IoT Platform Developer Locks In $20M Funding for IoT Device Digital Twins – IoT World Today
The digital twins use machine learning to help developers optimize IoT devices as well as allowing internet service providers to predict networking faults remotely
Ayla Networks has secured a $20 million investment to expand its digital twin offering that allows vendors to optimize their IoT devices.
Company officials said the investment will be used to further expand Ayla’s strategic positioning in key IoT markets by leveraging a combination of product innovation, sales, marketing and geographical expansion.
The growth equity round includes contributions from Arrowroot Capital, Trinity Power Limited, Voyager Capital and SJF Ventures.
“The IoT market has seen tremendous momentum over the last few years, particularly for everyday consumer use cases, and we wanted to capitalize on that long-term trend.” said Thomas Oh, vice-president at Arrowroot Capital, who is set to become an Ayla board director with the investment.
Founded in 2010, Ayla Networks’ analytics and machine learning tools help device makers visualize various parts of their IoT projects digitally, not only the devices themselves but also software apps, voice-activated features and cloud services.
Device makers can also use its product to enable remote customer support enabling technicians to fix product issues without requiring equipment be returned.
While Ayla is seeking growth in the smart home segment, the platform also supports enterprise-grade IoT projects.
Key use cases include monitoring data logs from connected industrial plants and commercial heating and ventilation systems so maintenance can be planned ahead of schedule.
Developers access the software through Ayla’s cloud platform or use the mobile app to manage devices while they’re away from the desktop. In the case of some smart home devices, Ayla offers turnkey firmware that can be installed with its product.
In addition to modeling IoT performance, internet service providers can use machine learning tools to predict networking faults in broadband equipment. Technicians can then attempt to remedy the issue before internet speeds are impacted.
Ayla’s machine learning architecture can automatically extract, store and process IoT data. It includes prebaked models for predicting key events such as device failure, degraded performance and unforeseen maintenance costs.
The machine learning algorithms are fully compatible with leading smart home brands Amazon Alexa and Google Assistant, in addition to Android smartphones.
Also supported is Matter, a royalty free connectivity protocol that aims to coordinate fragmented standards across smart home and IoT vendors.
“The demand for connected products, and the rate of change in the connected home, is increasing and we want to be best positioned to help the original equipment manufacturers and internet service providers fulfill that demand,” said Jonathan Cobb, Ayla Networks’ CEO.
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