Intel® RealSense™ Computer Vision Technology helps Simbe Robotics automate in‑store retail operations.
Challenge
One of the biggest blind spots in retail is in-store operations. In brick-and-mortar retail, inventory must be tracked manually by store associates, and analytic data is limited to tracking the sales at the register. Retail operations haven’t changed much over time, leaving businesses looking for ways to take advantage of new technology to improve their bottom line.
Solution
Simbe was founded in 2014 to address these challenges by using robotics and analytics to provide retailers with an automated solution. Tally captures real-time inventory and e-commerce grade insights to allow retailers to optimize their in-store operations.
Results
Tally is an autonomous inventory robot designed to provide retailers with accurate real-time shelf data. With the help of Intel RealSense depth cameras, it efficiently tracks shelf inventory and issues such as out-ofstock items, pricing changes and mistakes, and misplaced merchandise. Auditing around 10,000 items in 30 minutes, Tally empowers retailers and store associates with up-to-date information and shelf insights. Stores using tally experience a 2.2% uptake in sales due to optimized store execution and superior customer satisfaction.
The best choice for Simbe’s robot
Tally, Simbe’s robot, is the market leader in retail robotics, and the only fully autonomous robot in the industry able to traverse a store multiple times a day and connect to its charging base without the help of a store employee.
The heart of the solution.
The heart of the solution.
Using the (D435) helps Tally to see both the front and the back of the shelf and have a better understanding of what products are actually present. Additionally, since Tally has an entire store to scan, it was crucial that this analysis can be performed while Tally is moving. Remaining stationary would waste a significant amount of time, so the fact that the the Intel RealSense depth cameras can perform this visual representation in color and in motion was an important factor in determining the right sensors for the robot.
What's next?
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