Chamath Palihapitiya: All right, everybody, welcome back to This Week in Startups. We're continuing our basics series. Why do we do these? Well, so many founders email me, DM me all the time with basic questions. So when we see a question come up over and over and over again, we find experts, we bring them together, and we do these very short, tight, concise, basic videos. And they explain to you everything you need to know about important topics like legal or marketing. And we decided to add AI to the mix. You can see all the basics at thisweekinstartups.com slash basics. We do this to support founders. Just plain and simple. We know they need this information, and we are delighted that our friends at Google Cloud have sponsored this season. You can check out their report, The Future of AI, Perspectives for Startups. It's got insights from 23 different top AI experts. I think a couple of my besties are in there, like I think Shamantha Freeberg are in there today. Very lucky to have Matt Ruiz here. He is the co-founder and CEO of PhotoRoom. It's a Paris-based AI photo editing app with 300 million downloads, and they process, wait for it, 5 billion images a year. Reportedly, Matt, you got 50 million in revenue already. And it's what year? When did you start this company? Welcome to the program.

SPEAKER_02: Hi, Jason. Thanks. Yeah, we started in 2019, just before COVID, actually. So it's been like a six-year journey.

SPEAKER_05: Amazing. So you can make images on every language model today.

Chamath Palihapitiya: You can jump in and just describe what you want and get something that's, you know, let's call it funny that you could tweet, you know, with Grok Images or with Gemini or these other services. You know, you can make some interesting photos for a birthday card or maybe for a presentation. But this is what I find. I don't get exactly what I need. I typically get 60 to 80% of what I need. And so I'm curious, twofold, when do I get to 100% of what I need?

SPEAKER_08: And why does the world need a standalone company like yours? And I think these two questions are related.

SPEAKER_10: Yeah, it's a good question. Well, I think if you want control. So we started as 2019, it was not the world of GNI yet.

SPEAKER_12: And what we brought to the table is getting control, exactly what you said. And so we started actually for GNI. So you remove the background of product photos, your product photos. You can sell on eBay, Shopify, everywhere. And this is like actually the first step. Like you get 100% control of cutting out the background. And so this is what we bring to the table. A lot of the generative AI space is about creativity. You know, it's like create these dreamy photos. And we really focus to help like create photo that sell. So we bring trust, trust with your product. We don't change anything in the product you're taking in photo.

SPEAKER_13: And we also bring trust to the brand. So you know, like you can put your exact color, your exact logo and have the power of GNI. So that's why people love photo room so much.

SPEAKER_12: Like you get the benefit of GNI, but also the control of the traditional AI image editor.

SPEAKER_15: And this is super important for professionals.

SPEAKER_18: You know, if we're screwing around and we want to, you know, send stuff to our group chat and make people laugh, it doesn't need to be perfect. But if you're working for a very, you know, if you're working for Coca-Cola, like this logo, whether it's in Mexico City or it's in the Philippines, it's got to be perfect everywhere around the world. So I suspect you probably have global companies that have global design standards and then local design standards under those. Yes.

SPEAKER_22: Yeah, exactly. So we started from a mobile app, but we expanded and we serve some of the biggest e-commerce in the world.

SPEAKER_12: DoorDash is using us. Amazon is using us because the control we give, like you really have exactly your logo, exactly your colors. It's not only the logo of Coca-Cola. It's exactly you need the red of Coca-Cola. You need all these controls to appear for your brand.

SPEAKER_06: So it's really disaproachable.

SPEAKER_25: So yeah, and these businesses, even DoorDash is becoming international. People don't know that, but they're going global now. And they're buying some companies everywhere. And this is super important. If you're Uber Eats or you're DoorDash, you want to have some common experiences and you want to enable your partners to make consistent images that don't break the design and build trust. And when you have broken design, it lowers trust in products. It's a super important thing for founders to understand. So maybe you could show us the product and then talk to us about, you know, how you go to market with a product like this and find your customers. So it's sort of two questions, maybe give us the demo. And then when you're ready, explain to us how you got those first couple of dozen customers and then how you scaled it.

SPEAKER_30: To add actually on top of the DoorDash analogy, what's key for them.

SPEAKER_12: And there were a few scandals like a problem with that is that you don't like, let's take a photo of a salad. You don't want peanuts to be added to a salad with generative AI hallucinations.

SPEAKER_13: You don't want to have a lawsuit because of that. And that's why our approach is quite powerful for them and very important.

SPEAKER_06: So, yeah, here's a little demo in the Photorum website. We also have a Photorum, well, we started with the app too, so we really have everything you want here.

SPEAKER_12: And I drag and drop a pair of red sneakers in Photorum. So as you see, we're the best at removing background from that. You can create, well, we would suggest like to make it accessible. What we really do is make it easy to create anything from that. We want to build trust because our audience is the non-designers. If you're selling some sneakers, if you're a restaurant, you don't have all the skills. You don't have 10,000 hours on Photoshop, so it needs to be easy. And so I can create, I can use this AI background that is totally generated. And here you can see my sneakers, they're all the initial pixels. But at the background, it's all AI generated, but it's really, it really shades light on your product. And if you look back, you can even add like a, like a virtual try-on. So here I can use my pair of sneakers and put them together with a model that I can choose.

SPEAKER_35: Wow. Can remove the background from that again.

SPEAKER_25: Yes, by the way, for people who are watching, the fidelity on this is just extraordinary. These Nike high tops, I guess they're Air Jordans, I'm taking a guess. Yeah. I'm not sure which model.

SPEAKER_18: But, you know, when you attach them to a model here or put them on a background,

SPEAKER_37: they look like indistinguishable from an actual photo shoot.

SPEAKER_12: Exactly. And, you know, like for a small business, like a photo shoot is like 10K, like a cheap photo shoot is like 5, 10K a day. Like you need a display for people like that. You know, I was able to create a prompt and something that looks good for me in a matter of seconds. Like these Jordans look amazing now with my model. And I can reuse the same model for multiple product I'm selling. One of the features that works super well with our, like with bigger brands is the idea of creating, you know, a batch. So you have consistency of your brand with multiple photos. So if I take a batch of like, we're talking about DoorDash. If I'm a restaurant, I take a batch of dishes with like different, you know, different aspect ratio, different positioning and everything. I can center everything and make it like super professional in a minute. You know, when you're a chef, you don't want to spend your minutes like taking photos. You'd rather be cooking.

SPEAKER_40: It's a seemingly trivial example, but we have all had this issue where you want to normalize

SPEAKER_25: a group of photos. The photographers, you know, might've taken them from different angles, et cetera. And you want all the salads to have, you know, the same size and the same distance around them, the same cropping, et cetera. And wow, that's just done perfectly instantly. And if you think, if you're scrolling around a modern app, like a DoorDash or an Uber Eats, you wonder how they make it look so good. It's these kinds of tools. So is this tool going to be built into the, and are you going to like sort of API it into the DoorDash app

Chamath Palihapitiya: or does DoorDash just do this themselves for the restaurants? How, how do you see that going down?

SPEAKER_02: Yeah, you know, it's, so we partner with some of the biggest marketplaces and it depends on the approach. Uh, some will put that in their backend and they already have a photo workflow that is working.

SPEAKER_12: Some like Deep Ops, it's part of Etsy. They put that in the user interface. If you want to resell and sell some of, uh, fashion items, you just, uh, you're just flipping. Then you just go in the app and you can find some of the photo technology in there. Uh, so it depends on the approach and how much you want to have control still on, on the images,

SPEAKER_46: but both flows are possible and for the small businesses that use the app.

SPEAKER_18: All right. So this tool can be used by a large number of different people, but you have a business to run. What was the go-to market strategy here? I'm curious how you got started and then getting to 50 million in annualized revenue is a big number. It's not easy getting to a couple of million in the AI space. I don't want to say it's easy, but it's obtainable. But the jump between, in my experience, people who can get to one to 5 million, who can then get to 20 or 50.

SPEAKER_25: These are different types of jumps. So walk us through as a founder, how you got there.

SPEAKER_22: Yeah, so, I mean, it was quite fast, but it wasn't, like, instant.

SPEAKER_12: So we started mid-2019 and really, like, what we did a lot in the early days, and I think that was quite important, is we would, well, build and talk to users. So we had an office, we would, like, build the day and then go down to the McDonald's that was downstairs and talk to our users. We would go in the line, ask people if they were okay to, like, let us pay for their meal and in exchange for answering and testing this little app and telling us how they use photo apps. Now, that's brave. Really, we did that for weeks.

SPEAKER_18: Yeah.

David Friedberg: Well, this technique is the listening lab technique, I think some people call it. Is that where you found out about it? How did you become aware of it?

SPEAKER_12: It was from Zenly app, like, the co-founders that we knew that told us, but they probably learned, and there is, like, a mom test book that is amazing for, like, how to ask questions, actually, for listeners.

SPEAKER_18: Yeah, it's super important that you don't lead the witness, as it were. You have to ask a generic question, like, hey, your friend, I think the best one I saw was from Creative Good, an agency in New York, where they just said, hey, your friend sent you this app, and they said, try it out, it's cool. What do you do next? Yeah.

SPEAKER_62: And then you watch them, they say, okay, what do you want me to do? And they're like, you're supposed to just not speak and say, your friend sent you the app. Seems easy. It's difficult.

SPEAKER_66: It's difficult to not say, and then they do, like, two steps, and you're like, and they're like, I don't know what to do next.

SPEAKER_18: It says, submit, where it says, process image, and you're just like, want to just either absolutely punch this person in the face, or you want to punch your designer in the face, because it's so frustrating.

SPEAKER_68: Yeah, exactly.

SPEAKER_66: Generate result. What else can we put on this button?

SPEAKER_12: No, I mean, it's exactly that. Like, you go, you build this amazing feature, and users would never get to the feature that is down the floor. They would always, like, stop before. And so you always discover something, but it is so frustrating. And you really want to grab the phone from the hands and, like, push this button, please, you'll get there. And that's absolutely not what you want to do. And it's very, you're ashamed of your product if you're doing that well. Like, really, I was ashamed of the result with my co-founder, Elliot. Like, we were, but that's the only way. And that's, that's how we got the best feedback. Actually, we did it so much that I was banned from the, this McDonald's, the security guy.

SPEAKER_70: Like, they don't want me, they don't want to see me anymore. So.

SPEAKER_25: Yeah, that would be in France. Like, you accosting the people and telling them your pay for the meal is a little bit weird. Do it, do it at Starbucks.

SPEAKER_74: Yeah, I don't think they even have Starbucks in Paris.

SPEAKER_12: Yeah, they do. We, we did try. I mean, we, we did Starbucks, but it's not exactly the same audience. So, and people are.

SPEAKER_76: How do the French look at Starbucks now? Have they given into it?

SPEAKER_60: Yeah. Yeah. It's quite successful. I mean, Paris is also a lot of tourists, but yeah, Starbucks is quite successful.

SPEAKER_78: I think that was like the last city they think they could ever land in. No, we did not.

Chamath Palihapitiya: North Korea and Paris were the two. Yeah. So let's talk a little bit about how you got into the bigger companies. And then this customization, because how do you charge for products in the AI?

SPEAKER_25: You know, era of AI, because people don't have a lot of seats. Yeah. So do you do it on consumption based pricing? So it was really two questions there. How do you get into those big customers and then pricing?

SPEAKER_82: Yeah, of course. So, well, it grew up quite well.

SPEAKER_41: Like we started to have market fit with eBay sellers. Gary V talked about us in 2020, and we grew to like the 10 million in revenue.

SPEAKER_84: And then did you reach out to him or did he just stumble upon it?

SPEAKER_41: I need to refine the tweet, but I asked him like, do you please retweet for an entrepreneur? And he was like really kind. I got like, that was my first 100K views.

SPEAKER_45: You asked Gary V for a retweet and he did it.

SPEAKER_86: Yeah.

SPEAKER_45: Look at you.

SPEAKER_18: So bold. Wow. And shout out to my friend and friends with Gary V for 20 years. And that's, that is pure Gary V there.

SPEAKER_25: It's just like, he appreciates the hustle. Very nicely done. Yeah. So you get this, you get the sellers. And at what point does eBay and the marketplace find out about you? Or do you just tell them?

SPEAKER_91: It's twofold.

SPEAKER_12: So first, like we, I remember out of Akaton, we built an API because people were asking. And we put it on the side, but we did not have them like team to focus on it. And one day there's someone in customer support that tells us like, please, could I use your API? And are you sure you can handle the load? And well, I think we can do. And, and they did like for two weeks, no one's talking and no, they, we don't hear from them anymore. And one day, boom, like we get like millions of requests on one day. And it was like the Barbie movie that was using our API promoted movie. And they were like 20 million requests in a few, like in a few weeks, we had Beyonce, the Kardashian were using our product or technology inside, like make a Barbie poster. And that was the beginning of our second revenue line, which was the API.

SPEAKER_94: Hmm.

SPEAKER_12: And then the API was like, well, mix of like credibility with the Barbie, the logo. And at the same time, like the best, like, you know, Dbop, DoorLash, they're seeing their, they were seeing the app and they say, can you do that at scale? Like, that's exactly what I need. I just need it at scale. And so we started working with some of the, all the adopters of AI. And this led to, well, getting some of the like smaller, like international part of DoorLash using us. And they had like the best photo of the company. So then DoorLash is asking, how do you make these photos to this subsidiary? And, and they say like photo room. So it's really like product that grow at scale. And same with Dbop. Dbop was kind of using, you know, the sellers, they knew they were using photo room. So if my best sellers, if my best restaurants, if my best like, you know, resellers, real estate owners, they're using a tech, then why not using them?

SPEAKER_95: It seems to be working. And so that's really like pure product like growth for all these marketplaces. Amazing.

SPEAKER_25: Let's talk about how you're running the company. How many team members now? And are you experiencing the phenomenon of your team members as the founder, the ones who do embrace AI? And I suspect if you're an AI company, the team members embrace it in running the company.

Chamath Palihapitiya: How much more efficient is each team member becoming every quarter, every year in your estimation, given all the other tools out there that help people run companies?

SPEAKER_02: I think we're doing things that we couldn't do. So I would say in double digit percentage every year. I think it accelerated more.

SPEAKER_13: Most recently, of course, we use our own technology for image editing, but we also use like, you know, audio. We use 11 labs, we use lovable, like we build like special apps on our website to that.

SPEAKER_12: So we got, we got to, I mean, the way you do growth is totally different from two years ago, we're building apps all the time. Like, you know, as TikTok was like, everyone's making video, now it's everyone is building apps. And it's easy for non-developers to build that. And the developer, they use like either cursor or cloud code, same, double digit, more efficient. Yeah. We really try to lead by example, like, you know, that's the age. Like if you're an AI company, your biggest asset is speed. You're faster because you use good tools and because your team is relatively small. We're 100. Our edge is to move faster than the incubants. So I'm really like trying to demo, we try to like build in public inside the company to see how we can use, reuse AI. And that kind of pushes everyone, every function. We even have like an internal podcast that is built on AI telling us, well, it's user interview. It's notebook LLM about what we learn from the interviews.

SPEAKER_13: And so the way you teach your users is also about your employees, but also AI.

SPEAKER_18: Yeah, I had the founder of notebook LLM on the, on the podcast. Steven Berlin Johnson. And we are using notebook LLM internally a lot. Cause when we do research for this podcast or we're researching or we're doing a deal, like we're closing a deal at the venture firm. You might put all the documents or on the editorial side, well, a bunch of videos or PDFs, and then you can summarize it, ask your questions or even make a mini podcast out of it.

SPEAKER_08: It's really phenomenal. If you haven't played with notebook LLM, that is a crazy unlock.

SPEAKER_02: Yeah. It's so engaging. Like if you want, I mean, yeah, if you want to teach someone to the end, like say something to the full company or people, they don't.

SPEAKER_12: I mean, you need to repeat all the time. So do your all ends, you do your podcast, you do your slack, but that's like a phenomenal. And if you do like tens of podcast, tons of user interview, well, we do a notebook LLM to like share the result. At the same time, we have agents that would like find the five seconds of snippet of this video that you want to really have the exact word as the PM, for instance.

SPEAKER_25: That is genius. So somehow somebody just uploads to notebook LLM, all of those interviews, and then you can summarize them, ask questions of them or even make a podcast out of them. That is so genius. Now, talk to me about the models. Obviously, you're not building a foundational model. You're leveraging other people's models. How is that going? Open source, closed source, just the velocity at which these models are being released is crazy. It's crazy. It's crazy. And they're getting really good. Although there is a theory that maybe, you know, it's slowing down a little bit or maybe parity where they all seem to beat each other by 5%.

SPEAKER_12: What are your thoughts on those issues? Yeah. So actually, we did train like a foundation model for imagery, but we specialize, we train one that is specialized for all features that was creating the background or philosophy. And I think, well, if like for any founder, what I would say is, well, first, you need to be good at evaluating models, like because there's so much of the shelf for open source, like try to learn and eval, like what model is the best for your use case. And we really try, like, we really take what's off the shelf most of the time when we want to build a new feature. And our goal is really to push it like so much that then we reach kind of a limit for our audience, which is commerce. And what do we do then that is better for them? So background removal, well, initially, we took open source, and then we train our model. Now we have the best model in the world for the segmentation, which is a key feature for us. So it's core, so we would train it internally. Now, you know, the text to image model, like just for anything, that is not core to us, or the idea of generating a video or any LLM you use in the app. Here, we would try to evaluate what's the best for our user, and really compare it and to the point where we kind of feel, okay, this model is generalist is never going to be good enough for us, because too smart, so it takes time all the time to think, we need to train our specialized model on top of that. Well, just at this moment, we try training internally. So we do a mix because our goal is really to get the best. We're not player company, like we give the best to our users. So whatever is better at one point, we give it to our users can be internally trained can be someone else.

SPEAKER_25: How do you red team these and sort of build trust? You know, these things can make mistakes, we saw, you know, all kinds of weird behaviors recently, Mecca, Hitler, whatever it was some crazy. You know, thing that happened at a rock where, you know, people were tricking it or something. Yes. So you can have weird things happen, the red teams are in place for a reason. So and you have a higher duty, which is, hey, you know, DoorDash or whoever, you know, eBay, they need it to be perfect, you know, hallucinations or mistakes or, you know, just a brand safety issue. So have you had brand safety issues? How do you think about them? How do you avoid them? Or is this kind of going away now?

SPEAKER_12: I mean, not as big of an issue? No, it's still a problem. You still have like in people or people when you have 300 million downloads, like people will generate plenty of things, it's as wide as the internet. So what we do? Well, first, we're lucky in the sense that we keep the subject. So most of the use cases are like this. So it's the background. It's not as big, like as like a full like text to image, like a wide usage show. The usage is a bit limited in this case. The other like we like we have like some safe safety checks in generation at all level at the image level at the prompt level. And what we do, I think for the big brands, and that's one of our value is we have the B2C side of the we have the app. So we have like, you know, 30 million.

SPEAKER_18: Oh, it's another data stream that you could watch to know people's behavior. Cause you could do something completely innocuous, like put a bride and groom in the background, you know, having their, you know, you may kiss the bride moment at their wedding, totally charming. And it's for, you know, somebody who's in the audience in the foreground or something. Or it could be, Hey, let's have these two celebrities kiss each other. And now you got a lawsuit on your hands because you decided to be funny to do something like that. And it's, it is interesting to see young founders and people. I just had somebody on the podcast who made a deep fake of me in their advertisement for their company. And I said, yeah, don't do that.

SPEAKER_66: Don't do that confusing people. It's too good. So I asked them to remove me and then they put in a, a Muppet version of me and then put not Jason Calacanis on it.

SPEAKER_25: And I was like, so what did you do? I had them on the pod just to goof about it and talk about it. And I said, you know, there's a thing called the right to privacy in America. Yeah. And it's even stronger in France, by the way, in, in the EU, but celebrities have the right to their likeness. You can't use celebrities in any kind of advertisement without explicit permission. And you can't use a celebrity voice even like an act, a voice actor doing, you know, I don't know, Robert De Niro's voice. You're not allowed to do that. So do you have people trying to do those? And have you run into that problem yet of just people don't understand how advertising is supposed to work and do you protect against that?

SPEAKER_12: Weirdly enough, we didn't have too many problems. Like we, we, we try to respect like, you know, as much as possible. I think being focused, like really focusing on commerce kind of give us some leeway here. Like everyone is going to go like, we were starting to experiment with video. I know it's going to be a bit trickier here. Sure. Being able to A-B test here is, is key. And then you really need to be able to like filter at the prompt and the image level what you can do. Yeah, it is definitely a challenge. Uh, uh, it is moving super fast. Uh, so we, we try to do, I mean, our philosophy is to try to do best and really every time like someone, uh, like is not, is bypassing like really filter for that.

SPEAKER_128: Yeah. Correct. Anything like really have these signals where you can.

Chamath Palihapitiya: Yeah. You're the tool. So I don't think people expect the tool to have the responsibility for the output, but you know, you should have some level of awareness.

SPEAKER_25: I saw a chat GPT now, if you try to get it to make the star Wars characters or any of the Disney characters, cause I think they've had some legal issues with companies like that. It just won't do it anymore. So you can't go there and say, make me into a Jedi Knight. It just won't work. Uh, or make me a birthday card with C3PO on it or a Disney princess. They'll just be like, yeah, no, we can't do that.

SPEAKER_13: And we do buy some of like, we do buy content from art, from artists, from photographers, from some of the big. Oh really? So it is like, we're trying to do good on that side.

SPEAKER_135: Oh, so you will use it for your training data or for galleries or something like that. I think this is very wise.

SPEAKER_25: There are all these stock libraries out there. I'm sure that if they could get some reoccurring or, you know, decent usage, they would be delighted to have an extra revenue source from different tools. And then that gives you a differentiator as somebody who's doing it correctly. And I think that's the piece I'm hoping the industry comes to, which is thoughtful people like yourself saying, I'm going to proactively respect content. And how do you look at, I saw this week, it was just in the past week, I guess there was Vogue was, it might've been Vogue or Vanity Fair. They got into a little bit of hot water because they did their first like AI photo shoot. You heard about this? Was it Vogue?

SPEAKER_12: Yeah, I saw that. I mean, we just released like, uh, we were one of the partner for, uh, uh, GPT image, uh, in made. There were like five, 10 partners were the first on the photo side. And one of the features we launched was, well, just to try on. So it's one of the really key features now in photo room. You can, as I showed you, you can like, uh, yeah, try that with your shoes, but also a t-shirt. And well, I think it's, I mean, it's quite engaging. Uh, so some, like we'll see more and more on that. And like for small businesses, like our idea is that we are leveling the playing field. So if you're a small business, like you can really create your photo shoot, you can create more. I think we'll see like half a billion of entrepreneurs in the future. And this is really a tool for them. Now Vogue is, well, I think creative will create. So Vogue is like, there are plenty of, there are plenty of creative there.

SPEAKER_60: And they want just to try the new tools. Like cinema was a new technology. Like Disney, it was a new technology also. Pixar is the same. Like technology is the best, like creativity space for, for artists.

SPEAKER_25: There was actually a backlash with like some of those tools for making DH celebrities, et cetera.

SPEAKER_18: And you're like, oh my God, would this be fair or not? But you, you know, you, you can't make certain movies without using CGI. It's just not possible really. And this could open up a whole new venue. You could have models who say, I want to make my, uh, catalog of images of me available. And anybody who wants to use it can pay me a hundred dollars flat fee and use it. And that model could get a thousand people a year to pay a hundred bucks for their summer wear beach photo shoot.

SPEAKER_144: You buy the likeness or you rent the likeness of.

SPEAKER_18: You rent the likeness. Yeah. I mean, so why is that unfair? I mean, the only people who would complain about that are the people on the top who have made it already, you know, like when these tools come out. So there could be all kinds of new, all kinds of new revenue streams coming in from this. What about AB testing stuff dynamically?

SPEAKER_08: I know people like dynamic testing. And I wonder if you could do human out of the loop dynamic testing with your tool and have people ask for that.

SPEAKER_12: Yeah, actually. So our, our API is quite powerful for that. Like, you know, just write in description of the image in one line and have like five of them in your website and just maybe test all of this. So yeah, I think we see like the future is that everyone gets like a custom ads. You have infinite ads, infinite CRM imagery. And well, yeah, just in your, I don't know what kind of like a furniture style you like, but I can put the chair you're seeing in the style of like apartments that you like. So you can be more engaged and we can able to test that first based on segments and then really have a unique image for everyone, like white glove marketing for you.

SPEAKER_25: And if you knew I was of a certain age and I had kids and I lived in Austin, Texas, you could show a car that would fit a family of, you know, whatever, driving down the road in Austin, Texas. Exactly. It'd be super compelling to see the car you're thinking about getting or a car you weren't thinking about heading even better with five people in it or six people in it, driving down a road near your home.

SPEAKER_153: And you can see yourself in it, right? It's kind of brave new world.

SPEAKER_128: It's the same way when you like, you know, you write CRM messages, like you, you say, like, I name, hi Jason, like, you've, you've buy this product.

SPEAKER_12: You look at this product in our site. Well, the imagery can be a customized the same way. Like you can really like with cursive, like tag your name there, put the product with the other product that we think people buy together and send that as an image.

SPEAKER_25: That's that sort of things that people are starting to do with what's room with API. Imagine if Zuckerberg said on Instagram, allow me to be put in ads sent to me, like a little checkbox, make my put me in my ads.

SPEAKER_18: And then, you know, you're swiping up and you see yourself in this incredible Tom Ford suit with this incredible watch. And it has links. Here's the suit. Here's the watch. Here's the glasses. Exactly.

SPEAKER_43: I mean, that would be so effective and so engaging. You're putting me in the advertisement.

SPEAKER_12: Yeah. The question now is very interesting is like, do you want to see yourself like scrolling on Instagram for thousands of imagery? Or do you want to like, sometimes you might want to see yourself, you might want to see people that are same, like shame. Some might be aspirational depending on the brand, but give so many opportunities for marketers to like really find the way they want to like show that, you know?

SPEAKER_159: So yeah, and this is definitely is a kind of anybody. Have you ever heard anybody as the first? I just had this idea, though, of put me in my ads. Have you ever heard anybody talk about that in the industry? It must be such an obvious idea.

SPEAKER_24: Has yeah, I think anybody done it?

SPEAKER_12: There is an app that you can put like you can browse the internet with your like, with with your likeness. Yeah, the learning I think product wise is you want to see yourself all the time or do you want depends on the people, but it's starting to appear.

SPEAKER_18: But it's starting to appear. It would be so cool. I mean, can you imagine if you just got rid of the need for a tool to do that? And it just happened on Instagram, you know, you're swiping up and you just see yourself at vacation destinations or driving a certain car. Amazing. Matthew continues success with the company if people want to find out more or try the app where they go.

SPEAKER_41: So we for them.com we're on the App Store Play Store. And for the biggest company, we have the API, Matt. So on Twitter, LinkedIn, Instagram. Amazing. Thank you so much for doing this and sharing so much knowledge with our founders.

SPEAKER_25: All right. Thanks again to Matt for joining us for AI basics. If you want to check out Google's cloud report, future of AI perspectives for startups. All you have to do is go to go dot GLE slash future of AI. You're going to find predictions, real world examples and practical advice like you got today just for founders. And don't forget all episodes, legal, AI, marketing, accounting. It's all there for you waiting this week in startups.com slash basics late night weekends. You want to get sharper. Go to this week in startups.com slash basics. Thanks again. And we'll see you the next time on this week in startups.

SPEAKER_08: We'll see you the next time.