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Kindred SORT Robots Picked 10 Million Units in 2019 Peak Retail Season; Carter's, Inc. Achieves Optimal Throughput per Hour, 99.5% Autonomous Pick Accuracy

Kindred Robotic and Automation Experts at MODEX 2020 Booth #7791


News provided by

Kindred

Feb 26, 2020, 11:00 ET

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Kindred's SORT piece-picking robot
Kindred's SORT piece-picking robot

SAN FRANCISCO, Feb. 26, 2020 /PRNewswire-PRWeb/ -- Kindred, an artificial intelligence (AI) and robotics company, released its piece-picking results from the 2019 holiday retail season today. The company reported that its AI-enabled SORT robots installed across its rapidly-growing customer base completed 2 million unique picks from orders placed during Black Friday through Cyber Monday.

The company attributes the growth in picks of more than 218% year-over-year in part to Carter's Inc., North America's largest branded marketer of children's apparel, who used SORT robots during the 2019 peak fulfillment season for the first time.

Our customers credit their SORT systems for driving an average throughput increase of 30% year-over-year during the holiday peak shopping season.

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Throughout peak season spanning Nov. 1, 2019, through Dec. 20, 2019, SORT systems achieved a total of 10 million picks.

"With yet another record-breaking holiday retail season behind us, it's clear that AI-powered robotic solutions for automated picking are a must for retail operators," said Jim Liefer, CEO of Kindred.
"E-commerce retailers will continue to face the threat of labor scarcity and the increasing fulfillment expectation to delight customers more and more quickly."

Currently, in the off-season, Kindred SORT robots, installed at various customer sites across the U.S., pick over one million units each week. Carter's uses eight SORT robots for picking operations year-round at its state-of-the-art fulfillment center in Atlanta.

"Our customers credit their SORT systems for driving an average throughput increase of 30% year-over-year during the holiday peak shopping season," added Liefer. "Using SORT, Carter's has experienced exceptional throughput per hour, one of the leaders among the fleet."

SORT piece-picking robots utilize AutoGraspTM, a robotics intelligence platform that identifies and selects items to pick and place. AutoGrasp combines vision, grasping and manipulation algorithms to pick and place clothing, poly bags and other small items. Kindred uses cutting-edge AI research and human-in-the-loop data methodology to continuously improve robot capabilities so that picking becomes smarter, faster and more accurate over time.

SORT can evaluate items in real-time, picking and matching them to individual customer orders to increase productivity, expand capacity and improve overall efficiency for e-commerce and supply chain operations. The system can integrate with any warehouse management software (WMS).

Retail apparel and third-party logistics companies can realize the efficiencies of robotic solutions without making a large capital purchase. With Kindred's unique Smart Robots as a Service (SRaaS) model, customer pay-per-pick so they can scale capacity up or down according to demand.

For more information, visit http://www.kindred.ai/modex-2020.

Editor's Note: Kindred robotics and automation experts will be available at MODEX 2020, March 9 – 12, 2020. Please contact Hannah Minton at [email protected] to schedule a demonstration or interview time.

About Kindred
Kindred is a robotics and artificial intelligence (AI) company that develops robots to solve real-world problems. Kindred's cutting-edge technology is the foundation of a number of proprietary platforms including, AutoGrasp™, developed to operate robots autonomously in dynamic environments. Its team of scientists, engineers, and business operators have set a new standard for reinforcement learning for robots. Kindred's flagship solution, SORT, is a piece-picking robot with human-like grasping capabilities that operates in retail environments to separate multi-SKU batches into customer orders. The company is co-located in San Francisco and Toronto. For more information, visit http://www.kindred.ai.

SOURCE Kindred

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