Jake Aaron Villarreal: I'm Jake Aaron Villarreal, born and raised in Silicon Valley. Here to take you behind the scenes to share what it's like to be a startup founder, the journey they're on, the problems they're solving, the products they're building in an effort to transform industries. I'm excited to have with us today Guillaume Luccisano, co-founder and CEO of Yuma AI. Guillaume, welcome to the show.
Guillaume Luccisano: Thank you. Thanks for having me. Hi, Jake.
Jake Aaron Villarreal: Well, thanks for coming on. I know we had a call a few weeks back and I've been thinking a lot about our conversation then and happy to have you back and and talk a little bit about your company and the problem you're solving today in this whole mecca of AI that we're seeing rapidly take over a lot of different sectors and industries. Um, before we do that though, uh, where, uh, where are you joining us from today?
Guillaume Luccisano: I'm in Boston. Actually just moved to Boston a few, few months ago.
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I love that area. Where did, where were you before Boston?
Guillaume Luccisano: Uh, interesting. So, I'm French originally as you can hear with my accent. Um, yeah, spent 10 years in San Francisco. Uh, amazing time there from 2010 to 2020. Moved back to France for COVID... for COVID. Then after a short trip in Singapore and moved back to Boston for uh back to the US, exciting to be back to the US. Many reasons. Our customers are here, our team are split between the US and Europe. So it was good to be back uh back in the US and East Coast this time around.
Jake Aaron Villarreal: Yeah. Got it. Very cool. Well, East Coast, West Coast, technology is innovating everywhere and uh I guess before we jump into your story, just a little bit more background on uh Guillaume. He is, you know, as we know from France, a serial entrepreneur, angel investor. He previously was the co-founder of Socialcam uh and Triplebyte. Currently he is building his third Y Combinator startup as we talked about, Yuma AI, uh which deploys autonomous AI agents at scale to help merchants automate customer support. Um, we're going to talk a little bit about your company and the problem it solves today but I want to touch base a little bit more on your background.
We kind of both started in technology. I started in Silicon Valley, you you came to Silicon Valley. Um, Justin.tv was a company that we had heard about for a while and you were part of that which ended up uh having a great history. Um it morphed into Twitch which was acquired by Amazon, and the people that you met there, the founders, uh you continued to build with. Went to Socialcam with Michael Seibel who was Y Combinator partner for many years now, but really had a great exit there. In parallel when that was happening with you, I was doing the same thing but in startups. Uh I'd also been working in Silicon Valley and trying to figure out what was the next transformation that was happening. You know, the .com boom came and went in 2000 and then around 2007, 8, 9-ish we saw this mobile transformation come, and social and video and streaming and it was all kind of "what was, what was it going to become?" and gaming and all that came around. And it sounds like you were in the right spot at the right time. You were part of the exit of Socialcam. We talked about that a little bit which was a, a nice exit. I think you shared like 60 million or somewhere in that range. Um at the same time I had built a company, we had an exit as well and so as we continued in our parallel journeys we kind of seemed to be aligning in different areas. But you had a technology platform that was acquired and then you went on to become your own um CEO and leader of of companies.
So, a really good transition there of where you started, where you're at today. But in that, as you grew up and going back a little bit farther than that, did you have that DNA of being an entrepreneur from an early age or what really inspired you to to get into that whole sector?
Guillaume Luccisano: Yeah, I I mean it's, it's, it's an interesting question. So, I think I you know, it's hard to say. I mean because when you're a kid like it's you know, you you want to build stuff but projecting yourself that far, building a huge company, is something else right? Um, always wanted to build something, um and I think the lucky thing here is that I got into software engineering, so I started to build things. And naturally when you're in software engineering it's easy, it's easy to put something out to the world, right? Easy to test something, easy to give it to users, easy to test. So I think that's what made the, the bridge here. I wanted to build things for people and and being in software made this a possibility.
And I think as you said, um, so you know I did like an engineering school uh in Paris and interestingly that school was you know, it's called engineering school uh but it's actually a coding school. So what we did for five years is just coding. And it's interesting because like the more you code the better you get at coding. And and and I think like that was a great school in that sense where it was great to build stuff. And so you know, shortly after finishing school I arrived at Justin.tv uh in in SF and that's where you know I got extremely lucky and you mentioned that, like awesome founders, awesome environment, the momentum was crazy. Like it was on mobile, it was, it was social, it was as you said like I mean the live streaming and the video on mobile was emerging. So I was, I got lucky to be kind of the right place at the right time on that front that really helped me um you know, becoming an entrepreneur there.
And I think like here, shout out to Michael like on that front you mentioned him, but like basically I mean the backside of the story here, that what happened, I was I was at Justin.tv, like I was you know new employee there you know, we were probably 25 people when I joined Justin.tv. But came back from vacation one day and Michael came to me and said "Hey, um, we have this product here, uh Socialcam, and I've been working on it like and we're going to do a spin-off. Do you want to be part of it and be a co-founder with me, with another engineer?" And it was like you know, it's kind of like lucky to be at the right place at the right time where I had the chance to be a founder. And it was an easy pass for me, like it was not you know, like there could definitely have been a more struggling path to become a founder and here it was an easy pass where it's just like it happened and it was a great, great beginning.
Jake Aaron Villarreal: Yeah. Right time, right place. Um, how did you end up getting connected with Justin.tv in the first place? How did that happen? Did they recruit you? Did you connect with people that they knew?
Guillaume Luccisano: Uh, it's interesting. There is a... Okay, so Justin.tv was a Y Combinator company and Y Combinator had an event that called Work at a Startup and I think they had this in 2010... well 2009 or 2010 probably. And they did this again recently, but basically it was an event, Work at a Startup, where you just apply, you send, you send your resume there and all the YC companies at the time could look at it and invite people over. And and that's what happened. Applied there, got lucky I got connected to uh some great startups back then and um Justin.tv was one of them and the rest is history.
Jake Aaron Villarreal: I like it.
Guillaume Luccisano: Exactly.
Jake Aaron Villarreal: That's really amazing. Yeah, we've heard so much about that story over the years, but it's good to talk to someone who was on the inside of kind of how things rolled out and how things transpired. Um, you know, when we talk to vendors or we talk to founders rather, it's always about what problem are you solving that's you know, helping a company do their job better or create an efficiency somewhere and is it worth paying for? You know, AI is, you know, a part of every sector's life today and it's going to continue to be. Give us a little inspiration about what happened, how did you come across the idea of Yuma and really what's been the the inspiration behind wanting to try and solve this problem?
Guillaume Luccisano: Yeah, totally. So, uh I guess as a background, uh you mentioned it at the beginning, but we are building a platform to deploy AI agents at scale for e-commerce, for merchants, to help them automate their support. Uh and the way it started... okay, so the way it started, uh that's an interesting one. So, um I just had moved to Singapore. Uh I was somewhat on a break and I got very excited about AI. Anything about it was pre-ChatGPT. Um, and the thing is I had a good friend that was working at OpenAI at the time that left OpenAI to build his own company. And we were talking. I was like, "Why? I mean, I saw you were doing great, you know, a good job at OpenAI. You loved it. Why? Why are you leaving? I mean, what's happening?" And he got me all excited about LLMs and generative AI. Started to build prototypes. Uh, and it was like actually extremely exciting because back then, you know, it felt like all the big wave technology waves had faded out. You know, mobile was kind of like faded out, SaaS was faded out, like you know, crypto was, was gone uh back... And and like there was nothing and boom, this is, there were these sparks of LLMs coming up and this, and um we could see that there was something, I mean I could see that something big was coming there. Built a bunch of prototypes.
Um, and funny story, I had a Shopify store at some point in my life, you know, as a side project when my first daughter was born. I kind of like fell in love with like a French brand selling toys and I said, "Oh, I should do that for the US." And, you know, contacted them, started selling those toys in the US. Uh, and so I had some affinity with like being a merchant and and and owning a store and having to deliver support. And uh one of the obvious use cases with LLMs and generative AI is like support. You know, you see that you can generate messages and it seems like, "Okay, let's you know, let's answer." Uh it seems, it seems easy. Uh so built a prototype there. Um uh I had a friend that is a founder of Gorgias, which is like a helpdesk for merchants, and was talking to him and he said, "You should, you should make an app." Uh I made the app in a week, published it. And uh basically at some point the next, you know, published it, nothing happened. It's usually what happens. You launch something and nothing happens. It's always, you know, you always get ready, "I'm going to launch something" and but always nothing happens. So I launched it, nothing happened. But like three days later I wake up and had 50 emails from merchants and they wanted to try it out.
And lucky me, it was exactly at the same time as ChatGPT came out. It was about the same technology and the same time. And and it was just looking like a a co-pilot for a support agent helping them generate drafts to answer you know, customers' inquiries faster. And I woke up and I had those 50 emails and it was just the morning. So you know, I kept getting more emails every every few minutes and I was like, "Oh, well, there is something there." Like it, and and I'm not good at ideation. You know, I think I'm pretty decent, pretty good at building products and iterating on products and delivering something to users. But coming up with a good idea is difficult on what to build. And here, like I could sense this pull from the market where, "Oh, there is a need there. There is a problem with support. Support is broken." Support is usually low quality. It's very painful for merchants. It's costly, expensive. Nobody wants to do it. So support is a huge pain and it's like a huge source of cost, a huge source of frustration for merchants, for customers as well obviously, because like you know, how many, how often like did you have to like talk to support anywhere and and you had to talk to a dumb chatbot or interact or just wait for days to get an answer, right? So like, support is bad. And and what we're doing is, you know, we want to end bad support. We want to bring great support for every customer and we want to solve that problem for merchants.
Jake Aaron Villarreal: Yeah.
Guillaume Luccisano: So that's what we are... sorry I got, I took some tangent here, but uh from the very beginning to kind of what we're doing now.
Jake Aaron Villarreal: Yeah. No, that's really cool. I mean, uh customer support and focus is it specifically in e-commerce companies?
Guillaume Luccisano: Uh it's, it's a good point. So uh we started with e-commerce, but now we have retail stores that you know they have physical stores. So we can do hybrid, any, any merchant. I will say if you're a retailer, you sell online or offline, we can help.
Jake Aaron Villarreal: Yeah. There's a lot of innovation in that space. I mean, I just... I'm using a new platform uh in the last, you know, week or so here and I had an issue with it. And you know, they have the chat, you know, support that you can go through and then you get someone and you're talking to an AI and then pretty soon you're talking to somebody that's a real person. And then even then you're still like, "Okay, well, that sounds like a problem. It's a little more complex. We'll get back to you in 24 to 48 hours." And it's just not like ideal. Now, maybe I had a complex problem or maybe that's just the, the standard for responding to to customers that have issues.
Guillaume Luccisano: So, that's a good point, right? And and that's, I think that's what's changing. So, what we saw in the past is kind of the... and that was the beginning, right, of using LLMs for support, is to do Q&A. You ask a question, you get an answer. And so, you have a knowledge base that's just going to give you an answer like an, like an FAQ. And what we do, and if you really want to solve a customer's issue, is you need your AI agent to take action. So you need to give the same abilities that you give to your um, you need to give the same abilities to your agent and the same abilities that human agents have to deal with a request. So for example here, for your particular request, you need to have an agent that can take action, that can find information about, you know, your account, your specific problem somewhere in some some external services, but also can take action to solve it. And that's what we do. That's how you solve support, is actually by mimicking what any support agent is going to do, connecting that agent to external services. Um, um, and so maybe the tool you you played with... did I mean you played with... you interacted with didn't have that. A lot of the support AI that we still see at the moment don't take action. It's very basic Q&A.
Jake Aaron Villarreal: Yeah. And the next, you know, the next generation is definitely coming there and taking, taking off.
Guillaume Luccisano: Yeah.
Jake Aaron Villarreal: Well, it's... it could be a good customer for you because it certainly was frustrating for me. And you know, ultimately I ended up just having to hold tight until they got back to me and it was a very fairly simple request. Um, so I was just a little shocked and it's a pretty good company. They raised $70 million. They, they're doing well in the market. It's not like they, they don't have the money. Um, but I think just the process uh of really getting to the right answer for the right person and the right problem is, is the key. And you talked about AI agents and we're, we're hearing a lot more about agents being more, more engaging and really taking initiative, not necessarily just giving an answer. So talk to me specifically about how it's different now versus how it used to be. And and your product specifically, like AI agents, we want to see the action being taken, but maybe it's not always taken at the level we would hope. What's yours do differently?
Guillaume Luccisano: Yeah, no, that, that's a very, very good point here. I started to talk about an agent, but I think it's good to take a step back and look at what are those and what they do. So um, in short, basically an AI agent is using an LLM. Uh so like, let's assume... let's say using ChatGPT for, like, to to simplify. So we use ChatGPT, uh we give it a process to follow, uh and we give it access to, again, external services or actions they can take. And the goal is really to replicate what a human agent could do to solve specific inquiries. Uh and by, by giving this agent the right process at the right time, with the right tool at the right time, and with the right quality control and and safety boundaries, um you can basically build, mimic or replicate the behavior that a support agent will do. Like, you know, first you get, you get a ticket. It's some inquiry about, you know, changing an order, changing the address on an order for example. Like, first the agent is going to have to find the order. So it's going to have, you know, if it doesn't have the enough information, it's going to ask, ask for more information. Then the AI agent is going to go find the order. Then after, it's going to take the action, it's going to confirm the action with the customer, and it can solve if, you know, end to end it can solve the request. Um, and and and, and that's what we've been building basically for the past you know, year and a half, is like how can we build that platform that orchestrates those AI agents, and again, specific for for uh eco-, for a retailer, uh for a merchant and for support. Because like, and we have to be specific, because the type of requests you get is going to be different if you are in the, you know, hotel industry, e-commerce, like uh, you know, airline. It's very different. Like support is very different. Um, and being focused on support is also important because like, it's not the type of same type of request you get if you are you know for, for a merchant. There is the, there is what happened before a sale and kind of what happened after. Uh, it's not the same type of requests. Um, does it answer the question?
Jake Aaron Villarreal: Yeah, it does. Yeah, it does. For the listeners that can't see the product, walk us through it. So let's... you brought up a retail company. Let's say, you know, it's a company that's selling shoes, and you know, they got customers coming in and buying. Maybe they're buying in the store, maybe they're buying online, whatever their website happens to be. But there's issues that come up. They need to talk to an agent. They need to talk to somebody to get some support. Where does your agent step in and what specifically can it do all the way through? Walk us through what it looks like as you're logging in. Is it a web, web page you're logging into? And y-
Guillaume Luccisano: It's, it's a very good question. Okay, so those merchants, what they have in the background, they have a a support ticketing system, right? They have a way, and we call this a helpdesk, they have a way to... it's kind of a mailbox, right? A shared mailbox for all, for to manage support. Uh, and so they receive requests there and those requests can be you know, they can be a chat, they can be an email, they can be a contact form, a WhatsApp, SMS, kind of any channel. The goal is to aggregate all the channels there. Uh and what we are at Yuma, we're a plug-and-play solution that we connect directly to this platform. So this, this ticketing platform, this helpdesk. And we basically add a new agent to it. Except instead of an agent, it's going to be an AI agent. And what we do is every new message, every new request that comes in, uh we're going to analyze it and see if we can trigger our agent on it. And we're very big on safety. So the goal is to be, be very safe and see like, "Are we allowed to take on this, this channel? Are we allowed to take to look at this type of request?" you know. And if we are, we look at it and we basically go try to find the process to try to solve it. So if it's a, you know, order status inquiry, we're going to trigger our AI agent about order status. If it's an order change, we're going to trigger our agent about order change, and we're going to try to follow the, the process here. So the process is always custom, uh based on the merchant, what they, what they want, their policies, uh based on their integration. Uh and the goal is really to try to solve fully the uh the request that comes in.
And so we're very transparent, right? It's just like adding a new agent on your team that's just going to start taking on tickets just like another support agent, except it's 24/7, any language. It's kind of like, you know, the... has the full knowledge. Um it's going to be faster. Uh it's definitely an unfair advantage compared to humans, uh if you if you look at it this, this way. Um and right now our top merchants can automate, you know, about... fully automate, like full automation, like no human interaction, like close to 60, you know, about 60% of their tickets, right? And that's a huge number. Like we have some merchants at the moment, we're automating 5,000 tickets for them like during Black Friday, like season like, you know, 5,000 tickets a day we're just automating those for them. And it's just like, it's huge, especially during peak season. It's like, which peak season are big issues for retailers because they have to staff and you know like it's temporary and and we can come in and do that. Um that's basically how it works. We connect and we you know we do uh, we bring those AI agents to the platform and it's transparent. So any, any channel of communication, uh chat, email or else, uh we're taking it. Voice is going to come. Uh, voice is a bit more challenging because if you want to be very safe and have quality control and and and be fairly advanced in what you can do, you have this problem with the latency because you have to be fast. Um, that adds some challenge, but voice is definitely coming. Um, yeah.
Jake Aaron Villarreal: Yeah, that's really cool. You've got, I mean if you think about commerce in general, there's a huge market. And I know customer support seems to be one of the easier areas to to really use the application of AI and AI agents for reduced cost, you don't have to hire as many people, you know, there's no emotions involved. So you, you, you've gone out, you've raised, you know, $5 million, you have a team, you're executing on bringing this product to, to the market. As a company uh and as you're competing with a lot of different technologies today um, trying to capture this space as well. What, what, what's the biggest challenge for for the company today?
Guillaume Luccisano: Um, I'll say three uh at the moment, right. One of the big ones is staying at the edge. So I think we are at the edge of what's doable with AI, but I mean as you know the world of AI is moving just so fast at the moment that uh, definitely challenging, you know, we need to keep pushing every single day here. And it's interesting because like you know, it's my third company and I don't think I felt that much pressure to go fast before. Even though you know we had the pressure before, like we had always had to go fast, but like it seems this time it's like, this time it feels like we need to be all in all the time to deliver for the best product and the best value and to stay really on top of of of of the tech like all the time. So that, that's, that's number one. Like keep bringing new capabilities. And our merchants pushing us every day to see like "I want more, I want to automate more." So how do we keep doing that?
Um, and at the same time, AI can be complicated to deploy. You know, it's not always magic. It's not like a push of a button like "Boom, I have my agent and now I'm automating support and I can go to sleep and I'm done with it." Right? Like it doesn't work this way. You need... otherwise it fails. You need to tell your AI what to do, when to do it and and you know, correct it if it goes off of course. And so finding ways to simplify and to make this moment more magical is a big deal. So that's one of our challenges as well. Uh you know we're making progress. Everyone is trying to make this simpler, adopting AI simpler. But ideally adopting an AI agent will be just like you add a team member in your, in your team and you say, "Okay, now you are in charge of this. If you have any question, you come to me," and boom, it's done, right? That's kind of the end goal. You want to get there. We're not there yet, but we want to get there. Um, and then after the other challenge for us as a company, um, I will say is our US expansion. Like you have been very good in Europe and we have some great brands in in North America and in the US, but like we need to accelerate in the US. Um, and and that's I guess that's my fault you know, being maybe being French or whatever like we... but uh, but that's internal, that's us uh you know. Be more aggressive in the US because we have uh uh to be uh... yeah.
Jake Aaron Villarreal: Yeah, got it. You know, we we hear all the time when you're building technology and you're bringing products to market, you know, you have to have a moat. And sometimes it's just you're first to market and that's your moat because no one can catch up. Or maybe it's patents you have that no one can really use without paying you. Or maybe just in general it's hard to get into a spec-specific sector and you know, the moat is just trying to get in, it's really expensive. Um we are looking at what's happening in the industry when when it comes to people. Because without people the technology isn't really going to innovate itself. You need the right team. And so we talk about what's the moat around your people? Because what we're seeing, and this is really across the industry, is you've got the big companies, the big tech companies, you've got the big AI companies, and they're trying to scale up as fast as they can. They're in an arms race and they're also looking at where do they find their people? And they're talking to every company that has AI engineers and have people in the AI space. So it's not, it's no longer the small startups that you can hire people and keep them. It's you hire people for your startup and you're also, your people are getting messaged left, right, and center about "come join X company. We're bigger. We have more funding. We're scaling." What's the mo- what what are you doing to keep your people on board, focused, engaged on mission, and loyal?
Guillaume Luccisano: Yeah. Yeah, that's, that's a very good point. So I think one of the answers here back to what we said earlier, so we're not in SF at the moment. We have some people in SF, but we are not in SF. So we are, we are spread. Um to keep people, I think we have you know, we're working hard to just build a great product, deliver value, and and and delivering value and growing and being at the edge technology-wise like is fairly exciting. And I think everyone is finding it, find it, you know, very exciting at the company. So I think that's um you know, we move fast, we build great people, we deliver value and that's usually that's a good combo to kind of like uh keep people uh excited. Uh good vision as well, you know, based on where we're going on support right now, there are more things we want to do. Um but I'm with you, it is it is definitely challenging uh you know, like you do want the best people. Uh I don't think there is any particular secret uh here. I will say avoiding, avoiding SF is probably good. And the fact that we're not limiting ourselves to a particular geo has been, has been good to us. So we have been able to you know, get talents in many places where they are.
Jake Aaron Villarreal: Yeah, I think that's really a huge, huge, huge advantage for startups or even companies in general. That if you're not tying yourself to a specific geography... I know it's sometimes desired so you can get together with teams on a daily basis, but...
Guillaume Luccisano: Oh yeah.
Jake Aaron Villarreal: You know, there's a lot of tools that are helping companies just build remotely and sustain and scale remotely. So I think you have an advantage if that's your strategy. Um, we like to look at, you know, what what's the career track you're you're bringing people on and what's the vision they can see themselves continuing to grow with the company in. Uh, so that you're not just having them come on board, but you're really painting a picture of where they can be as you succeed. I mean, we we say this, but so many times when we're talking to candidates and they're coming to us, it's they've lost touch with their founders. There's, you know, you have one-on-ones, but you're really not talking and asking the right questions of, you know, "Are you really happy right now? What do you need from us to to really satisfy, you know, where you're at in your career?" Like the tough questions. You don't want to ask those questions because the fear is you can say, "What do you need us, need from us?" And the answer could be, "I need more money. I need uh more autonomy. I need to work from home." It could be a number of things you don't necessarily want to hear. But if they're uh being honest, at least you can support the process. The opposite to that is you get an email or a call, you know, someday and it's like, "Hey, I'm putting in my two-week notice." And it's that everyone gets it and you hate it, but what could you have done differently? So, being pre, proactive and preempting that, we just, you know, we just think it's such an easy thing to do, but I think it's something you forget about as a leader. We've, it's happened to us too by the way. So I'm speaking from experience. Um as a company you're, you're, you're growing, you're building. There's a lot of conversation around agents. Um you're talking about e-commerce but now retail. Is there any area uh that you think has the most growth for the type of product you're bringing to market as you look at 2025?
Guillaume Luccisano: Yeah, I think it like uh, what we see is that first we, we're going to keep diving into support as we do. Like you know, covering more ground, doing more, expanding and raising up that automation rate for our merchants, bringing you know more value. But I think merchants, the more we talked about then, the more they want an all-inclusive solution, which means like, they want something, they want help on support, but they also want to help on pre-sale uh, which means like you know they want sales, they want AI full cycle. They want AI on their website to help, you know, convert and and and do more sales, but they want AI after to help, you know, support customer requests. Um, and you know, no choice. We uh we're definitely going to do this uh because they want and it's easier this way, right? We started on support so we can do all the support things and after we can uh can come and help uh for the rest as well of the journey.
Jake Aaron Villarreal: Wow, that's really exciting. I mean, we're seeing a market where AIs are going to be talking to each other from sales to support to innovation, um, operations, uh, marketing, like all across the board. We see a world where, you know, it might just be a handful of people and you're hiring agents that are integrating and communicating and, you know, getting products into market and selling and supporting. So, that's kind of what we're seeing. I know it's coming. I don't know when and who's going to do it all, but I don't know if you need to do it all either. Might just be part of a a strategy of part of the business. So, that's really, that's really exciting. As you head into 2025 on the roadmap, I think you kind of explained where things are headed, but is there anything else that uh that we can be excited about over the next six, 12 months that you're bringing into the market aside from coming into the US and really accelerating here?
Guillaume Luccisano: Yeah, I mean this is this is you know one of the big uh big ambitions. Uh definitely bigger in the US, uh bigger presence in the US. Those full customer journeys to be here from start to end, very important. Uh voice is coming up obviously you know, our goal is to be omni-channel. We're going to cover the customer wherever they are, whatever channel they want to use. Um those are the big things, but they're you know big enough uh that we definitely have uh have a lot to build here. And the goal is augmenting and stay at the edge all the time. Like we have no choice if we want to keep automation to go up. And those AI agents you know to go from a good ID to something that keeps bringing value at scale like it's definitely not the same thing. Like you know and and we need to keep pushing on that.
Jake Aaron Villarreal: Yeah, really cool. Improving. I love that. Well, if anybody wants to find you or they want to find your company, where do they go?
Guillaume Luccisano: Uh you uh, that's a company. Otherwise uh, on LinkedIn uh and Twitter going to be there. Yeah.
Jake Aaron Villarreal: Very cool. So that's yuma.ai. Um and uh yeah, extremely excited to see where things go. Uh happy we had a chance to talk here and excited that you came on to to share your story. And for the listeners, I'm excited that uh you shared your time with us today. Means a lot to me. I'm your host Jake Aaron Villarreal signing off for now. But can't wait to catch up with you all on the next episode. Until then, take care. If you like what we're doing, don't forget to subscribe, leave a review on Apple Podcast or wherever you listen. Follow us on YouTube where we go behind the scenes to learn what it takes to be a startup founder.
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