Our AI in Retail Industry
Our AI operates without any human in the loop and is protected with high quality IP Portfolio. We have developed and successfully deployed a completely scalable AI retail industry solution for advanced scene to understand and recognize what is on the shelves of large retail stores.
We are experienced with University-Industry partnerships and pioneers in helping industry R&D for upgrading the AI solutions in retail world and beyond.
We developed our AI solutions from ground-up with a significant IP contributions in the area of scene understanding for Retail Inventory Analytics.
We devote to the business, move in fast pace, and follow the production demand. In 2018, Prof. Savvides became Bossa Nova Robotics Chief AI Scientist. Professor Savvides his CMU R&D Team developed from ground-up all of Bossa Nova Robotics Video Analytics that deployed in the robots fleet in just 24 months.
Our robust AI solutions have been demonstrated in the deployment of a large fleet of 550 robots live in 550 retail stores nationwide running 3 times a day in 2020.
Experienced Leadership in Retail AI Analytics and Robotics
- As Bossa Nova Robotics R&D team, Professor Savvides and his CMU team developed a product ready retail video analytics AI solution that was customized to retailers specifications.
- The World Class AI developed allowed Bossa Nova Robotics to scale from 20 stores in 2018 to 550 stores in 2020 using a CMU developed AI pipeline that was agnostic to store and isle location.
- Our AI solution was productized and deployed to 550 stores, running 3 times a day fully autonomously on Bossa Nova Robots. We took special pride in our solution for completely removing any Human-in-the-loop (HITL), thus all the image/video retail analytics were near real-time, providing the retailer all the out-of-stock information shortly after the robot finished scanning the isles.
- Amazing example of how a 1st class AI Academic team and a world-class recognized leader with strong past performance in delivering real-systems have made such strong Industrial impact using R&D from Academia and transitioning it to Industry for mass-deployment in under 24 months.
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