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To change the way AI models are trained through their very own federated (yet collaborative) learning framework.
Self-service checkouts have become ubiquitous due to their cost savings and efficiency, but they aren't perfect. Customer error, fraud and inventory issues detract from their efficacy, and their sometimes clunky user interface and opaque errors make them unpleasant for customers. But what if checkout machines could learn from the items scanned through them and their interactions with shoppers, and pass that information on to other nearby machines to train them as well? This is precisely what Edgify is addressing with its edge device machine learning platform.
Edge computing is an exciting field because it targets a major issue with machine learning - the need for expensive central processing hubs. Using Edgify's technology any machine that possesses a CPU or GPU can connect to a network of other similar machines and share its data and learning to multiple devices. Supermarket checkout terminals are only the start for Edgify - it will likely find use in vehicles, hospitals and mobile devices of all kinds going forward.
The company has raised significant levels of funding. This capital is being used to further develop its product and roll out the technology to new verticals. As AI adoption continues to surge across all industries, Edgify is extremely well poised to develop into a major player in this space.
Steph
Company Specialist at Welcome to the Jungle
Oct 2020
$6.5m
EARLY VC
Mar 2018
$7.6m
SERIES A
This company has top investors
Ofri Ben-Porat
(CEO)Was previously Senior Strategic Advisor for the Israel Ministry of Tourism and the Co-found & CMO of Bring-it.co.il.
Nadav Israel
(CTO)Before co-founding Edgify was the Founder & CEO of Uminis. Previously was Algorithm Engineer Researcher for Samsung and Director of Group Research and Devlopment for eyeSight Mobile Technologies.