 Hey, guys, my name is Joe Sheppey. I'm the CEO and co-founder of 12 Trades. And we created the very first psychologically-based player experience platform. So there's a bit of problem in gaming right now. Mobile game companies globally spend $15 billion every single year to acquire players, only to lose 85% of those players within just seven days. On top of that, we have 800,000 games just in the iOS Store alone. This is 70% of Apple's iOS revenue. There's 1,000 new games being made every single day. So how do game companies compete in such a competitive market space like this? What they do is they look at your behavioral data and start to guess. So that would be like me saying, OK, because all of you are watching startups pitch here today, that I know who you are, and I think all of you should have the exact same experience at Slush after this. It's silly, and it doesn't really work. So we're going to dive a little bit deeper into the place where behavior comes from. At 12 Traits, we use neuropsychological-based assessment as an underlying psychological technology. And we're able to measure the things in people that help us predict what users actually care about and what their needs actually are. So imagine logging into one experience where all of your players' data, their psychological data, et cetera, are there in real time. And you can do things like create customized rewards or personalized first-time user experiences. With 12 Traits, managing your players from one place is a reality. So how do we do it? What's under the hood? What we do is we take a questionnaire that's based on neuropsychological assessment. We send that out to players connected to a player ID. This is important because it detaches their real identity from who they are in real life and the game. So that makes this GDPR compliant effectively. From that, we're able to get about 400 psychological data points on every single user, and then we're able to scale that by ingesting behavioral data across the entire audience. So there's this issue like, OK, great. You guys can understand users. What's your bottom line? So we've seen so far, if you remember, 85% of players are leaving within the first seven days. We've seen a 6x increase in retention, a 39% increase in average revenue per pane user. The market size we're in, which is mobile as well as console gaming, is $135 billion market. About $20 billion of that is addressable. And we're at $300,000 annual recurring revenue right now. So are we the people to solve this problem? We think absolutely. We've led UX teams at top game companies in the past. We're clinical psychologists, particle physicists from CERN, quantitative neuroscientists who've won global machine learning competitions. And so why us? Why now? At this moment, there are 2.3 billion people in the world playing mobile games alone. We're raising a $2 million seed round. We're 12 traits, and we're powering the future of player centricity. So are you creating a single profile for a single game, or does my profile get, can I use that across all of the games on my device? Yeah, good question. So as we're operating right now, the ID that you're connected to is based on the game company's ecosystem. So if that ID connects to all the other games in their ecosystem, then they know all the other games that you're playing as well. How does that get incorporated into the player experience? So is this something that's a pop-up that comes up and says, fill this out, and we're going to create a better game for you? Or how do you think about conversion of your questionnaire? Yeah, you nailed it. So that's exactly what happens. And sometimes it's rewarded. We see the same results whether it's rewarded or not. The baseline is we need about 472 responses to scale across a population of about a million. For the machine learning algorithm really to work well, we need about 5,000. But to give you an idea, like one of our clients, it's around 200,000 daily active users. We'll easily get 10,000 valid clean responses within just a day. So that part's easy. Pricing model? Yeah, so right now we look at the UA's expenditure for that game, as well as the grossing and how much money the game is taking in. And based on that, we have a SAS model that we charge. For example, I'll give you 200,000 users. That would be around $80,000 per year. So that's on a recurring license basis. And there's value add built into that. So you actually estimate the degree which you're increasing utilization. Exactly. So think of like app Annie. So you need more psychological traits. You can scale within a game or across the whole studio. Great. All right. Thank you, guys.