Season 7, Episode 23: Building ad tech for the chatbot era (with Tal Shoham)

AI is changing everything, but it's only as good as the signals behind it. Branch connects customer interactions across paid, organic, offline, email, web, and app touch points, and turns them into the trusted context you need, with links and attribution that capture the full user journey. Learn more at branch.io. And while you're there, check out Branch's AI Search and Discovery report, covering insights from more than 300 enterprise marketing, growth, and digital leaders to understand how the industry is responding to the rise of AI search. That's branch.io. The problem is that the distinction needs to be drawn between the confidence of the economists and the correctness of their analysis. Welcome to the mobile dev memo podcast. I'm your host, Eric Sufert, and I'm joined today by tall Shoham. Tall. Welcome to the podcast. Hey, good to be here. So I was trying to think about how we first met. I actually don't remember. I believe we've known each other for quite some time though. So you were in leadership at Iron Source, and I'll let you give the full intro in a second, but I'm pretty sure we met there, but do you remember that differently? Well, it was probably like a casual connect, 2013. What was it? Super sonic, so a long time ago. That's right. Yeah. Oh, yeah. And they had that in Tel Aviv in 2015. And I think we actually met even before that, an SF. So many years ago. Good, but yes, probably more than a decade here. Well, you're doing something very exciting and new now. So I'm going to let you talk about that. So please introduce yourself to the audience for those who don't know you. All right. Cool. So first of all, Eric, thanks so much for giving me the opportunity to be here. A little bit about myself, Tall, I'm 42. I live in Tel Aviv. I've been in the Ed Tech industry for quite a while as we see. I started a company called Super Sonic, which actually my brother started in 2009, and I joined it in 2012. And then we merged with a company called IronSource, and we were fortunate enough together with IronSource to build one of the largest platforms for monetization for ad monetization for gaming companies. We've built an ed network with various kind of ad units, and we've built a mediation platform. And we're really kind of one of the largest out there. I spent quite a many years there on the business side. I led business development, relationship, everything on the product side. So a lot of different things on the mobile ecosystem. So did B2B, hardcore for gaming for many, many years. And then in 2020, I actually joined a company called Youth Games, the CMO. So got to experience B2C hands on, which you think you know gaming or B2C when you're spending so much time at a company like IronSource and Super Sonic. But then when you actually do it, you find out that you didn't know that much that you thought of. That was awesome. As a CMO, I ran around the $300 million of user acquisition budgets over the course of two years, also that M&A and publishing there. And we took that company public at the Warsaw Stock Exchange for a very billion dollars. That was very cool as well. But after two years, I basically left huge. And for the past four years, what I've been doing is a lot of angel investing. So I've invested in more than 20 different companies at gaming, cloud infrastructure, a lot of different things. I do a lot of advisories and boards. And I co-founded a few different companies without an operation role. Invested a little bit of my money, brought a few angels, VCs, and being kind of very, very involved like a boredom steroids with these companies. But that's all gone because I started an velocity eight months ago. And just what I do now, full time. So I actually had done a really big project with you, drip before you came on. So I kind of forgot, I forgot you were the CMO. But yeah, I said, I had done this kind of, I don't know, there was like a, I visited like three different offices or something. Yeah. Over the course of like two weeks. Yeah, that's right. And then you came on right after that. I forgot about that. But we didn't overlap at all with huge. And you did like a full analysis on the marketing side at you and helped us kind of identify the strength and weaknesses and what she proved and so on. I've actually used a lot of the research you've done. And the insights that you've given us exactly when I took office. Okay. Well, that's cool to know. And so kind of the occasion for having you on is velocity. Maybe it's kind of going to like a little bit more of a deep dive on what you're doing with velocity. Yeah, sure. So maybe I'll start with kind of why kind of I even thought that velocity makes sense. And what was the opportunity they saw in front of me? But basically we at IronSource, like I said before, we at Supersonic and Arison, we've built a monetization layer that helps gaming companies monetize a lot of the non-paying users. And it's a big issue on the gaming side because you have 95% of the users that are non-payers. And you do want to do something with that asset in terms of monetization and an improving LTV, which obviously it brings your cat and kind of marketing and growth capability. So we actually see something very, very similar in the world of AI native apps. So we're looking at AI native apps, whether it's a general AI search app, whether it's a photo generator, a video generator, editor or vertical AI for doctors or for lawyers or agents or embedded agents that are docked kind of on different websites. Everywhere that we see there's an interaction between a person and an LLM. And that company is trying to monetize those users. We see that 5% or 6% of the users will turn into subscribers because the majority of the monetization on AI native apps is done via subscriptions. But still 95% of the users will never pay. And we see that pain and that problem and that gap and they're very similar to what we saw in 2013 on the gaming side. And we thought, hey, this is a big problem for us to tackle. And we can help these kind of publishers, like AI publishers to solve that problem. And the crazy thing that we saw that unlike in gaming where the non-peers are not that of a cost center on the company, there's a little bit of server cost, but not that much. On the AI world, everyone is using AI for free is a massive cost center for the companies for for inference and tokens, right? So the problem is actually much, much, much, much worse than we saw in gaming. So what are the kind of AI developers do? They mainly limitations on the user. So you go to a general AI search app that might look like chat GPT, but it's a little bit different and you get to prompt today or three prompt today or 10 prompt today. So they're actually by design limiting engagement and limiting retention and limiting the opportunities to convert those users into a paying users and to creating a habit for those users using those apps. So the problem is actually cascading into going to deeper down the funnel of the product and so on. We thought, okay, this is something interesting for us to maybe solve. Maybe we can do something here. And that's how velocity was born under the assumption that we can create another monetization layer for these a native apps to deliver ads within the AI experiences natively within those AI experiences. Let's take an example of a chat app, very similar to chat GPT. So we understand the intent, we take the prompt, we take the element response and we understand what's interesting for that user and the context of the conversation. We collect all the signals in that conversation and we serve and add natively within that environment and according to the user's intent, that's the idea. So it's not intrusive. It doesn't harm the experience. We're actually bringing value to the user because we might show something that is actually interesting. So we're bringing value to what he's talking about. We're bringing a ton of advertiser value as well because then advertisers can now target users while these AI interactions. And of course, we're creating another monetization layer for the developer, for the publishers, so they can actually generate some money from these users and not only see them as a cost center on inference and so on. So that's kind of the circle that we're trying to solve. Obviously, chat GPT, OpenAI, are doing it amazingly. They introduced ads a few months ago. They're doing it for their free tier and they added a new tier called GPT Go, which instead of charging 20 bucks, they charge eight bucks, but with ads. Again, they're not, they didn't invent this. There's many companies that do it like Netflix and so on. So that's the idea that we want to introduce. We want to allow these AI apps, developers, software, web, mobile to integrate ads into the experience, maybe introduce new tiers with a lower payment, but with ads. So the users are actually accepting those ads, but they know that they're paying less money or for the free tiers and to help them on their CAC to LTV journey. That is always a challenge that every company in the world has. So that's kind of the vision. Yeah, I remember we spoke about this in January at PGC in London. And I think there's a couple of really interesting threads I want to pull on here. So the first is like, look, I mean, a lot of people, like I wrote an article that was sort of like, you know, very declarative in May of 2025. I said, obviously, open AI is going to monetize Chatship with ads. I mean, that was the title of the article. Obviously, Chatship will monetize with ads. And I think, I mean, I don't want to, I don't want to celebrate too much for that because everyone who worked in gaming knew that. I mean, that was like, it was not a question. It was just, it was an inevitability and it happened, right? But like everyone who worked in gaming knows that eventuality, because while you give away the stuff for free and, you know, there's free is ultimately like the end point of the price point because that's how you get mass consumer adoption. You know, you're never going to reach the potential scale by charging a subscription. You just can't. So, you know, ultimately they have to go to free and that means ultimately they have to embrace ads. And like everyone in gaming knew that that wasn't some deep insight. That was that only kind of maybe it was surprising to people that don't work in consumer, right? But you sort of called out a very specific difference and a very fundamental difference between any company that's running inference and, you know, free to play mobile games or free to, you know, free me on products, which is that, well, the inference costs money. Usually this is just kind of this sort of operational cost for onboarding any, any additional user for a traditional consumer, free me of app. zero. Right? Essentially it's zero marginal cost. That's a whole appeal of the business model. But with with any app or any consumer facing product that's running inference, there is a real cost. Talk to me about that. So talk to me about why advertising is probably even more necessary in this new kind of product paradigm. Yeah. So the issue that we see is that these limitations and this cost structure actually is causing the companies to limit the product in capabilities and features and how much they're actually democratizing their products. Right? So it's actually causing a lot of frustration for these companies because they're building amazing products, amazing technology, they're solving amazing problems. But they're very, very, very limited in how much it could be kind of adopted across the world, especially if you look at kind of the other GOs that they know like tier one where it's even harder for it to get the users to pay obviously. So that's kind of the main issue that we see on top of just creating more revenue. And our thesis is that not only that with these type of tools, you can monetize and create an additional revenue stream and maybe cover inference cost, you can actually expose your product to a much larger variety of audience. And that alone for me makes a lot of sense. And again, if you look at my consumer days, my gaming days, that was the business. Right? We wanted to get as much adoption as possible. And to get many users to talk about it, you increase your organic K factor and you have more opportunities to convert users into payers or you just have more users, yours, your product, which is also amazing. Right? So that's one of the things that we really feel that is really, really, really important in what we're building and solves a big issue, not just the monetization side, but also the productization, the features and the less like limitations these developers can actually impose on the product. So that's something very, very big that we're trying to solve. Again, the monetization side is just as important, right? You get more money, your LTV is better. Obviously, you're going to be able to be much, much more aggressive and more efficient on acquisition and growth, which again, if you look at the AI native world, it's much, much, much behind of how sophisticated the gaming world when it comes to marketing or monetization, right? It's a little bit of a up and coming kind of world and new layer of amazing technology and amazing product, this all amazing issues. But the monetization, ad monetization, marketing aspects are a little bit 2015ish when you look at the mobile ecosystem, which is amazing, amazing because you see that more and more of these companies are getting better and marketing, better monetization, understanding the value of ad monetization, starting to do things that in gaming is like something that everybody does, like segmentation and then I treat the users a little bit differently and different funnels and predicting the LTVs of users and then deciding what price points to push down or should they show ads and so on. So that's what we're trying to, first of all, bring to the table as team that has done it and has many years of experience in it. But also we see the market is evolving there anyway without us or with us. So we want to be there when that happens. Yeah, and there's another piece here, which is there's an additional signal, right? There's the context that can be added to the bundle of signals that you can target against. Maybe I'll just tell you my thought on the signal on intent. So the way that I look at a intent is that you have another piece of the machine learning and algorithm targeting capabilities added to the pie. So we always add behavioral targeting, contextual targeting. Now we also have intent. So when a user now speaks to you, for instance, a general chat about, hey, I want to train to run a marathon, please help me build a training product, right? So now, all of a sudden, we can show that user specific ads that can bring in value like travel, which is a running app or specific supplements or running shoes or running sunglasses, whatever it is that can actually be super, super relevant to that user. But not just like a regular search query, which again, searches probably one of the most amazing kind of things that Google has done with advertising in the world. The cool thing about intent is we can and conversation is that we can actually extract deeper signals, more layers of understanding of the user. It may be like budget, where it's from what he wants to do exactly how he wants to train for how long he wants to train. And then we can target an ad that makes a little bit more sense than a more simple query or or a simple search that's called like that. So the idea is to take all that encounter with our machine learning kind of algorithms and decide based on behavioral contextual, but also intent. And we see the results of intent, you know, already, you see it in CTR, you see it in conversions already, even though we're just getting started, but we already see those early signals of, whoa, this is like 5X, 10X, the better CTRs than what we thought we'll see or what we're hearing from other formats. Mobile game developers no longer need to pay up to 30% in major App Store fees. With XOla Web Shop, you can create a direct storefront, cut fees down to as low as 5% and keep players engaged with bundles, rewards and analytics. Start today at xola.com. That's xsolla.com or use the link in the episode show notes. So essentially like this kind of natural language interface is going to be a consumer expectation for all the products that they engage with. I mean, that's just how they're going to expect to interact with stuff. It makes sense in a lot of use cases. It's more convenient and they'll just get acclimated to it. And so for that reason, there's going to be this whole ecosystem of new products, but also maybe just retrofitted products that include that as an interface. And you're going to have the chat GVTs and I think probably at some point, Claw's of the world that build their own ads infrastructure for serving ads and Google's on that or they've adapted their infrastructure for Google AI mode. But you're going to have many, many, many more of them that just don't want to do that. They don't want to just as most gaming companies didn't build their own ads infrastructure. They used, they used IronSource. Maybe more. We can talk about that too later. Don't go there. Don't go there. Don't go there too soon. But so they'll they'll want to tap into some monetization infrastructure that's provided by somebody else. And so there's kind of just two opportunities here. One is just there's this expansion of engagement surface area or there's going to be probably inventory that either exists now and transfers over to this conversational interface because all these apps are going to adopt that and probably just new net new inventory because there's a lot new apps they could create it to take advantage of this. And so that's just an opportunity. But the other piece here, which is kind of like the AI native aspect to it, is that the placements are probably going to be different. They're going to look different. There's a new signal to capture here. That means that like if you want to do this really efficiently, you sort of need to be native to this space. And that's what you are doing. You're building this sort of like native technology, the native infrastructure to serve those new placements that are informed by this new signal in the most efficient possible way. Let me know if I describe that correctly. Yes, yes, 100%. Exactly like you said. And what this new placements and kind of creatives mean is first of all, we're finding out as we go, which is very, very cool. It feels again like 2013 on the gaming side that you know, we're in a way that wasn't a thing and then we found it like that's a massive massive kind of powerful tool that every gaming company would might want to use. And today, there isn't a single company in the world that doesn't use it right on the gaming side. So that's exactly what we're doing. We're doing something that is a little bit different. It's in chat or in AI, depending what it is, it could be an image generator. So for instance, while you're creating an image or creating a video, there's some sort of, you know, it takes maybe 20 seconds, 30 seconds. So a very cool ad unit that we're showing now is that we show a large image or a large ad instead of showing just a kind of time error or a spinner. And after 20 seconds, when the image is ready or 30 seconds when the image is ready, we shrink the ad that we just took the entire kind of real estate and we show it as a banner below the image that was created as an example. So that's kind of a loading phase ad that we've invented. We can show there an image, we can show their video, we can show their audio, depending on the whatever the AI does, right? That's a cool example. Other cool things that we show is we show mini GPs or mini LLMs inside LLMs. So and then of course, we show video and we show carousel and images and then an animated gifts and then it reached HTML. So everything around the creative side is very, very interesting. And we try to do it in chat or in AI natively. So it feels a part of the experience and not too intrusive and that it makes sense. Of course, the demand there needs to be according to the intent and context of the conversation or the session that the user does. And again, I'm saying a lot about conversation or image, but it can also be vertically eye in the world of doctors or vertically eye in the world of lawyers or vertically eye or whatever it is, right? But the idea is to be in the experience of AI and native as possible. That's the idea. Got it. And so we talked about all this this new stuff that you know presents an opportunity. Talk to me. How would you map what you're building to like, you know, the sort of existing ad tech workflows? Like how would you position, how would you position what you're doing? Is it, you know, closer to an ad network, DSP, something totally new that has no sort of, you know, prototype in the existing sort of ad tech? Where would this fit on the Luma, the Luma escape? Yeah. Okay. All right. Cool. So it's definitely in the heart of it. It's an ad network that AI apps can integrate and monetize, and advertisers can tap in and show their ads through our own algorithms and machine learning systems that decide what add to show to what user. So it's definitely a monetization tool for A and A to apps, and a distribution tool for advertisers in the world of apps, e-commerce, whatever it is, brands, and so on. But it's of course much more than that because we come from an experience of also building platforms and mediation, and so on. And our thesis is that this is going to become massive, and a lot of different companies are starting to adopt that are going to adopt it more. So obviously we're also building a mediation platform, which we come from that world. So we're building basically an NAI native mediation for the players that are going to come into this world. There's already players in this world. We already have competitors, which by the way is great, because if we didn't have competitors, meaning that we're doing something wrong, and we're in the wrong area of interest. So I'm happy that we have competitors, and that's amazing. And competition was actually one of the things that I think made us succeed in the ISORs having. Having Apple in as a competitor is always good, right? As an example. So in this world of AI, we don't have the Apple events or Google's yet. We have other companies that we're competing with. So we're building an end network. We're building a mediation platform. So any developer wants to use multiple end networks and manage them, control them and optimize them all through a single tool from a single technology can do it through our mediation. And we're also building a lot of cool other features like a conversation manager, which is basically an abstraction layer that takes the prompt, strics them down of any PII or sensitive data, and basically passes only signals that are okay to pass to kind of other bitters and other buyers and other networks. So various companies in the world of AI don't have to worry about their prompts or commands or requests from AI, got a roaming around the world freely, which we understand is very, very important. So privacy and the kind of integrity of data and so on is something very important for us as well. So it's more of a platform that contains an end network, a mediation, AI-specific tools like the abstraction layer that I just described, and a lot of other cool things that we're building as well. Got it. I'm talking about how, it's a my like kind of operating theory for a lot of consumers that just gaming is at the bleeding edge, and it creates standards that get adopted like years later by other types of consumer products. Right now, I think that definitely was the case with mobile gaming, right? So like you saw monetization, UA, all of that got established by firms like IronSource, it was really early in the space or AppLuvIn, but that infrastructure needed to exist before you could actually scale premium games, right? So like that category didn't really take off until you had, I mean, it just AppLuvIn, IronSource, the company that Unity acquired that became Unity ads, these were all founded 2011, 2012. I think IronSource was 2011, but it is, so all those, all that infrastructure needed to be in place and then these consumer category of free-to-play mobile games could take off. And then all of the monetization tactics, all of the user acquisition tactics that ultimately became the norm for the entire mobile ecosystem were established by mobile gaming, right? And so, talk to me about how your experience in mobile gaming is informing your approach here, because you're talking about like new category, new sort of like monetization models, new business models when you think about the cost of inference and that having to be accounted for. How is your experience in IronSource and huge? How is that informing how you're approaching this? Okay, cool. So I think it has a lot to do with my conviction of why we as a team even decided to do this, because we feel that a lot of the things that we saw happening in gaming is starting to happen in this ecosystem as well and it has to happen as well, right? Because the theory that the foundation models are only becoming better and better, building software is only becoming easier and even commoditized into the point that everybody can build a platform, everybody can build an app, everybody can build software, everybody can plug in whatever foundation model they want into their app or software, web, mobile, and can have amazing capabilities, right? If that's the thesis, so monetization and distribution will become the most crucial things for everyone. Why? Because marketing, distribution, how do you rise above the noise? When there's a thousand that can do what you do? And monetization is how do you charge money when there's a thousand like you that can charge a friction of what you're charging and maybe do the same thing? If those are the two challenges that we believe in, so we believe that what we've built in IronSource, my experience is CMO at huge. Our experience from coming from the gaming world is super applicable to what we're building here now as well. That's in the core of our thesis and what we see and the value that we feel that hopefully we can bring to this market in terms of giving them these monetization layers. By the way, this monetization layer can be for apps, it can be for software, it can be for a lot of different things in the future that don't even necessarily consider using this monetization layer on top of a SaaS model or a subscription model or token usage model, whatever it is. The same goes for distribution. So that experience coming from building that hands-on, we've built a 0 to 1, 1 to n. We are very fortunate to become one of the largest end networks and mediation platforms in the world. I'm an IronSource IPO and for $10 billion as an amazing company. So that me and CMO I manage hundreds of millions of dollars hands-on. So hopefully we can bring all that into this world and kind of help this market as well in that sense. And I feel that we've already doing it. So a lot of the times when we're speaking to our design partners, we already have more than 12 different design partners, which is amazing and we're very happy about that. But when we're speaking to them, for instance, about monetization and bringing our tactics, our knowledge, our experience from the consumer gaming world to this world, they're super happy about it, they want to learn, they want to implement, they're super keen to experiment different things and try different things. Same goes for marketing. I'll give you an example. On the gaming side, creatives has become a religion. So I have giving companies that we generate the 100 creatives a day. That's the capacity. That's not necessarily a known thing when you look at the AI native kind of world. They do much less and maybe they're less aggressive in trying new creatives and so on. On gaming, it's gaming one-on-one. Everybody does it. Everybody does it. It's like if you don't generate a ton of creatives and then test them out and have predictive models of what will work, what won't, you have no chance. Just like a few examples that we do now on this segment that I think are super valuable. The second thing that is very valuable is our experience when it comes to building SDKs and being in app, whether it's a Web SDK or a mobile SDK. We believe in working direct. I love the work directly with the developers, with the companies, whether it's an advertiser or a publisher, a demand side or a supply side. That's something very, very big that I think. Because we've done it for 70 years, I think we know how to speak the language of developers and the pains and the needs. Hopefully we'll be able to build the right technology for them to use as well in that sense. So yeah, I think just the fact that we've been in this massive shift called mobile, hopefully that would help us in this massive shift called AI. That's how we see it. Yeah, I think there's a couple other relevant factors here, particularly with the timing of this moment. One is Wall Street Journal just reported last week that open AI is considering very aggressive price cuts. Yeah. Because they're basically in a consumer attention war with Anthropic and they need to win it. It's very important to them because they missed the enterprise strategic competition. And I think you're going to see that happen throughout the consumer space. Because AI, I think it's pretty obvious that for a lot of these verticals, it's just like it is in mobile. It's going to be winner-take-all. And you're going to need to have the biggest consumer footprint. And so you're just going to need to fight for that. And the way that you fight for that is you drop prices. And you're probably going to have to take a loss on the inference, which is different than what we saw in gaming as we just talked about. And so, well, you got to monetize somehow. And ads is a really good way to do that. It's probably the best way. And they probably should have done that to begin with. But now is the second best time to start. And the other thing here is that the VC money is just going to run out. I mean, you saw that with gaming. Like, people had to get a lot more disciplined about monetization when, you know, there was a free-to-play moment. And when free-to-play wasn't really seen as this kind of like, exciting, totally new category, it was just, well, it's established. And the VC money dries up when you stop seeing big content exits. And while you got to get more disciplined about monetization, it's going to happen with a lot of these AI apps. I mean, a lot of these companies are reporting basically fictitious AR. And they're going to have to get disciplined about funding, about monetization because that funding is going to run out. And ads is just going to be a really good way to do that. And that's just going to be another motivating factor. So I talked to you about the timing. Are you seeing some of this happening already? So I think it's a great point. Yes, we do see a lot of it happening already, especially on kind of the apps that we work with and the companies that we work with. Are much more focused on monetization, being profitable, managing a healthy business, than probably the rest of the foundation models, which are, first of all, have endless amount of money, as you said. And they're fighting for attention and adoption. So the answer is yes. And I think that's part of the interest that we see from the market in adding ads, as you said. The fact that more and more companies are focused on that and versus market share and market attention, I think is massive. And I think VC's money is in, and investors are looking at that as well. You said it as well. Like on the gaming side, today people look at your game economy and monetization before any. anything. You could be a low-down application, but with amazing KPIs and you'll get funded, that wasn't the case back then, right? I think that happens exactly like you said on the AI world as well. So the answer is yes, and you see that all the time. And I think that's why also a lot of the companies that we speak with are very, very intrigued on what will be the impact on KPIs. We'll be the impact on retention, engagement, the conversion to payers, how much money I can make out of this. Can discover inference costs, like a lot of important questions that we have a lot of answers to already because of the design partners. But we are seeing that more and more companies are intrigued and open to try one of the experiments and they understand that also funny. Like when you look at the gaming world in 2012, 13, 14 people are very skeptical about ads. The word as keen to integrate ads, hey, of course, let's add a word. No, it wasn't the case like today. So that's kind of the notion that I'm getting from this world as well. With the fact that you have other comparison like industries that you can compare to. So people see the value and they're intrigued by the value. So that's kind of how I experience it. Well, the value on the publisher side, but also the value on the demand side, right? I mean, if open AI needs to, you know, race to over up all the attention, what's what's a good way to do that? Well, by ads, right? If I had to promote chat to PT, you get installs, right? And I imagine that they, they, you know, these large, the large companies that want to be the absolute category leaders are probably very intrigued by placing ads in other apps that do feature this kind of like natural language in engagement model. Definitely. And the cool thing that we see as, you know, in gaming, we saw that a gaming advertiser, so gaming demand works really well on gaming supply, gaming publishers, right? And we see something that is very, very similar to that on the AI world. We see that AI demands, so AI advertisers, different tools of AI work really, really well on AI supply in terms of conversions, in terms of the click through rates and so on. So that's something already kind of that we see in the data. And I'm saying that doubling down in terms of getting more and more of these types of advertisers and definitely works really well. So we're bringing a lot of value to this advertisers. And the fact that AI on AI works really well is amazing with intent or without intent. But of course with intent, we can even take it farther. So if you're doing whatever a task related into an image generation, then I can show you something in the world of image generation as a tool, then why not? Right? Or end someone. So of course, we're not only showing AI tools, we're showing other campaigns as well, like e-commerce and fintech and gaming. And there's a lot of different things that we show. But I thought that's a very interesting observation that we saw lately that reminded me again of the gaming world of gaming demand, on gaming supply and how amazing it works. So we see a similar trend. How do you think about measurement? How are you approaching measurement? So for us, measurement is as of now, it's exactly the same as it is in the in-app gaming or in-app other experiences and so on. We're performance marketers by nature. So we look at performance, we work with all the regular attribution kind of methods and companies and report everything on the event side to the advertisers. So for us, it works the same. The interesting thing about measurement in my mind will be what will happen in the future when we'll be able to complete the full funnel of the transaction within the AI experience. Right? I think this will be the most interesting part and we also open AI. Still don't do that on chat GPT, but I think we'll have a more of what we call agent to agent kind of capabilities where you'll use agent A and agent B will serve an ad maybe to that agent without you even being part of that experience and will complete that transaction or with you being part of that experience, clicking on that ad that the agent shows you and completing the full transaction through whatever AI application you're using. I think this will be the future of what we're building and kind of what we're thriving for. This agent agent capabilities that we're already experimenting quite a lot with and I think their measurements, attribution, you know, the full funnel and events will be, I don't want to say more challenging, but different than it is today. Different than it is today. You know those channels your colleagues keep bragging about the ones getting all the credit? Yeah, they might be doing squat. Attribution makes every channel look like a hero, even when it's a zero. Incremental tells you who's actually doing the work. It's like a lie detector for your marketing budget. Start using incremental today. Get your demo at incremental.com. That's INCRMMTAL.com. Mention that you came through the mobile dev memo podcast for a special 15% discount for the first six months. Talk about how the size of the space, how large is this space? Are there some skilled AI supported apps that people might not be aware of or that they'd be surprised by in terms of their scale? Yeah, oh yeah. So I was actually surprised when we did our market research before, you know, going to do our fundraising on the size of the market. So it's actually quite massive. So you have the foundation models. The foundation models are probably around 56% of the AI usage today. And on top of that, you have almost double of what they're doing in terms of daily usage, impressions, and applications. You have a ton of different AI native apps software. You have vertical AI, which is exploding in the world of, you know, you have vertical AI, again, like I said before, open evidence is a good example. It's a vertical AI for physicians and doctors in the US, making around $200 million a year just from ads. As an example, you have vertical AI for lawyers. You have vertical AI for all kinds of different things. And of course, you have everything around the agents, embedded AI, docked agents, and websites, and so on. That's massive. That's massive. And it's only only only growing as like way time goes by. So the opportunities and kind of the market as we map it is really, really big in terms of the size of supply. And the advertisers are super keen to get into that kind of opportunities. So we have a good match of a lot of supply. And a lot of interest from the demand side to kind of be there as well. Do you think like the reality is that the tam is everything because basically ever consumer facing app will adopt some kind of natural language interface? I think definitely. Yes. So look every website, every app, even gaming apps, even like a lot of consumer apps, have added some sort of conversational layer to their kind of platform, or some sort of AI capabilities. It doesn't always have to be a conversation, right? So we do see a lot of even traditional like platforms, websites, applications, adding those capabilities into them. And then we can help them monetize those opportunities as well. So definitely yes. What was it like going to market to raise money with this? I mean, say, you know, like I think you know, if someone just spins out of open AI, they get a term sheet walking down the street. Advertising historically has been less exciting from like a fundraising standpoint. You had a, you know, fantastically successful fundraise. Like what was the experience like the AI sort of updraft collide with the historical fund investor skepticism of ad tech? So for us, I think it was a combination of our passion and experience in ethics. So we've done it. We've built a massive platform. We've built great success at a supersonic audience source later in my partners in Unity. So I think that experience and our understanding of the etich market was key. That's one. The second thing is that we look at what we're doing as almost like an index kind of a bond for AI. And this is how I saw supersonic when we did supersonic. Basically, we said, okay, if gaming is going to be called large and going to become massive supersonic, our source, we're going to grow together with it, right? As an end network is a mediation platform. We're going to have a lot of clients using us, a lot of clients getting money with us, monetizing with us, marketing with us, and so on. And we'll grow with the market at least. And maybe we'll be better. We'll grow faster. And how I see what we're doing now is the exact same thing only for the AI world. Or if indeed AI will become as big as everybody thinks it will and take over every part of our lives and software and applications and being bettered in more and more kind of interfaces, then velocity will grow with it because hopefully we'll be able to monetize with a lot of these opportunities and to market a lot of these opportunities. So I think the combination of our experience, being kind of a an index on AI, kind of growing with AI, and maybe you know, like again, I believe in the thesis that building software has been become a commodity and our investors really feel the same way. And they all feel that if that's the truth, everybody's going to need another monetization layer at some point and maybe even more than just one. So we're going to offer one and hopefully you're going to be adopted by millions and millions of users, developers and so on. So that was, I think kind of the core success reasons for the race, the team AI and this thesis that monetization is going to be need and distribution. Right. And the distribution point is pretty key. I published this like long form podcast series called The Prosper Society and that was the whole that was the whole basis of the series. It's like all the binding constraint moves to distribution because there's going to be this just massive baseline increase in the amount of content available. And so, well, the good news is if you, if you agree with that, you agree with that. I think most people agree with that. Like the good news is advertising systems are really, really efficient at matching interests with the most relevant place to express them. That's probably the most efficient way to discover things is advertising because there's the commercial component of the bid, but there's also just the ability to sort of like measure that intent, right? And so that's good news, right? If you just left it up to like kind of search or whatever, like that wouldn't work as well or like the affiliate model, which you know, Shatchy PT was pursuing in abandoned and favor of advertising, that wouldn't work as well. But ads does a really good job of routing demand. And so, so I've seen a lot of startups that are just saying, well, we're going to do ads for chaplots. And like that's kind of like a bad model. I don't I don't think that's that interesting. Talk to me about the difference between ads in AI output and truly AI enriched advertising because that's what velocity is doing. It's actually capturing the value of the signal to do routing the most efficiently. Talk to me about the difference there. Yeah, sure. So I think AI in the et cetera world has basically three layers that it's impacting and kind of helping, right? One is on creative and messaging. So you can use AI today to create a creative on the fly for Eric. You can have a creative based on your location, based on your language, best in your interest with a message that says even your name or your hobby or whatever it is, and you'll get something very, very custom made for you as a creative until we'll get something completely different. So that's one layer that AI really impacts. But by the way, this is something that everybody could use a bit like not not just AI native like what we're building, but that's one impact of AI. The second thing on AI is just better optimization when you're looking at machine kind of learning models and kind of matching and bidding and overall performance AI is dramatically improving that. And the last kind of I would say layer, which is the most relevant for us, is everything around intent understanding and having the ability to kind of see the intent under the signals have a long form conversation from a user and extract whatever is interesting there in terms of really, really understanding what can be incremental, what can be relevant for that specific user. I think that's that's the big part of what we're trying to build and what is very, very different than others. You can understand goals, context, preference, budget, like a lot of different things that you are unable to get without this, I would take a AI interface. So that's that's the relevant layer for us and that's where we're focused on as well. We're going to do creatives in real time as well where we have better optimization and machine learning algorithm because of AI. But that's something that I think is becoming a commodity for every active company in the world. The third layer hopefully will be something a little bit more unique that we can have as an advantage or as another layer of targeting and understanding and tent better. I think there's something that I'd be curious to hear your thoughts on is what's the sophistication bar for starting an ad tech company now versus like 2013 era because it feels like it's, you know, the ad tech is always used machine learning for optimization. I mean, that's not new certainly, but like it seems like, you know, just just looking at, you know, the kinds of things that Facebook is doing, you need much more capable technical talent to really launch something tractable now than you probably did in 2013. Is that the case? 100 percent. And I think it's actually funny because we spoke about how much AI is actually building software and technology easier. I think when it comes to ad tech, it might even be the opposite because you need to have the right type of people in terms of the tech capabilities, experience, understanding of machine learning algorithm and someone on the machine learning. But also if you look at what we're building, we're going direct. So how do you build the SDK? How do you actually build technology that someone will be willing to integrate your SDK? You know how hard it is. Like nobody wants to use a third party SDK because of what it can potentially do to your application. So whatever it is, it can be web, it can be mobile. In that sense, I think you need to raise even more money than people think today because you need to be able to be able to have that capability of learning with real traffic and maybe even bleeding some money on performance understanding and model optimization and so on. And I think the experience of actually doing that in the past, understanding the machine that you need to bring and using the resources to bring the right talent and to actually going to market aggressively and build kind of then bring supply and bring demand. That's much much much much harder building this kind of two way marketplace as well, right? That's much much harder and you can commoditize that. You need to just go and do the work and it takes time and it takes a lot of heavy lifting and the right team. But that's what we love to do and what we're passionate about and that's kind of our experience. So that's what we did it and that's what we're doing it now. But I do think it's becoming like you have to fight the algorithms of Google, of Facebook, of AppLavin, of Moloco, of LiftOff. These are insanely amazing companies like with super smart people with all the money in the world and all the data in the world. And that's what you need to go up against. Again, it's a different world. We're going into int chat now in the data. AI and so on. But you want to have the capability, the technological capabilities in the end of what these companies are putting the bar at. So that's what you need to build. And then finally, like, talking about how this space is developing. Like, where do you see this space in 12 months? So the thing that I can testifies what's happening now and what we feel will happen in the future. So what we see is that like there's a gazillion more AI products being built every day. So every day that we do our kind of market research and we're on top of all that if you're developers and all the different apps and we speak to them, we're very much in the market doing like hundreds of conversations every week. So we see that there's many, many more apps agents of vertical AI that is being built all the time. And we actually see an explosion of kind of of these AI apps in every category. So that's in terms of supply. In terms of adoption of advertising, I definitely see more and more AI companies adopting advertising. We see it ourselves with our own technology design partners, developers that are telling us I would never ever consider doing ads a year ago. Now let's test that. Let's see how it works. Let's see the impact on KPIs and so on. We feel that advertising is going to become a more and more meaningful part for the demand side. So more and more developed like advertisers are going to want to target and find users within these AI interactions. Of course, chat GPT is doing us a lot of work on it and helping us and a lot of people are already buying a chat GPT. And then when we approach them to buy a nest, they're already know what we're doing and how it looks like and what's the value that we can bring and what's intent and so on. So I think that's something that is going to continue. Maybe another point is that AI native app for months is going to continue to emerge and going to continue to develop and we're going to see a lot more different ad units within those AI experiences that we haven't seen before. Like I said before, like mini chat GPTs or kind of agent to agent and more experiences. And I do think that the performance of the monetization with the right segmentation on monetization is going to help cover inference costs for a lot of these developers. And then they will adopt word war. So that's kind of how I see it again. I can only say from my experience, what I see now, right? So that's kind of what I'm and let's not forget that I'm super biased. And of course, but yeah, that's that's kind of how I see the market. I see it only like it's just the beginning. It's just kind of very it's gaming 2012. And that's how I feel. Paul, this was fantastic. Thank you so much for sharing your insights today. How can people learn more about velocity? They can go to our website velocity.io. They can reach out to us on LinkedIn. They can reach out to me. We're always happy to speak to anyone that is interested in learning about what we're doing, about the technology that we're building, the problems that we're trying to solve. Yeah, reach out. We'll be happy to speak. Cheers. Thank you so much for your time. Thanks so much, Eric.