How AI Is Changing the Future of Food (Chef Robotics Explained)

Third eye, being an investor, and then Chef Robotics. like 16, 17 years old and there's people in Brazil and Argentina and China who are using this product. A few angel investors were like, "Why don't you turn this into a company?" What exactly are these robots doing? So, what each robot's kind of doing the work of two people. Robots don't fail, they don't slow down, they just like go. Those are the two things that kind of got me excited. It's a big market, feels like there's a big pain point. And I guess one more thing which is like advice would you give to people like starting something? The passion hypothesis says that passion leads to the success. You look inwards and you're like, "What am I passionate about?" But the truth is that like Hello everyone. Today we have Rajat Pagaria on my show. He's the founder and CEO of Chef Robotics. Rajat, I'm so excited to have you on the show. How are you doing today? I'm good and thank you Monish for having me. I'm excited. Thank you. I want to ask you many questions about Chef Robotics, but I really want to like ask about you first. Like, can you give us a little intro about yourself, starting Third Eye, then moving on to being an investor, and then starting Chef Robotics? Like, how has been the last decade of your life been? That's a It's a broad question. That was a big question. Yeah, I guess what I went to like high school and a lot of my kind of like schooling was in Cincinnati, Ohio. Basically during school, I mean, in high school I was very focused on kind of like, okay, like my my number one goal was I wanted to go to a good school. So, I was like I worked really hard to get into a good school. And then kind of like when I got accepted, I was like, "Okay, fine. Like I basically last like 5 years I was super focused on that goal." And I was like, "Okay, now I'm free. I can like do whatever I I want." And that's really when like entrepreneurship really started. So, kind of my senior year of high school I worked on a few different projects. One was called Cafe Mocha, which which is basically this like at the time Medium really didn't exist very much. So, there's like Tumblr, there's these different like blogs, like WordPress blogs that people are doing, but I was like, "Okay, well, I like to write." And there wasn't really a good platform for young writers to publish their writing or their research or their poetry or what what have you with the world. So, this is really where I learned how to do software engineering and then actually like ship this thing. And at the time I I was like 16, 17 years old and And since I'm Ohio, like suburban Ohio. I was like, "Wow, like there's people in like Brazil and Argentina and like China who are using this product." And it's pretty cool. And so this is like relatively formative experience for for me as a young person. But that was kind of my first kind of real entrepreneurial endeavor. You know, then my first my goal during college, my like basically freshman year of college, my goal was to find a co-founder for Cafe Mocha, the social networking for website for young writers. Um that was my goal. And so like I would I was doing computer science at the time and you know, I was like, "Okay, who who's the best kind of engineer here, right?" And um I found some really great people that kind of became really close friends and interesting what what happened is that we entered this hackathon, PennApps. And And at the time like AlexNet had just happened and computer vision had just kind of like it felt like it was having its stride again with deep learning, CNNs. So we were like, "Okay, well why don't we take that idea? We combine it with like smart glasses." The Google Glass was having its heyday at the time as well. And what if we build like a product for the visually impaired for this hackathon, just for the hackathon? How are you helping the visually impaired though with the glasses? Yeah, so the idea basically was that So it's funny like there's three of us and one of our um my co-founder at the time's grandfather was visually impaired. So that was kind of like where we knew what the problem, I guess. But But basically the idea was that, you know, the visually impaired kind of has this idea of like learned helplessness, right? Like you kind of go through life and you kind of constantly need help. And I think our idea was like, "If we provide them a product that they could put onto their face, like smart glasses, and they could use a verbal signal, like okay glass recognize this." Or something like this. Um and then we could take a picture or video stream and then do a you know, real-time object recognition and detection. Then we could tell the person verbally, "Hey, you're looking at ibuprofen or Advil." Or it's a $1 bill or a $5 bill. Or here's what the menu says at the restaurant. That's such a good idea. Yeah, we This seems like a very simple idea. You know, honestly, we didn't know much about computer vision or anything at the time. We were like two weeks into to college, right? But we ended up doing really well at this hackathon. And we just hacked our way through this. And we did really well. And at the end of it, a few angel investors were like, "Oh, why don't you turn this into a company?" We were like, "Okay, like why not? What do we have to lose?" So we decided to kind of do this. This is what became Third Eye. And you know, a lot of my kind of college experience is this Third Eye, right? And we worked on this for around three and a half years. Ultimately, it became a decision of do we like drop out and do this full-time or do we kind of sell the company? And for various reasons, we decided to sell the company. So, you must have learned a lot about like image recognition, machine learning during that process as well, right? I I think exactly. And and I think that that's exactly right, which is like that was my first experience really with AI, right? And I became really excited about this prospect of AI. You know, this was like 2018, 2019 type of time frame. So, anyways, but for me personally, I was like, okay, like this thing seems exciting. And it it and it basically was like, okay, like I had a few things that I was thinking about next. I was like, okay, like first of all, I want to like really learn how to build companies um from basically like a mentor, right? Somebody more senior. And then the second thing was like, okay, what's the next thing I want to do? So, I tried to do parallel process both these both these things. So, from in terms of like learning, I convinced Slava Rubin, who's the founder of Indiegogo. He was giving this talk at Wharton. I was like, "Hey, like, you know, this is who I am. I did this thing, the Third Eye." He was launching this new like equity crowdfunding product for Indiegogo. He he runs Indiegogo. So, he's launching this new product for equity crowdfunding. And I was like, "Well, like I'm I'm guessing you need help with deal flow. What if I help you build like some new vehicle to get deal flow using a bunch of scouts all over the country as founders, basically." So, I was like basically create my own create try to convince him to create my own job with them. And I was like, "Okay, well, in return, can I just follow you around and attend the meetings you attend and and and things like that." So, he he did say yes. So, basically that like that was a really awesome experience because like for a few months, I just followed Slava around. Like went to all his meetings and like, you know, he's thinking about like acquiring companies and like I was helping with the model and like it helping make slides for board presentations. Like a bunch of like pretty like intense stuff that as a young person, I probably shouldn't have access to, but he became like a really great mentor. So, that was like during the day, and then the evenings, of course, I was like thinking a lot about, "Okay, what do I do next?" And I became really excited about like essentially two ideas. One was AI, of course, just continuing AI. And then the second was energy. It feels like those two are things in in various breaths and scopes are the the two big things that are going to affect our lives. Of course, just given the Third Eye experience, I was more excited about AI. I was like, "Okay, what what's the right product and company to build?" So, then I really took a deep dive into the market, right? Like who are the customers for this? And I I became excited about this idea of like AI in the physical world. And and what I mean by this is like at the time like the AI companies that existed were like people who are doing machine learning for like spam detection, spam filtering and stuff for like Netflix recommending you content. It was mostly in a cloud, all software based. And I was like, okay, well, I think there's something exciting about AI in the physical world because like 90% plus of GDP is in the physical world. Like Tesla's a figure robot, humanoid robots. What else is an example of that? Well, I think I I I I think like my thinking was, okay, like what are the foundational industries that represent most of GDP? It's the It's the labor market. It was half of GDP. Like retail jobs, nursing, uh hospitals. Yeah, transportation, construction, even things like mining. I mean, these industries were just so gigantic. I was like, okay, well, what's the biggest part of the physical world? Well, it's the labor market. So, then I was like, okay, well, like I want to do something in the labor market, uh which obviously takes the form of robots, right? AI-enabled robots, right? But again, didn't exactly know what the right industry was. And so, this is when I kind of the impetus for the fund happened. So, another very close friend of mine, Nandeet, um you know, while I was doing like third eye and startups in college, he convinced a bunch of really great LA funds LA-based funds to essentially do the same thing I did with Slav. Essentially take him on as essentially like, I'll do whatever whatever you need me to do, which of of course was a lot of like, you know, helping with getting deals over the line, but also like fund operations. He did like whatever it took, basically. I can tell you enjoyed that experience a lot. Yes. Like the investing and looking at deals. Yes. So, we decided to kind of say, okay, well, why don't we do something together? We became close friends, and we launched Prototype Capital. And the the idea was like, it seems to be the case that there's going to be this big influx of companies are using AI in the physical world or even IoT or ML. So, let's go after them. But to go after them, they don't just exist in the Bay Area or LA or New York. Those companies are like everywhere else. They're in like Cincinnati and Idaho and Atlanta and all these other cities in the US um and and around the world. So, you know, Silicon Valley VCs are not looking for those companies. So, how do we get access to them? The way that we can get access to them is by finding out who the fan founders hang out with for fun. Well, and and the truth is most founders hang out with other founders for fun. So, if if I want to get after like a really great company in in Atlanta for insurance tech, let's say hypothetically, then if I can find that founder's friends and convince them to be a scout with us, and I give them carried interest if they refer us great deals, deals that we invest in, then hopefully we can get some really great under the radar deal flow. Yeah, so this is kind of what we did. So, we had around 70 different kind of founders all over the country. And and yeah, we we we basically invested in a bunch of different companies. But but from the chef perspective, it also kind of got me in front of some of these potential customers. It got of potential customers in construction and agriculture and food and all these different industries. And of course, I did end up focusing on food. I I always knew that like I wanted to like like the whole idea for Prototype was like founders investing in other founders. Me personally, I really like building. I never wanted to become full-time VC, at least in the short term, or medium term, I guess. You're too young for that. Yeah, I really wanted to build stuff. And I was like, "Okay, Prototype is going to be a thing I always do, but like I want the full-time thing mostly to be building." So so yeah, anyways, like I I I the food industry was very exciting. And the reason it was very exciting is because few kind of macro trends. One macro trend was just the size of the industry. You know, I I learned just looking at data as I was spending a lot of time. Like once I selected it seems to be something in food, I looked a lot of data about what's the size of the industry. What I learned is that the biggest industry on planet in the US is kind of nursing and personal aids. The second one's kind of retail sales people. And the the third one is food preparation, food service, food production. My perception was that the first two are not tractable by AI anytime soon. So, it felt like number three is actually arguably the biggest market tractable for AI. This given this idea that the proxy for market size of AI is the number of humans who do that job. So, I said, "Okay, well, it seems like there's a really big industry." And and then I was like, "Okay, is there a problem?" Because of course, in startups you need to be solving a problem. So, with that again, I took like an anecdotal approach as well as like, "Let's look at the data approach." Anecdotally, I talked to food truck operators to fast casual operators to airline catering to ghost kitchens, but manufacturing, anyone and everybody. They all said basically, "My number one problem is big labor shortage. It's like on a given day, I don't know which 80% of my people are going to come to work, and because of that, I'm leaving revenue on the table. So, it felt like there's a big like from anecdotally, it felt like there's a big pain point. And then I confirmed with data that the BLS in '23 2023 reported that the food industry is actually the number one labor shortage in the US, more than like retail, more than manufacturing. And this is combining assembly, food preparation Everything. It's just like the food industry basically. Okay. So, it's like basically that's those are the two things that kind of got me excited. It's like it's a big market. It feels like there's a big pain point. And there's one more thing which is like, you know, it felt like the status quo AI robots could kind of scoop food and make a Chipotle bowl or a Sweetgreen bowl. Like it felt like that's like something I can imagine. So, technically, of course, we hadn't done a ton of homework at the time, but it felt like the puzzle pieces came together, and that's why we decided to kind of focus on broad scope stat industry. So, can you talk a little bit about like that what exactly are these robots doing? Because the hardest thing in my opinion is like food is so it's hard to manipulate food, right? Because it's so complex. Yeah, so today like our go-to-market is really food manufacturing. So, which is different than a lot of people think. A lot of people are like, "Ah, robots for restaurants, right?" But like like you alluded to, we are actually focused on manufacturing. You know, essentially the way you can think about it is anytime you have kind of a meal that you might have on an airplane, or like if you get frozen meals from the grocery store, or you go to the grocery store in in the deli section, the fresh food section, all those prepared salads you might find at Trader Joe's, all these like kinds of meals are actually made by people. And they're made by people in these big facilities, basically food factories. And the way it kind of works is you have these long assembly lines, and on the assembly line there's like 12 people Each person has a big tub, and they're kind of scooping trays, scooping food into trays or burritos or wraps or sandwiches. The most mundane tasks. H- Humans should not be doing that. There's no future where humans are going to do this. It's just not going to be a thing, right? So, so today that's what we focus on, right? So, we focus on the food assembly. W- Which means it kind of like, you know, like you have to scoop food from the big hotel tub, and you have to not crush it, you have to work with any portion size. Customer wants 53 g of shredded chicken, you do 53 g. You got to be consistent. Then you have to detect and track and place the carrots into whatever compartment the customer wants, but also spread it the way the customer wants. And and of course you have to do this in a way that's scalable so that you're not making custom software or custom hardware per ingredient or per tray or per customer, but rather it's really a AI-driven more flexible solution. All right, let's talk business. So average assembly line worker would I don't know would make 50, 60k like something around that a year. So how do you price for your services? Is it like a yearly subscription? Yeah, so we'll charge we're charging a yearly recurring fee. And that's of course less than humans. So we're each robot's kind of doing the work of two people. And of course again, nobody's being fired, right? They're Those people are going to do a different task. It's probably better to do that other task which is less redundant. And so yeah, like our business models we're going to we're going to charge them a small kind of implementation fee. We call it like a NRE, non-recurring expense. And that's mostly just for like the initial configuration, installation. Like we're going to have a couple of apps engine applications engineers who fly out and deploy the thing and train the team, things like that. But there's no big CapEx up front. Right? So they they basically say, "Okay, look, you're going to pay a small non-recurring expense." And then once that's done, you're going to pay us a yearly recurring fee. That yearly recurring fee is going to be less than the cost of your people, that's two people. And then the ROI for them is really like, you know, yes, Chef is cheaper, but that's honestly like number five on the list. The the biggest ROIs are really like, you have to remember there's a big labor shortage. The other thing is that like they often can't run all their lines. So if they have 10 lines, they can only run seven because they just don't have people. They don't have a supply of labor to meet the demand from customers. So they they're under they're under producing. So if we can say, "Okay, well line eight over there, why don't you put these eight robots and line eight can run now?" That's a ton of money for you, right? So increasing revenue is something we think a lot about. Often times we can help increase throughput, average throughput. Robots don't fail, they don't slow down, they just like go. Whereas like six hours into the shift, humans they get tired. So Chef can usually increase average throughput, which is again a lot of revenue. We we usually think like I think the best businesses are businesses that increase revenue more than save cost. So we we help with that. And then we also help with like yield. Like we we we like waste less food. So, what's next for Chef Robotics? Like are you guys going to be raising another round? What are you going to be focusing on for the next like let's say a year or two? Let's see. So, there's a few things that are top of mind. So, one thing that's really exciting about Chef is we have a really good set of like existing customers that are quite big customers. I mean these guys have like lots of different plants all over the world. And so, really landing landing and expanding, which is a lot of customer success. And really like just essentially living with them. Like really making the product extremely good for them. Obviously, there's a lot of product and engineering work to do that. But we really spend a lot of time on that because we think that if a customer buys two robots, that's not that impressive. But if that same customer buys 50 robots, that's extremely impressive because they're not going to buy 50 unless the thing really works. But of course, we have to really make it work then, right? And that's the sweet sweet recurring revenue per robot per year. So, it's it's good for your company. Good for the business as well. So, yeah, kind of scaling within current customers. Now we're at a point where we obviously kind of announced what we do recently. And now we're at a kind of a point where we do want to scale go-to-market and sales and marketing. Honestly, we've been very quiet. I mean as you've probably seen, we've been very quiet. And and the reason we've been very quiet is like, you know, we we felt like we had something we're onto something. And you know, we're so focused on current customers that getting more sales folks or marketing folks wouldn't really do much. We we can't even handle the demand, right? But now we can. Now like like we feel like the product's ready to scale and we have the team to execute against it. So, it's like okay, like really scaling go-to-market. So, that's like getting that new customers. And then I would say number three is really kind of continue to really invest heavily in AI. So, we have this like dedicated AI team now who who are kind of using imitation learning and learning from demonstration. And also decision transformers to kind of say, "Okay, well let's use production data. Let's combine it with like imitation learning to learn new SKUs, new products, new ingredients. And let's try to get build like more of a generalized food manipulation model." So, what I've observed from like researching you like talking to you, you're really good at picking the right problem. And I feel like a lot of people like myself included like have been like unintentional with a few like ventures. So, what advice would you you to people like when when they're starting something? What should we decide to focus our time on? This is a obviously there's a big can of worms here, right? I think broadly there's like two different schools of thought I've heard that I've I kind of like think about. It's like one school of thought is this passion hypothesis, which is kind of you look inwards and you're like, "What am I passionate about?" And you do you do that. I think that can work. And if you're passionate about something done, easy. Especially if the the passion matches up with a big market and like a big opportunity. But the truth is that like I'm not like before Chef or like before Protoype, like I wasn't inherently passionate about like the visually impaired or food. Like I love robots and AI, but honestly food is not like I'm like I never loved cooking or like yeah, so I wasn't deeply passionate about it. And like before Chef, like I wasn't like passionate about really this thing. And I think a lot of my founder friends are like this. It's not like Aaron Levie super passionate about cloud storage. You know, you don't wake up and be like or like HR software. It's like let's go. Not like most people are not super passionate about these things, right? So the passion hypothesis says that like passion leads to success. And there's another hypothesis which is like that the equation's kind of the it's inverse, right? Is it impact? It's what's success. If you're successful, that leads to passion. I tried the passion thing which is like, "Okay, like what am I what am I what do I care about?" And like yeah, I I I I guess I figured out that I I I like air robots. But then I I did the opposite, which is like, "What's the right company I can start that will be successful? How do I increase probability of success?" Because as soon as things start to go well, it's very easy to become passionate. Like if you're really good at something, if you're just winning, then you'll become passionate. So for me this took the form of, "Okay, let me find a really big market." Like, "Okay, let's look at the data. What what is the big biggest market?" It's like labor industry. It's like, "Okay, food is the biggest market tractable." Then it was like, "Okay, there's a problem." Then it was like, "Okay, assembly is the right go-to-market, not cooking or prepping." Then it was like, "Okay, manufacturing." Today if you look at Chef, you're like, "Why did he end up or we end up in food manufacturing?" It's kind of like not sexy, it's kind of boring, right? On the surface. But then if you look at this history, it's like, "Ah, like today they're building this, but tomorrow they want to build that." It makes sense. So I I tend to think like figure out what's going to make you successful, and then passion would follow. Well, with that said, I I you so much for coming on the show. You answered like amazingly. Thank you so much. Yeah, thank you, Manav. Appreciate it.