S07, E23: Building ad tech for the chatbot era (with Tal Shoham)

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Welcome to the Mobile Dev Memo podcast. I'm your host, Eric Sufort, and I'm joined today by Tall Shoham. Tall, welcome to the podcast.
Hey, hey, good to be here.
So, I was trying to think about how we

first met. I actually don't remember. Uh, 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?
Was probably like a casual connect 2013 while I was at Supersonic, so a long time ago.
That's right. Yeah. Oh, yeah. Yeah. And because they had that in Tel Aviv. Uh
yeah, they had that in Tel Aviv in 2015. And I think we actually met even before that an SF. So many years ago.
Could have been. Yeah. So 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. Tal. I'm 42. I live in Tel Aviv. I've been in the edtech industry for quite a while as as we see. started at a company called Supersonic which actually my brother started in 2009 and I joined him in 2012 on the business side and then we merged with a company called Iron Source and we were fortunate

enough together with Iron Source to build one of the largest platforms for monetization for ad monetization for gaming companies. We've built an ad network uh 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 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 the mobile ecosystem. So did B2B hardcore for gaming for many many years. And then in 20120 I actually joined a company called Huge Games as CMO. So got to experience B2C hands-on which uh you know you think you know gaming or you know B2C when you're spending so much time at a company like Iron Source and Supersonic but then when you actually do it you find out that you didn't know that much that you thought of. That was awesome. uh as a CMO I ran around $300 million of user acquisition budgets over the course of two years. I also led M&A and publishing there and we took that company public at the Warso stock exchange for over a 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 atte 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. Uh invested my a little bit of my money, brought a few angels, VCs and being kind of very very involved like a board on steroids with these companies but that's all gone because I've started velocity eight months ago and this is what I do now uh full-time.
So I actually had done a really big project with huge right before you came on. So I I kind of forgot. I forgot you were the CMO, but yeah. So I had I had done this kind of it 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 I forgot about that, but we didn't like overlap at all with Huge.
Yeah. You did like a full analysis on the the marketing side at Huge and helped us kind of identify the strength and weaknesses and what we should improve and so on. I've actually used a lot of the research you've done and and

the insights that you 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 is velocity. Maybe it's maybe kind of go into 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 that I saw in front of me. But basically, we at Iron Source, like I said before, we at Supersonic and Iron Source, we've built a monetization layer that helps gaming companies monetize a lot of the non-paying users. And it 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 and improving LTV which obviously improves your CAC and kind of marketing and growth capability. So we actually see something very very similar in the world of AI native apps. So when looking at AI native apps, whether it's a general AI search app, whether it's a a photo generator or video generator or

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 companies trying to monetize those users, we see that 5% 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 very 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 maybe we could help these kind of publishers like AI publishers to solve that problem and the crazy thing that we saw that unlike in gaming where uh non-payers 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 do these kind of AI developers do? They mainly put limitations on the user. You go to a general AI search app that might look like chat GPT but it's a little bit different and you get two prompts a day or three prompts a day or 10 prompts a day. 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 kind of 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 [snorts] and that's how velocity was born under the assumption that we can create another monetization layer for these AI 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 LLM response and we understand what's interesting for that user, the context of the conversation. We collect all the signals in that conversation and we serve an ad 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 him something that is actually interesting and according to what he's talking about. We're bringing a ton of advertiser value as well because the advertisers can now target users while these AI interactions and of course we're creating another monetization layer for the developers 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, Chad, GPT, OpenAI are doing it amazingly. They introduced ads a few months ago. They're doing it for the 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 cap to LTV journey that is always a challenge that every company in the world has. So that's that's kind of the vision.
Yeah, I remember we spoke about this in January at PGC in in London and I think there's a there's there's a couple like really interesting threads I want to pull on here. So the first is like look I mean a lot of people like I I wrote an article that was sort of like you know very declarative in May of 2025. I said obviously OpenAI is going to monetize chat GPT with ads. I mean that was the the title of the article. Obviously chat

GPT will monetize with ads. And I think you know 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 an it was an inevitability and and it happened, right? But like everyone who worked in gaming knows that eventuality because well 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 was surprising to people that don't work in consumer, right? But you sort of called out a very specific difference and and a very fundamental difference between any any company that's running inference and you know free to play mobile games or free to you know premium products which is that well the inference costs money. Usually this is just kind of the sort of operational cost for on boarding any any

additional user for a traditional consumer premium app are zero right essentially it's zero marginal cost that's the whole appeal of the business model but with with any app or any consumerf 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 [clears throat] 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 it 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 other geos than you 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 our my consumer days, my 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 you increase your organic K factor and you have more opportunities to convert users into payers or you just have more users using your product which is also amazing right so so that's one of the things that 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 cominging kind of world and and new layer of amazing technology and amazing product that solves 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 we see that more and more of these companies are getting better at marketing, better at monetization, understanding the value of ad monetization, starting to do things that in gaming is is like something that everybody does like segmentation and then and 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 of experience in it. But also we see the market is evolving there anyway [clears throat] 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's can be added to you know the the bundle of signals that you can target against.
Maybe I'll just just tell you kind of my thought on on on the signal on intent right. So the way that I look at a intent is that we have another piece of kind of 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 sticks to for instance a general chat about hey I want to train to run a marathon please help me build a training program. Right? So now all of a sudden we can show that user specific ads that can bring in value like Traa 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 search is probably one of the most amazing kind of things that Google has 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 and maybe like budget where he'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. Let's call it like that. So the idea is to take all that in account 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 and you see it in CTRs you see it in conversions already even though we're just getting started but we already see those early signals of wa

this is like 5x 10x better CTRs than than what we thought we'll see or what we're hearing from other formats
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as an interface. And you know, you're going to have the chat GBTs and I think probably at some point clouds of the world that you know, build their own ads infrastructure for serving ads and you know, Google's done that or they've they've, you know, 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 like just as you know, just as most gaming companies didn't build their own ads infrastructure. They they use, you know, well, they used iron source. [laughter] Not anymore. We can talk about that too later. Don't go there. Don't go there.
Don't go there. too too 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 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 that get created 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 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 if I described that correctly.
Yes. Yes. 100%. Exactly like you said and and what this new placements and kind of creatives mean is first of all we're we're finding out as we go which is very very cool. It's it feels again like 2013 on the gaming side that you know rewarded video wasn't a thing and then we founded hey 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 timer or a spinner and after 20 seconds when the image is ready or 30 seconds where 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 they're 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 GPTs or mini LLMs inside LMS. So, and then of course we show video and we show carousel and images and then and animated GIFs and then rich 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 or the session that the user does. And again, I'm saying a lot about conversation or image, but it can also be vertical AI in the world of doctors or vertical AI in the world of lawyers or vertical AI or whatever it is, right? But the [clears throat] idea is to be in the experience of the 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 about how would you map what you're building to like you know the 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 that has no sort of you know prototype in the existing sort of adtech how where would this fit on the luma the lumaccape
yeah okay all right cool so it's it's definitely in the heart of it it's an ed

network that AI apps can integrate and monetize and advertisers can tap in and show their ads through our own kind of algorithms and machine learning systems that decide what ad to show to the to what user right so it's definitely a monetization tool for a native 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 mediations and so on and our thesis is that this is going to become massive and a lot of different companies are starting to adopt it 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 was actually one of the things that I think made us succeed in desires having having app as a competitor is always good right as an example. So in this world of AI we don't have the app loans or Google's yet we have other companies that we're competing with. So, we're building an ed network. We're building a mediation platform. So, any developer who wants to use multiple ed networks and kind of manage them, control them, and optimize them all through a single tool from 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 strict down of any PII or sensitive data and basically passes only signals that are okay to pass to kind of other biders 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 kind of roaming around the world freely which we understand is very very

important. So privacy and a 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 ed network 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. And talk to me about how so my like kind of operating theory for a lot of consumers is 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 iron source who was really early in the space or app, 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 apploven, iron source, the company that unity acquired to that became unity as these were all

founded 2011 2012. I think iron source was 2011 but so all those all that infrastructure needed to be in place and then these consumer category of freeto 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 like 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 Iron Source and 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 and 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 could build an app. Everybody could build software. Everybody could 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 of what 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 at our source. My experience as CMO 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 kind of our 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 could be for software, it could be for a lot of different things in the future that don't even necessarily consider using this kind of monetization layer on top of a SAS model or or subscription model or token usage model, whatever it is. The same goes for distribution. So that experience coming from building that hands-on, you know, we we've built it 0 to1, one to end, we were we were very fortunate to become one of the largest ed networks and mediation platforms in the world. I I source IPOed for $10 billion as an amazing company. So me as CMO, I managed hundreds of millions of dollars hands-on. So hopefully we could bring all that into this world and kind of help this market as well in that sense. And and I feel that we we 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 you know 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're they want to learn. They they want to implement. They're super keen to experiment different things and try different things. Same goes for marketing you know like on the I'll give you an example on the gaming side creatives has become a religion right so like I have gaming companies that we generate 100 creatives a day like that's the capacity that's not necessarily a known thing when you look at the AI native kind of world like they they do much less and maybe they're less aggressive and trying new creatives and so on on gaming it's gaming 101 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 know, you have no chance. Just like a few examples that we do now on this kind of segment that I think are super valuable. The second thing that is very valuable is our experience when it comes to building SDKs and kind of being inapp whether it's a web SDK or mobile SDK. We believe in working direct. I like I love to work

directly with the developers with the companies whether it's an advertiser or a publisher demand side or supply side. So that's something very very big that I think because we've done it for so many years I think we know how to speak the language of developers and the pains and the needs and hopefully we'll be able to build the right technology for them to use as well in that sense. So yeah and I think just the fact that we've been in this massive shift called mobile hopefully that will help us hit this massive shift called AI that's how we see it. Yeah, I think there's a couple other relevant factors here, particularly with this with the timing, right, of this of this moment, right, which is one is, you know, Wall Street Journal just reported last week that OpenAI is considering like very aggressive price cuts.
Yeah.
Because they're they're basically in a in a you know, consumer attention war with Anthropic and they need to win it. It's really important to them because they missed the the enterprise strategic competition. And I think you're going to see that

happen throughout the consumer space, right? Because a, you know, I think it's pretty obvious that like for a lot of these verticals, it's, you know, 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 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 you know, 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 freeto-play moment and when freeto play wasn't really seen as this kind of like exciting totally new category and it was just well, it's established and the VC money dries up when you stop seeing big content exits and well, you got to get more disciplined about monetization and that's going to happen with a lot of these AI apps. I mean, a lot of these companies are reporting basically

fictitious ARR and they're going to have to get disciplined about funding about monetization because the 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. How so? Talk to me about the timing. Do you 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, you know, first of all, they have endless amount of money as you said and they're they're fighting for attention and adoption. So, 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 VCs monies and like investors are looking at that as well like you said it as well like on the gaming side today people look at your game economy and

monetization before anything you could be a low DO 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 we 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, what will be the impact on retention, engagement, the conversion to payers, how much money I can make out of this, can this cover inference cost 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 want to do experiments and they understand that also funny like right when you look at the gaming world in 2012 134 people were very skeptical about ads they weren't as keen to integrate ads hey of course let's add reward 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, 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 OpenAI needs to, you know, race to hoover up all the attention, what's what's a good way to do that? Buy ads,
right? Buy ads to promote Chat GPT, get installs, right? And I imagine that they they are, 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 engagement model.
Definitely. And the cool thing that we see is, you know, in gaming, we saw that 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 of the AI world. We see that AI demand, so AI advertisers, different tools of AI work really, really well on

AI supply in terms of conversions, in terms of clickthrough rates and so on. So that's something already kind of that we see in the data. I would say that doubling down in terms of getting more and more of these type of advertisers and definitely it works really well. So we're bringing a lot of value to these 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 further. So if you're doing whatever a task related into an image generation and I can show you something in the world of image generation as a tool then why not right or and so on. So, of course, we're not only showing AI tools, we're showing other campaigns as well, like e-commerce and fintech and 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 gaming supply and how amazing it works. So, we see a similar trend,
right? How do you think about measurement? How how are you approaching measurement? So for us measurement is as

of now it's exactly the same as it is in inapp gaming or inapp other experiences and so on. We're performance marketeteers by nature. So we look at performance we work with all the regular attribution kind of methods and companies with and we 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 this will be the most interesting part and we also open AI still do that on chat GPT but I think we'll have a more of a 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 to agent capabilities that we're already experimenting quite a lot with and I think there measurements attribution you know the 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.
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Talk to me about how the size of this space. How how large is this space? And are there some scaled AI supported apps that people might not be aware of or that that they'd be surprised by in terms of their scale.
Oh yeah. Oh yeah. So, 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, so it's actually quite massive. So, you have the foundation models. The foundation models are probably around 50 60% of the AI usage today. And on top of that, you have almost double of what they're doing in terms of um 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 as 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 kind of different things. And of course you have everything around the agents embedded AI adopted agents in websites and so on.

That's massive. That's massive. And and it's only and only only growing as like late 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 every consumerf 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. Doesn't always have to be a conversation, right? So we do see a lot of even traditional like plat platforms, websites, applications adding those capabilities into them and then we

can help them monetize those opportunities as well. So definitely yes.
What what was it like going to market to raise money with this? I mean so you know like I I think you know if someone just spins out of open AI they they get a term sheet walking down the street. Advertising historically has been less exciting from like a fundraising standpoint. and you had a you know fantastically successful fund raise like what what was the experience like? Did the AI sort of updraft collide with the historical fund investor skepticism of of adtech?
So so for us I think it was a combination of our passion and experience in ETIC. So we've done it we've built massive platforms we we've built great success at a supersonic iron source later my partners at unity. So I think that experience and our understanding of the ad techch 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 become large and going to become massive supersonic iron source we're going to grow together with it right as an ad network as a mediation platform. We're going to have a lot of clients using us, a lot of clients spending 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, right? 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 be embedded 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 the the like again I believe in the thesis that building software has been become a commodity and 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 right so we're going to offer one and hopefully going to be adopted by millions and millions of of users, developers and so on. So that was I think kind of the core success reasons for for the raise the team AI and this thesis that monetization is going to be in need and distribution,
right? And and the distribution point is is pretty key. I I so I I published this like long form podcast series called the prosperous 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 and 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 is advertising because there's the commercial component of the bid, but there's also just the ability to sort of like measure that that intent, right? And so that's good news, right? If if you just left it up to like kind of search or whatever, like that wouldn't work as well or or like the affiliate model, which you know GPT was pursuing and abandoned in favor of advertising, that wouldn't work as well. But ads does a really good job of routing demand. And so so so I've seen a lot of startups that are just saying, "Well, we're going to do ads for chat bots." And like that's kind of like a 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 it's actually capturing the value of the signal to do rooting the most efficiently. Talk to me about the difference there.
Yeah, sure.
So So I think AI in the tech 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 a creative on the fly for Eric. You can have um a creative based on your location, based on your language, based on your interest with a message that says even your name or or your hobby or whatever it is and you'll get something very very customly made for you as a creative and tall will 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 on improving that. And the last kind of I would say [clears throat] layer which is the most relevant for us is everything around intent understanding and having the ability to kind of see the intent, understand 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 could 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 say kind of AI interface. So that's that's the relevant layer for us and that's where we're focusing on as well. We're going to do creatives in real time as well where we have better optimization in machine learning algorithms because of AI. But that's something that I think is becoming a commodity for every asset 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 intent better. Actually, I think just something that 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 like adtech has always used machine learning for optimization. I mean that 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 you need much more capable technical talent to really launch something tractable now than you probably did in 2013. Is that the case?
100%. And and I think it's actually funny because we we spoke about how much AI is actually building software and technology easier. I think when it comes to adtech 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 a machine learning algorithm 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 could be web it could 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 go into market aggressively and build kind of and bring supply and bring demand. That's much much much much much harder and building this kind of two-way marketplace as well, right? That's much much harder and you can't 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 that's what we love to do and what we're passionate about and that's kind of our experience. So that's why we did it and that's why we're doing it now. But I do think it's becoming like you have to fight the algorithms of Google, of Facebook, of Applo, 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. And again, it's a different world. We're going into inat native AI and so on. But you want to have the capability, the technological capabilities in the end of what these companies are are putting the bar at. So that's what you need to build.
Got it. And then and finally like talk to me about how this space is developing like where do you see the space in 12 months.
So the the the thing that I can testify is 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 the different 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, vertical AI that is being built all the time and we actually see an explosion of kind of 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 even consider doing ads a year ago. Now, let's test it. 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, Chad GPT is doing us a lot of work on it and helping us and a lot of people are already buying at Chad GPT and then when we approach them to buy on us, 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 ad formats 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 more and 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, 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 it's gaming 2012, man. That's how I feel.
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.