Dexai Robotics signs $1.6 million contract with US Defense Logistics Agency
Leading provider of intelligent robotic solutions for commercial kitchens Dexai Robotics announced a $1.6 million contract with the US Defense Logistics Agency (DLA) to automate food service at several military installations across the country.
Dexai has contracted to supply 10 Alfred super chefs, an automated cooking robot designed to improve production and operational quality, reduce food waste and lower the risk of spreading viruses and germs.
The first Alfred robot began operating in late 2021 in the Monarch dining hall at Travis Air Force Base in Fairfield, California, making Travis Air Force Base the first Department of Defense unit to deploy the device. Monarch DFAC is open to all 7,300-plus active personnel working on the base and serves an average of 950 customers per day. Dexai has not publicly said where the remaining nine robots will be deployed.
The Alfred installation at the base is part of a pilot program that includes placing nine additional robots in various military dining halls across the country. With this robot, the US Air Force hopes to reduce food waste, improve sanitation and ease staffing needs in its dining facilities.
The US Air Force and Space Force have expressed interest in using robotics in other operational areas as part of this industry program.
“We are very pleased to work with Dexai on testing and integrating innovation and technology into our food and beverage operations. Our goal is to make our operations more efficient, safe, simple and sustainable. In terms of functionality, ease of implementation and flexibility, Alfred far surpasses anything we have seen on the market. The fact that it can be optimized for the unique needs of each facility is also a significant differentiator. We are confident that this pilot program will be just the beginning of a long career for Alfred in the US Air Force and Space Force. I can't wait to see what other roles and ideas we can develop with the commercial industry through this program”
The robot uses artificial intelligence and computer vision to assess and adapt to its environment. Thanks to its ability to manipulate a wide variety of standard kitchen utensils, Alfred can be installed in any existing commercial kitchen and prepare a very wide range of dishes.
“Anyone who has worked in the restaurant industry will tell you that no two kitchens are exactly alike. From floor plan to cooking process, every commercial kitchen has a unique environment with unique needs. Alfred's ability to recognize and adapt to these unique requirements, wherever it is deployed, puts the robot in a league of its own”
Dexai traces its origins to a collaboration between researchers at The Charles Stark Draper Laboratory, MIT and Harvard. The company was founded in response to the widespread labor shortage in the restaurant industry.
As of November 2021, employment in restaurants and bars was down 6.1% from the pre-pandemic peak in February 2020. According to the National Restaurant Association, 78% of US restaurant owners reported they do not have enough staff to support current demand.
Dexai, founded in 2018 as a subsidiary of The Charles Stark Draper Laboratory, develops market-ready, scalable robotics and artificial intelligence solutions to meet real-world needs.
In response to the persistent labor shortage in food service, Dexai co-founders David Johnson and Anthony Tajun developed Alfred, the first and only intelligent, adaptable cooking robot designed to work in any existing kitchen.
Alfred uses advanced artificial intelligence and computer vision technologies to identify and handle a wide range of food and kitchen utensils for preparing salads, bowls and other dishes without any changes to restaurant layout or recipes.
“What is remarkable about this robot is that it uses kitchenware, so it can really cook whatever chefs come up with. There are no recipe limitations. I think the most time-consuming part is working with the chef's vision. So a chef comes in and says, 'Oh, okay, I want to make this. I want to do this.' And it's about teaching them what they can do with the robot”
According to Johnson, food is especially challenging because of how variable it can be. No two heads of lettuce are the same, so the robot must cope with the uncertainty involved in food preparation.
“There are difficulties specific to food. An example is food regulations. For instance, you cannot touch food-power management with automation without meeting certain requirements”
According to Johnson and Tajun, the hardest thing for the robot to learn was gathering arugula. Anthony said: "Alfred eventually realized that to gather arugula efficiently, it needs to push everything together so all the greens collect in one corner, and then scoop them up. It was just like watching a young person learn, and that is so powerful."
