from the University’s Data-Driven Entrepreneurship (DDE) AI Accelerator, the DDE Seed Fund programme and the DDE Fast Track Executive Designate Programme, all supported by the Scottish Funding Council via the Data-Driven Innovation Programme of the Edinburgh and South-East Scotland City Region Deal.
Edinburgh Innovations CEO, Dr George Baxter said:
Talented researchers at the University of Edinburgh are well placed to find solutions to tomorrow’s problems, and the growing demand for data is just such a challenge.
This technology has great promise. We’re proud to support Dr Patras to take his discoveries from the lab into the marketplace, which will ultimately bring far-reaching benefits.”
Image credit: Alex Machado/Unsplash
