 From Austin, Texas, it's theCUBE, covering South by Southwest 2017. Brought to you by Intel. Now, here's John Furrier. Welcome back everyone. We're live here at the AI lounge with Intel, hashtag Intel AI. This is theCUBE, I'm John Furrier. Our next guest is Michelle Baccarat, who's the co-founder and CEO of Find Mine. Retail startup out of New York City. Entrepreneur, welcome to theCUBE. Thanks for joining us. Thank you, thanks for having me. You're in the Intel AI, pretty packed here, isn't it? Yeah. I'm pretty proud of it. I think it's the cover from the rain. Full of rain here, yesterday was hot. You got a panel here later in the afternoon about AI and retail, the convergence. But I want to ask you as an entrepreneur, what got you into starting this company? Was it an itch you were scratching? Was it a vision? Was it something that you felt compelled to do? Give us the story of Find Mine. Yeah, it's actually a little embarrassing. It kind of sounds like the most selfish reason to start a business, it's because I had a problem that I wanted to solve. But I think that's the best way to start a company, honestly, because it means you're gonna be passionate about it, you're gonna be a user of your own, whatever you build. And for me, that challenge was I would buy, you know, like my silk bomber here with this big flower on it, and I'd be like, yes, I love this, this is great, and I would get it home. But I wouldn't have tried it on with, you know, the pants and the shoes that go with it. So when I get it home, I'd be like, uh-oh. Now I have to figure out how to put an outfit together around this to wear it and feel confident. And I think a lot of women especially have this challenge where we feel pressure to be stylish, but not everyone has that kind of style gene where you can just see something like this and be like, oh, I know five ways to wear that. So I struggled with that. I struggled with that when I would buy furniture, even when I would buy things like electronics, like I was really looking into buying a drone at one point. I was like, oh, that sounds cool, I could fly a drone, I want to learn that. I found the drone model that I thought I wanted, but then it comes with all this stuff, right? All these peripherals, they don't all plug into the drone, so the research involved to figure out how to use one product in combination with another product was way too much work. And I figured someone should be automating that and help a consumer like me answer the question, how do I use this for any product that I might pick up on the shelf? And so that, that was the catalyst. So where is it now today? What's the status of FineMind? Yeah, it's fine. Solving all the problems, did it? No, not yet, close. No, but so, you know, that was like seven years ago that I started noticing this problem in my personal life. Then I researched and found that tons of other people have this problem, customers will buy 170% more if you show them how to use the product that they're buying, but I didn't have the tools to solve it. I have a product management background, but I wasn't a computer scientist, a data scientist to actually like execute it. And so I met a friend of mine's husband as a computer scientist and I sort of like, you know, suckered him in with like one little project and then he was like, wow, this is really interesting. He cares nothing about fashion, by the way. Like he wears his Columbia sweatshirt and jeans like every single day. So he doesn't really feel the problem the way I do, but what he saw was this opportunity to use artificial intelligence and machine learning and technology to solve this really interesting problem of like, can we make a machine replicate what a human does, which is like figuring out what's stylish. And then that's what hooked him in and he thought the problem and the application of the technology was so cool. So that was, you know, in 2014, we started working on this. Since then we've, you know, launched a product, we have customers on board, we work with fashion brands and retailers, we produce revenue, we raise money, we have a team now, we have a real office, we're not working out of our apartments anymore, so it's going. And so now you're in the middle of this AI world and if you think about the data, your problem that you were originally solving actually applies to a lot of things, whether it's learning, healthcare. So it's kind of like the data drives more opportunities to collective intelligence. Is that kind of where this is going? And you see that the trend where it's the data in the algorithms or the algorithms in the data? Yeah, I think that access to the data is a big factor. So in retail, there's tons of data, right? Transaction data, product data, user data, all that kind of stuff. And a lot of it is very easily accessible. It's not all like private information, customer information that you have to guard really closely. Obviously there was some of that because you're doing transactions, so it's credit card information, there's location data, you know, gender, all that kind of stuff. But the product data is publicly available. So we didn't even have to have a customer live before we started doing cool stuff with machine learning with large data sets because we would just go find products that were live on the internet and use that data. I think in different industries like healthcare, it's a lot harder to come by the data and there's a lot more concerns around it. Michelle, what are some of the learnings that you've had now if you look back, where you are today, where you were, what are some of the key learnings with the venture you're building around what was surprising to you, what popped out as value? Was it the machine learning? I mean, what were some of the learnings you could share? I think in general, my best piece of advice for startups is just don't die. And I say that a lot and people laugh, but it's so true, like I've seen so many friends with startups that kind of had a moment where they were like, okay, it's all falling apart and they just, they said, okay, that's it. But if they had stayed around for like five more days, 10 more days, 50 more days, like how their fortunes could have changed is incredible. And we've gone through that, I've seen other people go through that. So that's number one. And then number two is like, don't wait, just do something. So I think for a long time we were sort of like waiting to get like the right data sets in the right order and like getting it all perfect first. And that's not the right way to approach it. Just go. So get a horse on the track and at least run the race, get something going. Yeah, exactly. And don't run out of cash, as I always say, you can't go out of business when there's money in the bank. Yeah. So okay, so now on the tech side, what has surprised you on some of the amazing things that are now starting to come into visibility for you? And what do you see as your vision? So what's kind of obvious and that you're going after? And what are some of the things that you see in your vision that others might not see? So what's really what we're doing right now and every startup needs focus, you can't do everything all at once, but you do need to have this bigger vision to make it a billion dollar potential kind of exit company. Cause that's what people want to invest in if you want to take venture capital and not every startup needs to. You can sell finance a business. But for me, this rapid growth was really important. And so I think what was really important was that we kind of like built something that could scale long-term. So this broad vision of like every single product that you could pick up off the shelf as a consumer, you know exactly how to use it. For me, there's like a personal mission in that because I hate waste. I went to Berkeley like we talked about before. So I have a little bit of like that hippie mentality and I was buying all this stuff like in fast fashion and just sat in my closet and then we'd throw it out or I would never use it. And that made me really bummed. And the reason I was throwing it out was cause I didn't know how to use it. And if I had just gotten that piece of information up front, then I probably would have been able to integrate it into my life and I wouldn't have thrown it out. So doing it across all industries and retail. So really efficiency too is key on this. You can actually accelerate that. Absolutely. So on the fashion side, is that where the focus is now on the retail side or is it still on that? Yeah, so we're B2B. We sell to fashion retailers and brands. They use our technology and then they figure out where they want to get it into the consumer's hand. So it might be on the e-commerce page. It might be in the store. It might be in the associates phone. So that you as a shopper don't even know that a customer, the associate is kind of cheating, right? They're looking at a fine mind to find out what outfits to recommend. They might just be having an interaction with you like a human does. But they're using an assistive tool to get that efficiency that you mentioned before. So you have a panel coming up this afternoon without giving away all the content. What's the topic that you're going to talk about? So the panel is artificial intelligence for good. And ours specifically is autonomous worlds. So it's about the automation that's kind of all around us and becoming more ubiquitous and how artificial intelligence is making that possible. So I always get, I'm so amazed by autonomous vehicles because I think it's so obvious mental model because we all have cars or have been no transportation but it's pretty radical when you think about the impact of autonomous vehicles. And I mean, this is pretty amazing trend. I mean, all smart cities is also mind blowing as well. Think about what's going to happen for the digital citizen. What are those services? So there's some amazing potential but also work that has to get done. What's your thoughts on those two trends and the impact 10, 20 years down? Will there be cars on the road in 25 years? Yeah, so actually on the panel coming up it's going to be myself kind of from the retail perspective there's going to be someone from the smart cities perspective and someone from the autonomous vehicles perspective. And I'm kind of like, what am I doing here? Like those trends are so much bigger and more like amazing and life changing than what we're doing. But I actually think that retail is so ubiquitous and like we all shop all the time whether it's through Amazon, whether it's in physical store and so it's a little bit more accessible almost whereas like the idea of having like a driverless car is harder for you to picture. And one of the things I'll be talking about probably a little bit later is how like you don't actually realize how much of this is going on around you all the time whereas like seeing a car on the street without a driver on the left hand side like the driver seat is like a shock, right? You're so not used to that. You get worried. I'll be asked the retail question because one of the things you're close to that as a retail is that you know you're seeing a lot of the brick and mortar sites becoming destination oriented. Not so much day to day shopping, e-commerce obviously exploding, it's becoming what it is. And there's some tie in between digital and analog now kind of converging. What's the big takeaway? What's the state of the art right now in retail? Is that the vibe right now that it's a combination of destination base or is there something else going on? Can you share some color on what's happening in the retail world? Yeah, so everyone talks about like, oh my God, like no one's gonna shop in stores anymore. Well, we're a long way away from that. Over 90% of all commerce is still done in the physical store. It's just that all the growth is in e-commerce and that's why everyone talks about it is it's like huge disruption because it is like all of the growth is in e-commerce which is incredible. So at some point maybe it'll completely take it over but I personally don't feel like that's the case because we're humans and we create social interaction and part of shopping is that social interaction, that consultative nature of selling that I just don't hope, I hope won't be replaced completely by a screen. So you're having fun here South by South was a little bit rainy today, got drenched as you were walking over here. What's the show like been for you? I got here this morning. Came straight from the airport to one event and then went to another event with my suitcase like trying to get around. So the rain definitely put a damper on that but I'm hoping it comes out. The Intel AI booth here, AI lounge, what do you think, pretty impressive? Yeah, we actually can check out Finemine in that corner over there, we're on that wall and it's a live website. It's actually showing John Varvitas which is one of our customers. They're a high-end fashion brand from Men's and we show the complete outfit so you can go actually like shop right there and Finemine would get credit for that. So and Intel has been an awesome partner to us and just really innovative and I love rainy street, I think it's so cool. Like these are all houses converted into bars converted into an Intel experience. It's very meta. Yeah, in the AI, very meta. It's a meta of meta. Michelle Backer, thanks so much for spending time on theCUBE. We're here inside theCUBE. He's inside the AI lounge here with theCUBE. I'm John Furrier and we'll be right back with more coverage from South by Southwest.