5 Ways Computer Vision will Change the Face of Food Service Management

Employees and managers overlook many details of their tasks. From over-scooping ingredients to mixing up orders, workers are making mistakes that can add up to a costly loss. Just last year, error in discounts for Burger King’s Whopper meals cost Carrols Restaurant Group, the largest Burger King franchisee in the nation, $12.4 million in the first nine months. Facing continuous revenue losses from human errors, many leaders of the food industry turn towards computer vision to help them oversee, both literally and figuratively, all portions of restaurant management.


What is computer vision and how does it relate to restaurants?

Emerging from artificial intelligence and deep learning, computer vision trains computers to “see” the world using digital images from videos or pictures. It allows computers to formulate a suitable response after interpreting and understanding the visual cues provided in the digital images.

Leveraging machine learning and deep learning, computer vision has been getting better at detecting objects, recognizing facial features, tracking objects, etc. In recent years, this technology has made its way to the food industry, where accuracy and efficiency are crucial. Unlike humans, computers with computer vision and excellent AI can see details of the check-out process and make accurate, real-time analysis in stores, especially limited-service restaurants (e.g. Chipotle).


Let’s uncover how the computer vision powered system is reshaping restaurant management!

1) Computer Vision increases labor savings.

Labor costs typically range from 20% to 40% of the gross revenue, with fast-food restaurants being in the lower end and table-service restaurants being in the higher end. As the minimum wage is increasing, restaurants often have to downsize their staff or shorten operation hours to account for the high labor cost.

By implementing a cashier-less checkout system that utilizes computer vision, restaurants can increase labor savings by eliminating most or all cashier positions. To estimate the savings, we can look at the range of national restaurant cashier salary, which is around $14.5K to $31K. The labor savings can be more accurately estimated through a function of hours of operation, proportion of time working on cashier activities, and local minimum wage.

2) Computer Vision increases throughput/efficiency.

Computer vision powered checkout systems can process transactions faster, increasing the efficiency of ringing up restaurant customers. Unless we are looking at restaurants in places with a continuous high-density inflow of customers such as airports or food courts, installation fee and the overall cost of the cashier-less checkout system is strictly less than labor cost of adding another cashier position.

Furthermore, many restaurants’ peak periods often only last a few hours a day. It’s simply not feasible to hire another cashier just to accommodate a throughput increase during peak hours. Hence, computer vision powered checkout can solve the issue of long lines during peak hours, leading to a better throughput throughout operation hours.


3) Computer Vision provides restaurant owners with operational insights

By overseeing all the steps involved in the food prep and checkout process, a computer vision powered system can provide analytics that can be used to increase efficiency and customer satisfaction. For example, computers can reduce food wastage by tracking orders and accurately assessing supply and demand of each ingredient based on the time and other factors.

In all-you-can-pick buffet-style restaurants (e.g. Moe’s), the computer can analyze customers’ orders to determine popular combinations of ingredients and dishes. This will help restaurant owners redesign their menus to tailor to the preferences of their customers.

4) Computer Vision increases accuracy when prepping orders

A checkout system powered by computer vision can ring up more accurately than a human cashier. It can analyze each frame of the video captured from the camera, calculating the sizes of the scoops and verifying the ingredients accurately. The accuracy of such technology can reduce 0.25-1% of the revenue slippage occurring from cashier undercharging.

Furthermore, providing accurate billing when doing a combination of online orders and in-person orders is difficult, especially when ordering takeout becomes a new normal in the current state of the pandemic. With the computer vision system installed, online orders can be monitored as the machine observes human baggers and notifies them if there are errors, such as mixing up orders or missing certain dishes. Mistakes that involve promotions and discounts can also be avoided completely thanks to the automation.

5) Computer Vision increases Customer Satisfaction, especially in the state of pandemic

In the current state of the global pandemic, customers are afraid of being in close contact with staff members in restaurants. Even if restaurants offer takeout, customers are still fearful of being infected by COVID-19 when picking up the food.

By installing computer vision powered checkout, restaurants can eliminate the cashier-customer interaction, promising customers a human-contact-free and efficient, fast checkout process.

In the current and post COVID-19 world, restaurants' preparedness to combat the spread of the virus is the key to gaining customers' trust and increasing customer inflow.


Get Started with Agot.AI’s Operations Data Hubs

Most companies only offer technology that utilizes computer vision for one restaurant operational task, such as only monitoring check out. But why not have a central system that can do all types of operational tasks?

Agot.AI's Restuarant Manager can do just that. A multi-use tech, our technology power a diverse set of applications that allows cashier-less checkouts and online order verification tools. Leveraging computer vision, our solution optimizes throughput (5%-15% increase in market share), increases quality control, and supplies accurate billing (95% reduction in order assembly errors).

If you want to start eliminating errors and receiving comprehensive analytics of your restaurant today, schedule a free demo with us to see how effortlessly our Restuarant Manager can be installed. This demo can help you determine how you can use cutting-edge technology to improve the efficiency of your restaurant.




Jim Swartz

Founder of Accel Partners

· Founding general partner of Adler & Company and lead director of 50 successful companies
· Former chairman of the National Venture Capital Association and a 2007 recipient of its Lifetime Achievement Award

Elizabeth Yin

Co-Founder of Hustle Fund

· Co-founded LaunchBit (acq 2014)
· Reviewed over 20k startup pitches, her work has been featured in numerous publications including TechCrunch, Forbes, Huffington Post, BetaKit, and more

Michael Joseph

Founder of Green Chef

Alex Fishman

Founder of Empros Capital

Innovation Works

Provide Seed Funds to Startups

Michael Donohue

Early Employee of WhatsApp

Charles SongHurst

Early Employee of Microsoft

Bhiksha Raj

Professor at Carnegie Mellon

Written By
Chloe Wang
Head Of Growth

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Michael Joseph

Founder of Green Chef

Alex Fishman

Founder of Empros Capital

Innovation Works

Provide seed funds to Startups

Michael Donahoe

Early Employee of WhatsApp

Michael Joseph

Bikshah Raj

Professor in CMU

Michael Joseph

Charles SongHurst

Early Employee of Microsoft

Michael Joseph

Michael Joseph

Michael Joseph