This restaurant tech start-up uses computer vision to get your fast-food order made accurately
- Restaurant tech start-up Agot AI has closed a $10 million seed funding round with Continental Grain, the Kitchen Fund and Grit Ventures as investors.
- The start-up installs overhead cameras in restaurant kitchens and uses computer vision to scrutinize if workers are preparing orders correctly.
- The drive-thru ordering boom during the Covid pandemic has made order accuracy more difficult for fast-food restaurants.
Restaurant tech start-up Agot AI has closed a $10 million funding round that will help the company work toward its mission of improving fast-food order accuracy.
The start-up installs overhead cameras in restaurant kitchens and uses computer vision — similar to that used in autonomous vehicles — to scrutinize if workers are preparing orders correctly. The technology is supposed to improve labor efficiency and decrease customer wait times.
Agricultural investment firm Continental Grain, which recently bought poultry giant Sanderson Farms with Cargill, led the start-up's seed funding round. The Kitchen Fund – which has investments in Sweetgreen, Cava and Gregorys Coffee – and Grit Ventures also participated.
Agot raised just $50,000 during its previous funding round in May of 2020, according to Pitchbook.
"We are thrilled to support the Agot team in bringing their computer vision solution to market, increasing labor efficiency, improving off-premise operations, and providing real-time analytics to sophisticated QSR operators," Continental Grain said in a statement to CNBC.
Order accuracy can have a strong impact on consumers' willingness to return to a restaurant and overall experience. The American Customer Satisfaction Index's annual consumer survey found that fast-food restaurants' orders were accurate 84% of the time in 2021, down from the prior year's score.
Agot co-founder and CEO Evan DeSantola said the technology can spot over 85% of order errors and call attention to those problems before workers serve the food to customers.
"We see that across the [quick-service restaurant] industry order accuracy is becoming an increasingly large problem as a result of the shift to drive-thru," DeSantola said. "What was once a smaller pain point, when the accuracy rates haven't gotten much better, is now a much larger pain point."
Drive-thru orders were growing before the pandemic, but the health crisis led many consumers to switch to that ordering method because of shuttered dining rooms, convenience and safety concerns. In December, drive-thru transactions rose 22% compared with a year ago, according to the NPD Group. SeeLevel HX's annual drive-thru study found that average times across 10 fast-food chains slowed down by nearly half a minute last year.
DeSantola and his co-founder Alex Litzenberger, who serves as the company's chief technology officer, met while computer science students at Carnegie Mellon University. They started the company 2½ years ago after experiencing long wait times and wrong orders themselves. The founders' alma mater also participated in the seed round.
"What was very clear to us about Agot is that it is not a point solution," said Greg Golkin, managing partner of the Kitchen Fund. "It is a platform that is being built, and order accuracy is just the first application. Computer vision is not going to stop there."
Golkin also said that Agot was the furthest ahead of other start-ups who are exploring similar computer vision solutions within restaurant tech. According to its founders, Agot has received multiple acquisition offers that it has refused.
DeSantola said Agot's typical customer has at least 2,000 restaurant locations. However, he declined to share the names of current restaurant clients, citing strict nondisclosure agreements.
Agot plans to use the money from the latest funding round to grow its product and engineering teams and to expand its reach, both for existing clients and adding new chains to its roster.