How Chef Robotics found success by turning away its original customers

A few years ago, chef robotics were confronted with potential death.

“There were many dark periods in which I thought I would give up,” founder Rajat Bhageria tells WAN to his six -year -old company. But friends and investors encouraged him, so he stopped.

Nowadays, chef robotics not only survived, it is one of the few food -technical robot companies that blooms. The startup, which recently collected a Serie A of $ 23 million, has 40 employees and selection customers such as Amy’s Kitchen and Chef Bombay. Dozens of robots installed in the US have made 45 million meals so far, says Bhageria.

This can be compared with a graveyard of failed food-technical robotics companies, including Chowbotics with his salad robot Sally; Pizza Delivery Robot Zume; Food kiosk robot Carcaseand, more recently, agtech Small robot.

Bhageria says he saved his company by doing something that founders fear at an early stage: reject signed customers and reject millions of dollars in income.

The Grasp Problem

It all started when Bhageria obtained his master in robotics Upenn’s famous Grasp Lab. He dreamed of the sci-fi promised world where robots did our household work, we cooked our lawns and cooked our five-star tines.

Such a world does not yet exist because engineers should not fully resolve the robot Trouble. Training the same robot to wash a wine glass without crushing and a cast iron pan without dropping it is a difficult task.

When it comes to robotkoks: “Nobody has built a dataset of how do you pick up a blueberry and don’t squash it, or how do your cheese pick up and don’t climb it?” He describes.

His original idea with chef robotics was similar to the long list of starting robotics that died: a robot line for fast casual restaurants. That’s a huge industry With a chronic shortage of employees.

“We actually signed contracts. As we had contracts of millions of dollars. Of course we don’t do this anymore. So what happened?” he said. “We couldn’t solve the technical problem.”

In such companies, an employee completes an order by assembling all the varied ingredients that are needed for every meal. These restaurants want robots to replicate that process, because the alternative is that dozens of robots are dedicated to and calibrated for a single ingredient, some of which are only used occasionally (we look at your, anchovies).

But Bhageria and team could not build a successful pick-up-up robot because the training data does not exist. He asked his potential customers to have him installed robots for one or two ingredients, to collect and build training data from there. They said no.

Then Bhageria had an Epiphany.

Instead of trying to give bust to give existing customers what they wanted, he might need different customers. “It was really bad because I spent the past year and a half of my life to convince these people, these fast informal companies, to work with us,” he remembered.

Saying no leads to yes

It did not help that fundraising after 2021 cruel. VCs also looked at the cemetery. “We spoke with dozens of different funds,” said Bhageria. “We have just been rejected again and again.”

Bhageria thought about giving up. “You come home and are like, what am I doing in my life? Am I doing the wrong one? Do I have to stop?” He remembered.

But he grooves in and In March, 2023, a seed round of $ 11.2 million collected Led by construct capital, while also checks from Promus Ventures, smaller Perkins and Gaingels landed.

Bhageria and team also found their perfect market, part of the food industry that is known as ‘High Mix Manufacturing’.

These are food makers who have many, many recipes and make thousands of portions, but usually as meals or meal bins. For example; Salads and sandwiches or main courses and side dishes. These are meals used by airlines and hospitals, etc., or are frozen food meals for consumers.

Instead of an employee capturing all the ingredients for each meal, “High Mix” employees form an assembly line. Each person repeatedly adds his individual ingredient to the tray until the order is completed. Then they mount the following recipe.

“It is actually hundreds of people who stand in a 34 Fahrenheit room, and they essentially create food eight hours a day,” he describes. “So it’s just a terrible job.”

Consequently, this industry also has chronic labor shortages.

Robotics was not economically feasible in the past due to the variety of ingredients. But a startup is building a flexible bone, where the robots are built in collaboration with the food maker, works.

Even better, “while we learn how to do this chorizo, or we learn to peas, or this sauce, or this zucchini,” the bots get the Real-World training data they need to ultimately serve fast-casual restaurants. Bhageria says that this is still on his route map.

The best of all, thanks to the reborn interest of VC in all things AI, fundraising this time was “weird” easy, says Bhageria.

Avataar Venture Partners, co-founder of former Norwest VC Mohan Kumar, was specifically looking for startups of “AI in the physical world” and chased chef robotics, says Bhageria. He closed this round in less than a month. Avataar LED, with existing investors who build capital, Bloomberg Beta and Promus Ventures, stack in, Among other things.

The new financing brings the total of chef to $ 38.8 million. He also signed a loan of $ 26.75 million from Silicon Valley Bank for financing equipment.

And the process this time was “exciting,” he said.