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Radius AI brings edge AI to retail, wins Innovation Award

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At VentureBeats fourth annual AI Innovation Awards provided in July at Transform, Radius AI, located in Tempe, Arizona, won the Edge AI award because of its artificial intelligence (AI) computer vision technology that equips retailers with real-time insights on queue analytics, customer counts, store layout, parking lot analytics, customer journey and employee metrics.

In accordance with nominating committee member Andrea Huels, head of AI, THE UNITED STATES at Lenovo, Radius AIs computer vision solution helps retailers, particularly convenience stores, make the most of missed opportunities, such as for example knowing if someone left the store without purchasing. or if the stores product placement is ideal. The target is to provide insights to greatly help retailers create increased sales and satisfied customers.

The focus of these human-centric AI would be to nudge staff in real-time to allow them to make improvements, said Huels.

Radius AI happens to be performing a 1,000-location deployment for an enterprise client, which Radius claims to function as largest computer vision project in the convenience store sector.

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Collaborating on edge AI

Back 2017, Radius AI founders Abhinav Chowdary and Jeff Cox became friends while working together at Wells Fargo in Arizona, however the two had long discussed collaborating on a startup, particularly in computer vision.

At that time, retailers weren’t taking into consideration the edge, Radius AI cofounder Susan Sly told VentureBeat. Many were contemplating how exactly to use AI for online engagement, however, not so much when it comes to how it might benefit the client experience in brick-and-mortar stores. But Chowdary and Cox realized that convenience stores, making use of their already-existing on-premises security camera systems, were a highly-successful segment that has been underserved by AI-driven computer vision technology.

Current Radius AI CEO and cofounder, Aykut Dengi, was an engineering professor at Arizona State University when he met Chowdary and Cox in 2018. Excited by the Radius AI technology, he took a sabbatical from teaching and offered his services free of charge. Finally, Sly was earned as a fourth cofounder after 2 decades building large sales teams being an entrepreneur, she was serving on a Phoenix advisory board for startups and searching for her next challenge.

Candidly, significantly less than 2% of tech companies in the U.S. have a minumum of one female founder, she said. Therefore the possibility to partner with a team of individuals who value inclusion and results was a straightforward yes. Furthermore, Sly said she could easily observe how the Radius AI technology could radically shift the brick-and-mortar landscape.

Although I hadnt written a type of code since 1992, I was wanting to jump in, she said. Even yet in the 1990s, when I was focusing on an early on facial recognition project, I possibly could see where this technology would eventually take us.

Convenience stores were an untapped opportunity

Over 29% of Americans visit a convenience store each day, Sly claimed, but due to the pandemic along with other macroeconomic factors, there’s been a shortfall of retail workers which includes resulted in challenges in meeting customer support expectations. Which has meant an untapped chance of growth, she explained.

Among the items that we value in the store is how exactly we may use AI and specifically computer vision to improve parking lot-to-store conversion, Sly said. Because after we will get people in the store, then theyre more prone to buy something.

Each convenience store has its Radius AI edge device, which, combined with existing security camera systems, permits fast and secure data visualization. The companys intelligence solution offers insights from enough time customers enter a store, including customer counts, paying vs. non-paying customers, heat maps and a complete customer journey.

Sly noted a key differentiator for Radius is its relationships with partners that hardware integration. Which means the business can tackle the installation, the edge device and the GPUs, along with services.

Radius AI has generated out its custom models. While there are several different labeled training datasets in computer vision for things such as image recognition, there isnt readily-available training data to identify human intent.

We’ve developed fundamental models that capture human motion and we interpret those actions based on the context, Dengi said. In retail, he noted, that context is crucial. For instance, when COVID-19 restrictions were set up, many retailers implemented social distancing rules. While that managed to get more difficult for a few computer vision models to properly identify things such as for example how busy a store was, Radius AIs edge system could adapt and keep maintaining accuracy.

Radius AIs computer vision future

Sly said that Radius AI happens to be centered on three things: Trust, ease and wow.

Our goal is usually to be probably the most trusted computer vision company on earth, she said. We recognize that this is a bold statement, but we wish the adoption of our product to be easy and we use strategic partners to determine methods to deploy computer vision efficiently our record so you can get a location ready to go is 1 hour and you want to beat that.

Lastly, she said, the business really wants to wow customers. Our vanguard opinion is that people think that humans and AI are better together, she said. Five years from now, we are releasing products that help humans be superheroes.

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