RoboStrategy, Inc. (BOT) June 10, 2026 Capital Markets Day Transcript

Okay, guys, let's start. I'm calling in here from the NASDAQ office in New York. We're here to do the RoboStrategy Investor Day presentation. I'm Andrew Kang, the CEO of RoboStrategy, and let's get into it. So RoboStrategy is an exciting new venture. It is one of the very first publicly listed venture funds on NASDAQ. Not only that, but it's the first robotics-focused venture fund that is on NASDAQ. We listed around a month ago, but the listing day was really just the starting line for us, not the finish line. And I have a lot of exciting things to talk about today. You know, starting off, which is why should you care about robotics and physical AI, which is the investment focus of the fund? You might have seen, you know, playing with all the new AI tools and chatbots that have come up over the past few years, that the development of AI is really accelerating. It's getting better month by month, year by year. And that has implications not just for the digital world and knowledge, knowledge work, but it has implications for the real world as well through physical AI. Um, and so growing up, we always watched all these sci-fi shows and movies and, you know, in, in them, you saw robots, you had robots that talk like humans. Uh, they could do the job that humans were doing and they can understand the world like we do. And that we always thought was something that was way in the future, 50 years away, 100 years away. But I think with the recent developments in AI and physical AI, that is probably a lot closer than we might think. That is something that is coming over the next few years. And the models for these robots are starting to get really, really great. And it's going to have a lot of implications for not just the robotics industry, but for every industry in the world that requires physical labor. And so there are a lot of really prominent people like Elon Musk, Marc Andreessen. They say we're going to have millions, potentially billions of robots in the world. And I tend to agree with them. This is going to be potentially one of the biggest industries in the world, as big as AI, if not bigger than AI. And in terms of where we are right now, I would say this reminds me a lot about maybe 2022, 2023, if we were to draw a parallel to the AI world, where we're at that inflection point where things moved for very slow and very slow incremental chunks for a long period of time. And then in a very short period of time, that slope started to change where we were starting to make larger and larger amounts of progress every single month and every single year. And so you can see on the chart here, we look at, this is basically measuring AI capabilities of Quad and ChatGPT, et cetera, on software engineering hacks. And you can see that for a while, we were making some small progress. And then in the span of just two years, the capabilities of these models exploded. And not only did the capabilities of the models explode, but so did the revenue of the companies building the models. And so did the valuations of those companies. And so I think that has not yet happened with the physical AI industry and the robotics industry. It's still relatively small. I would estimate the total market cap of all private robotics companies at somewhere between $100 billion and $200 billion. So we compare that to, say, for example, the total market cap of Pokemon trading cards, which is around $50 billion. It's really quite early. Where do we invest as a fund? Our core focus is on robotics. That includes vertically integrated companies. That includes humanoid companies. That includes companies focused on industrial automation. And it also includes companies within the supply chain. As a fund, we invest multi-stage. So from the seed stage to pre-IPO and potentially public, but the majority of our fund is going to be at the venture in private stage. Where we're most excited about are the robots, the robot companies building in the general purpose field, because that is what is really exciting about robots is that they don't need to perform one specific task really well. We believe there's a big market for companies that are focused on application-specific robots. But if we think about the biggest companies in the world, Apple, NVIDIA, they make general-purpose devices. And those devices, they're really useful for a lot of different things. And because they're useful for a lot of different things, people are going to buy a lot of them. They're useful if the world changes. For example, for GPUs, you can run a lot of different types of models on them. You don't have to just run one model on them. And if we can make a lot of something that is general purpose, then one, that's a big market. You can sell a lot of units. And then two, you can really achieve economies of scale, make these objects and devices more affordable. And when they become more affordable, they're more accessible to more people. And, you know, the company can sell even more of these robots or products. And so how do we think about the size of the robotics market? You know, when we talk about trillions, tens of trillions, it's a little bit difficult to comprehend. It's such a big number. One way we look at it is we say, look, robots, they're eventually going to substitute a lot of physical labor. In the same way, you know, these AI models are starting to substitute a lot of knowledge work. It's just easier to have a robot do something. It can work 24-7, 365. You don't need to worry about the robot taking sick days or for it to get too tired or for it to not like the job and quit. And you don't have to worry about if it quits, you have to hire new people. you have to train new people. Just the overall trends in society where people are less excited to do these tough industrial physical labor jobs and birth rates declining means there's a great opportunity for robots to help fill that gap. But in terms of the actual sizing, we produce billions of cell phones per year. We produce hundreds of millions of cars and PCs. And if we think about something that is, you know, as technologically revolutionary as robotics that can understand the world, then I would assume that we're going to be selling a very similar amount of robots. And, you know, Elon Musk makes the claim that we're going to have tens of billions of robots. And, you know, if you take a rough projection of this, this is what the numbers look like. We're not going to get there immediately. But if we get there, say, between 2035 and 2040, within just a few years, we're going to start reaching the millions of humanoids. And in terms of revenue, right, say, for example, we sell one robot for $50,000, and we start scaling that up to 100,000 robots. At that point, 100,000 robots at $50,000, you're already talking about $5 billion. That is a really substantial amount of money and you will have a very substantial company selling 100,000 robots. But companies like BMW, Volkswagen, they have hundreds of thousands of employees. Walmart, Amazon, they have millions of employees. And so what if we sell a million robots? Well, that gets us to $50 billion. That's still not scratching the surface. The physical labor market is so much larger. And so we scale that by 10 again, you get a 500 billion, 10 again, 5 trillion. And you can see very quickly how revenue could potentially scale to the trillions of dollars, potentially tens of trillions, which would also imply tens of trillions of market cap. And I know this sounds crazy, but imagine, think back to the time when the iPhone came out in 2007. You know, Apple at that time, well, the year before, they were trading at somewhere around $50 billion. Today, they're closer to something like $3 trillion. So that's more than pretty much the combination of all the top market cap companies at that time. And it would have, if you told somebody, hey, look, in the future, Apple is going to be $3 trillion, it might have told you, you were crazy. But we live in a crazy world and we live in a world where we're seeing some really fast exponential growth. And there are some key, what I would consider macro level shifts that are driving the adoption for robots in the future. A big part of it is we're having a labor gap in a lot of countries around the world. Not only are birth rates falling, but populations are aging. People don't want to do these really difficult jobs anymore. And, you know, you talk to people that are trying to fill lines in, you know, California and Japan, it's a lot of times really hard. They can't find enough labor. And a lot of time, if they do, people aren't excited about the job and they leave really and not only that but labor demand is only going to rise as the world continues to grow as ai allows us to build different things we're going to need more of a requirement for labor i think you know a lot of the talk in the world has been recently around the build out of data centers. And it's funny because the bottleneck for those hasn't been the GPUs, although GPUs are a bottleneck. It hasn't been the materials to build the data centers. It has been the electricians and the plumbers and the people that are putting the whole data center together. And so if we think about robots as a way to fill that gap, well, they can do the same work eventually as a human would be able to do, but they'll be able to do it a lot more efficiently. And so we actually did an analysis where we looked at, hey, if we had a $50,000 robot and we had it work for, say, seven years, we took into account the cost of electricity, the cost of maintenance, et cetera, what would that cost per hour look like? And it came out to around $1.9. And so you think about the all-in cost of any human in a physical laborer job today, depending on the geography, including benefits and admin, hiring, et cetera, that comes out to $30 to $50 all in. It's really difficult to compare to something like a robot. And not just in the US, but even in lower wage countries around the world. So why are we doing this? Previously, we were investing out of mechanism capital, investing our own capital, and we were actively investing in the robotics industry. But we saw a major need in the market because previously, companies, the biggest tech companies in the world, they IPO'd at pretty reasonable valuations. NVIDIA went public at less than a billion dollars, Apple, Google, Microsoft, they all went public at, you know, I think below 10 billion or very, very reasonable valuations. Today, you look at OpenAI, Anthropic, SpaceX, some of the, you know, most interesting companies of this generation, they don't go public until they're past that trillion dollar mark, until they're making tens of billions of dollars of revenue. And so all of that value creation that used to happen in the public markets, now that's happening in the private markets. And it's been accumulated by this small group of venture capitalists and their network. So there's a little bit of the concentration of value growth. And it's not like the public market doesn't want access to these companies. The issue is they don't have access because, well, now there's so much capital in the private capital markets where companies don't need to go public. It takes a lot of work to go public. You have a lot of regulation. When you do go public, a lot of reporting requirements, which are sometimes not so easy to deal with. And so if there are more and more funds offering these companies capital in the private markets, they're going to continue to stay private for longer and longer. And so RoboStrategy is one of the solutions for that, where we take our network and our investment experience and our investments, and we have a public vehicle where public market investors can now have access. And so that's different from, say, a generalist VC fund, where maybe they're not focused on robotics. Not everyone has access or the capability or the network to invest in these funds. And they also charge these performance fees as well on top of their fund. Some of the funds, they can do really well. Some of them, not so much. But there's very few, if any, that have a robotics focus. compare this also to the alternative of robotics etfs that are out there most of these concentrate on public equity robotics companies which i would consider there are some interesting out ones out there there's tesla for example tesla's you know one to two trillion dollar company and their optimist program is interesting but they have a lot of other stuff in the business it's not pure play. And what I would say is most of the exciting developments and innovations in the robotic space, they're all happening in the private markets. These are companies that have formed maybe two, three, four, five, 10 years ago, and they will continue to stay private for the foreseeable future. And so there are a couple of reasons why investors would choose RoboStrategy. One, we talked about earlier, the performance fees. Two, public access. And three, liquidity. Unlike traditional venture investments, robo-strategy is publicly traded. There is no need for you to pursue OTC opportunities, secondary opportunities. You can trade this directly on NASDAQ. The other part, and what I would consider the most important part is our institutional due diligence capabilities. Throughout the last one, two years, we've built an incredible team of former robotics operators and founders that can fill a lot of the gaps that a traditional investor might not see. Because as the CEO of RoboStrategy, I've definitely gotten to a decent place with my understanding of the market, but nothing replaces decades of actual work as an operator, right? They understand all the things that you might not even think about to ask. What could be the reasons a company in the space might fail and what are the reasons they might succeed? Is the talent at these companies actually good? Can the CEO, the CFO, the researchers actually execute or do they just have a good pedigree? There are a lot of questions that come up in due diligence that don't exactly have obvious answers. And we spent a considerable amount of time making sure that we're investing in the companies that have the best chance of success. And what we optimize for is the risk reward of that investment. So we believe they have a high chance of succeeding with a low chance of failure and really large upside. And I'm going to pass this over to Kevin, our CMO, who's going to talk a little bit about our marketing.

Yeah, thanks, Andrew. Hey, guys. Yeah, as Andrew said, I'm Kevin. I'm focused on all things marketing and content for RoboStrategy. Before I jump into this slide, I think setting the framing, just zooming out and talking about our thesis is pretty important. And so essentially the thesis for RoboStrategies Marketing is that over the next 12 to 18 months, we think that attention on robotics overall and physical AI will do something along the lines of 15 to 20x what it currently is today. um there are a few reasons for this um one of them being when you see a physical humanoid robot in front of you it's a very visceral reaction right there is like a it's different from software update going out and then you see something and you're like okay you know this is tech but it is abstract um a real robot doing work in front of you is something that really resonates with a lot of people. And we've seen this happening already. Every once in a while, you might see a video pop up on your feed of a robot at the Knicks game doing a dance, for example. Over the next few years, as it goes from a video every once in a while to actually seeing this incredible piece of technology in front of you, we really think it's going to have a large impact on society and will capture a lot of mindshare. I fully expect that robotics will be the focus point of tech. finance and would not be surprised if politics got very interested in what's happening in the field and could honestly see this becoming a national priority. And so we're coming from the backdrop for the marketing is essentially we think there's going to be this enormous inflow of attention. And there is really nobody doing a good job right now in helping to explain what future of robotics may look like to everyday people. That is the opportunity and the gap that we anticipate RoboStrategy can fill, and that is our ambition. In terms of the foundation for how we actually do that, that's where I'll jump into the slide here. So the foundation is very much going to be internet native digital media, right? If you are watching this you probably are watching it on x or on youtube so you know gotcha right this is already something you're doing right now um but yeah you know i don't think i'm telling anybody anything they don't know by saying cnbc's i mean their viewership is down significantly their influence in the market um relative to other options is dropping dramatically um podcasts x and youtube are you know there's there's a lot of bullets that you can read through if you're interested in seeing some of the stats around it. But the main takeaway is this is how people are making financial decisions these days. More and more people are going online to do research. X as a platform is probably the most important, right? That is the arena where people come in to discuss finance, tech. VCs are looking to make investments. Typically, they find out about these things on X. And so having that as the foundation, starting with X and then podcasts and YouTube as those second fronts for us is essentially the strategy and where we're looking to start. So in terms of the, you know, the current assets for the team and our breakdown, our resources, we on purpose did not do any marketing really for the first two weeks of launch around RoboStrategy. It was very much designed, right? I think that it is, you know, We have started to unveil a taste of what we're going to do in the future. But the idea was to have a very subtle stealth launch and then build into our marketing engine from there. Even with that, you're able to garner over a million impressions on RoboStrategy's launch week. In terms of the team and backers, the total follower count for people that are just directly involved with RoboStrategy is 8 million followers, or around 8 million followers. For anybody who is well versed in social media, right, you know that that it's actually not the best proxy for impact. But a very good proxy for impact is, you know, what are the total impressions that you're getting per month, right? And so from the team and the backers, we're seeing an average of 75 million impressions per month, which is over 850 million impressions annually, right? Close to a billion, which is very extreme. If Andrew keeps putting out bangers, you know, you could see even higher numbers there. And I think the really important part to call out is that the people that are involved with Robustrategy, their audience is built around, you know, talking about the future. What does AI actually mean for society? What are the things that people should be looking at and looking to do? And so you can see some examples here, right? There's an article from myself, an article from Andrew, both doing around 3 million views each and just showing like the amount of influence that comes from the reach that we currently have in distribution. So this is essentially the way that we'll bootstrap the initial audience around robust We can jump to the next slide here, Andrew. um cool and then yeah just you know one thing that we have consistently seen uh pre-launch and even post-launch is there's just an overwhelming appetite and demand for people that want to learn more about robotics right they they need a place that they can go and consume educational content they don't know how to get exposure to the industry um and you know to call a spade a spade, it's a very nascent industry in terms of how the attention economy currently sits. You have Elon Musk, who goes on a podcast, call it once every three months, talks about optimists. Brett Adcock is very good at putting out content, but there are not a lot of people that are actually filling that gap. A clear example here, Andrew's been deep in the robotics space for over two years now, essentially just bringing some of his thought leadership and thoughts on what the future of robotics will look like. And Elon Musk essentially coming in saying, yeah, it's super obvious, right? Engaging with Andrew, it shows that the conversation is already flowing to us. And so, yeah, in summary, right, we expect this enormous wave of attention that will come in. We think that the opportunity for us is to be that central hub where people can get informed about robotics, right? They can have educational content, entertaining content that we will be able to put out and just generally help people understand what the future of robotics will potentially look like so that they can, yeah, essentially as people want more of this information, we will be the central hub to put it out. I would also call out the other very important part of our marketing engine deals with portfolio companies, right? The purpose of RoboStrategy is to invest and help these companies scale up and become as important as possible, right? To fulfill their mission statements. And so there's a lot of help that we can do on their side for distribution to help grow their brands, grow their distribution. And then the cross-pollination of those two audience we think will be critical as well. So as RoboStrategy's brand grows, we will see companies that are doing very interesting things. We can let our audience know, highlight the things that they're doing, which are cool. And then as their brands grow as well, right, their surface area as they market with us will flow back into the central hub, which is RoboStrategy and the team here. So, yeah, you know, to in conclusion, right, to summarize, we know a massive wave or we have high conviction that a massive wave of attention is coming. The idea is to position early, build a strong foundation, build funnels that will convert people to our channels and capture that attention and look to compound it as the entire backdrop of robotics becomes more and more important in the public eye.

Yeah. To provide some more context on why we think we're even talking about marketing as our core competency here. As Kevin mentioned, helping our portfolio companies is really important. And it helps us, you know, as a part of our portfolio, if the companies do well, and if we can help tell their stories of the world and help them increase their reach to millions more people, then they can also sell more robots. They can get in contact with more potential customers. They can hire better talent. They can raise more in further fundraising rounds. And so it's important for our portfolio companies, but it also helps us as well because for RoboStrategy, we want to scale as a fund. We want to get to a very large size, potentially one day even as big as SoftBank. And to do that, we need everybody to know about us. And to do that, right, we're going to go across a lot of different channels. And for people, once people know about us, you know, more people might consider investing in a robust strategy. And that also helps us with, you know, not having a discount to our NAV, which is something that a lot of closed funds, closed end funds might need to deal with is managing their premium or their discount to NAV. And in general, funds try to avoid discounts and they might prefer to have premiums. I'm going to go a little bit into the team. My previous background was the founder of Mechanism Capital, which we were investing in Frontier Technologies. It was primarily my personal capital. And throughout the last two and a half years, I have had the opportunity to build great relationships with some of what we consider most important robotics founders of the next generation. And I'll let the rest of the team introduce themselves here.

Hi, everyone. So I'm Mark Weinstein. I'm the Chief Operating Officer of RoboStrategy. I've been a partner with Andrew on Mechanism Capital for the last six years. We've invested together in over 100 companies. I've been helping build out the team operations and finance stack for the company, as well as sitting on the investment committee and helping to evaluate investments. Prior to Mechanism, I was at Morgan Stanley and Jefferies on their investment banking Hello, everyone.

My name is Scott Walter, and I am the Robotics Research Diligence Director at RoboStrategy. And I have firsthand knowledge of what it's like to create a robotic startup out of a doctoral thesis. I've been in the business for 40 years now and have created two robotics companies, both with successful exits. And the idea of those companies was to reverse engineer existing robots, create digital twins of them, put them into virtual worlds, and then begin to do simulation layouts, planning, along with robot offline programming. so that sounds kind of familiar it's very much what's going on right now so that skill set is sort of the perfect skill set for helping us to reverse engineer many of the investments we're going into so we understand exactly what they're trying to do hi everyone i'm jack pearson and i'm an investment principal you can think of me as a mini scott i've spent the last 10 years as a founder and operator in robotic startups, including a stint in Shenzhen.

My focus has always been on building and integrating industrial and automated systems that deliver value in the real world, not the lab. So I'm excited about robots that do real work and bring true economic value.

And then I believe I'm the next person that is on here. But yeah, I'm Kevin. Like Like I said, I'm focused on all of the marketing here at RoboStrategy. Previously, my career, I spent a number of years venture investing in emerging technologies, mostly in the financial technology space. And then I was an early employee at a company called Monad, was more or less responsible for the brand growth. So I took it essentially from zero to hundreds of millions of impressions per month. also played a larger role in the fundraising of hundreds of millions of dollars for the firm.

Yeah. So this slide here is on the investment team. But I think it's important to call out that we're not just building only an investment team. We're building a real robotics investment platform. And what that means is we're going to be involved and try to be involved in the national policy around, you know, how do we drive forward the robotics industry? What are the different government initiatives and laws that can be put in place to make sure that our industry really expands? And, you know, that could be through loan programs. It could be through government, direct government investment. It could be through setting up new training programs. There's a lot of ways to make the industry flourish where, you know, right now it's still very early. But we believe that correct policy can really, really drive the explosion of the industry, like you saw in China, for example, where the government poured in a lot of money and support. And it's the reason why they have hundreds of humanoid companies today. And so recently, for example, on our policy team, we recently hired Bill Hughes, who was previously heading up policy work at ConsenSys. We are also building out a research practice internally. A lot of the roots of our team members on the investment team come from doing deep research, publishing that publicly, and it helps with a few things. One, it helps to inform our thoughts. It helps to build our brand. And then additionally, we can answer some really important questions that are not answered right now. There's no semi-analysis of robotics. And the industry and their portfolio companies and us, we have these questions around, well, if the demand for robots jumps from tens of thousands to millions, tens of millions, how elastic is the supply chain? How is the supply chain going to deal with that? Where are the potential bottlenecks going to be? And how deep are they going to be? And how might that change over time? So there's not much information around some of these questions. And I think that will be an important part of driving our brand forward and our ability to invest in the best roboters companies. So I think an important part of the fund being successful is we need to be able to build relationships with founders and tell our story around why RoboStrategy should be one of the key investors in the company. And so one of the things that we have uniquely is a permanent capital structure. We don't have the typical seven to 12-year fun life that traditional VCs do. Capital that stays in can potentially stay in for a very, very long time. And so it means that we have the ability to not just invest in the Series A, but also the Series B, C, D, et cetera. And that is really important for founders to have that long-term capital partner so they don't have to worry about, hey, in two years, am I still going to have funding or not? Because if we are able to scale, we'll be able to write those checks as long as we believe that these are the right guys that are going to execute and build the next big company. We also have a very unique team of former robotics founders and operators. We have not really met any other venture capital fund that has that similar type of experience. And there's a lot of venture capital funds that maybe have an experience in SaaS or in AI. And now they're looking to get into this field, but it's going to be really hard for them to be able to underwrite these deals and really figure out what is the risk or reward that we're dealing with for every single investment. And this is something, by the way, that the founders appreciate as well, the fact that we've done our research so deeply. And not only can we help them from a financing perspective, but we can offer our perspectives, having worked across a lot of different companies in the industry. And for some of our team members, you know, having built similar companies, Scott, for example, having sold his last company to Kuka, you know, helping them with introductions to other potential customers, supply chain partners, and potential talent in the industry. And this is a totally different network, by the way, than the traditional, you know, SaaS, right, industry, which was concentrated primarily in areas like San Francisco and LA and New York, where, you know, A lot of the customers and relationships and talent, they're in places like the Midwest or in other parts of the world. And so there is a big geographical difference that we spent a good bit of time tapping into in terms of the network that it's going to be a little bit difficult for other funds to catch up with. In terms of the marketing component, we talked about that already. And we've been very active in supporting the founders that we work with. And, you know, there are some quotes that, you know, some founders have put up in terms of their experience working with us. Brett, he's the founder of Figure AI. And then Evan is the founder of Standard Bots. These are the real heroes of the story. You know, I don't want to take any credit away from them. These are guys that are actually doing the really hard work in building these incredible companies. And we're very fortunate to have a good relationship with many of them. And so that, you know, we can not only can we invest in, you know, the rounds that are happening now, but we can do it in the future as we believe these companies will continue to grow. And the best way to invest, I believe, is doubling down on your on your winners. Talking a little bit about a little bit more why this is important. Right. There was this tweet that went viral last week talking about Anthropics latest round. That was a really hot round. And I think at this point, a lot of the world understands that Anthropics is built in a really incredible product. They have really incredible models and researchers and this company could be going places. But when a company gets hot like this, right, everybody wants an allocation is thin. And if you were the VC that passed on robotics, you know, two years ago, three years ago, you might not be the first in line. You know, for Anthropic, for example, they were, there are a lot of prominent VCs that tried to get into that round and a lot of them weren't able to. And so being early and showing your support is something that we believe is going to be really helpful for us as a firm down the line. This is a little bit about the portfolio. We've made at least 12 investments so far and continue to make them. And in terms of our overall portfolio strategy, what it looks like is we believe in high conviction, high concentration. So you might expect, say, 70% of the portfolio to be concentrated in those really high conviction bets. And so that might be anywhere from six to 10 companies. And then we might have another 30% of the portfolio in earlier stage companies. And the rationale there is, look, what's going to move the needle is if you're sizing investments correctly. But at the same time, if we're going to be investing a lot down the line, we need to have those early relationships so that we can, one, follow that team and company and seeing if they're actually executing or not. Because one of the biggest predictors of success in the future is your success and execution capabilities in the past. Not only that, but we're able to have those relationships and of course, be able to get into the later rounds if we're investing early. And it also just gives us a lot of visibility into the ecosystem to kind of see how maybe the data collection space is evolving, how the actuator design space is evolving, et cetera. And so Figure is one of the biggest companies within our portfolio. We are really excited about this. We think this company is going to be essentially the apple of our generation. And I'll hand it off to Scott to talk a little bit more about Figure and Eptronic.

Yeah, thank you, Andrew. So Figure is probably the consensus leader in the humanoid space right now. Now, that's not my opinion. That's the opinion of many of the roboticists and other founders that I speak to quite frequently. And a lot of it is because Brett has really been able to execute quite well and assemble a crack team. I was an early investor in Figure around the same time as Andrew before we knew each other. So I had a chance to sort of see what was going on there. And I was really impressed with the team that they put together, the speed of execution. They own the entire stack in the hardware. So from feet all the way out to the fingertips, they're building everything on their own. And they're also building their own AI stack. So I expect the execution will only get better. And if you didn't see the 200-hour live stream a few weeks ago, that is where a lot of people are building the conviction and why they really see them as the current leader. Now, another humanoid company, which is also in our portfolio, is Aptronic. And again, a very good team, very good founders. Jeff Cardenas is an excellent CEO. He's one of the OGs going way back to like around 2015 when they were starting to build robots for NASA. And then they founded Aptronic. And actually, some of the other humanoid companies out there gained a lot of their experience some Aptronic and actually had some early prototypes built by this team because they were that good. They're extremely respected to the point that companies like Google DeepMind have invested in them twice and are seeing them as a platform to be able to do their physical intelligence on top of them as well. So I consider them kind of a dark horse. A lot of people have not heard of Aptronic, but over the next several months, you probably start hearing more and more from that team.

So thanks, Scott. The next company is Dyna Robotics. So I would say Faker and Aptronic are the most known companies within our portfolio. But we don't always invest in these companies. And it's not always the best time to invest in them after they're really well known. It's still a good time to invest. But of course, maybe it's better to invest earlier. And so Dyna is a company that we found last year. And the CEO and founder of Dyna, co-founder of Dyna, Linden, he had previously sold his company to Instacart. It was also in the hardware and AI space. So incredibly relevant. And he's assembled a great team of researchers alongside his co-founder Jason Ma, who was previously at NVIDIA and DeepMind. And I think what's special about this company is that not only are they excellent at physical AI research, they're one of the few research labs out there that were able to actually achieve above a 99 success rate for real world tasks in deployment. You see a lot of videos out there of robots trying to show off physical AI models, but a lot of the time, those are short clips and they might have tried a hundred takes and, you know, they just found, they clipped the best one. And that's the one that you see online. What really matters is, can these robots do work in a deployment environment? Can they do it without any human intervention? And can they do it for a continuously amount of time? Because if you have a robot in a lab that needs to be, you know, serviced or debugged every 30 minutes. That's not a real product. And so getting to that production grade capability is something that Dyna has been incredibly focused on and has been one of the few that have started to really execute on it and deploy their robots in real world environments, one of which includes a partnership with Red Bull and with other pretty well-known enterprises across the world. And they also have, they're building their own robot as well. Next one is Path Robotics. I'll hand it off to Jack to speak about them.

Great. So we've just heard about three amazing general purpose systems, but I think we believe that the future isn't really about general versus special purpose. Both will coexist. The question is, where will each be successful? So I'll touch on this quickly before getting into Path. A simple mental model that we use is For a special purpose to win, there needs to be a big enough TAM that's big enough to support a dedicated player and a technical barrier that is hard enough that a generalist can't cross it. And welding is basically the perfect market for this. There's a structural label gap. It's one of the biggest choke points to re-industrializing in the US. It's predicted that there's going to need to be an additional 300,000 plus welders by 2029 to meet demands. there's 80 to 90 000 openings per year and basically only two new welders entering for every five retiring so this is a huge problem and part of this is because welding is the hardest thing you can do in a factory it's um it's it's almost a craft that people spend their entire lives perfecting this isn't something that you can easily on board now we've had welding robots for basically 40 years the key thing is that these robots are pre-programmed they're not autonomous which means it requires a lot of skill to program them and you can only use them when you have a high enough volume of tasks so automotive uh and industries like that it's a very niche product that isn't scalable across all of the possible welding jobs and path is the first to truly crack autonomous welding so they have a solution that doesn't require programming and that can adapt on the fly to all of the variability that happens during welding, whether it's the part warping, whether it's placement, and that's a huge, huge deal. It's required tens of millions of weld inches to build a world model that can actually produce and work and deliver value in this space. And that moat is something that will be very hard for a generalist to accumulate a data set that's big enough to compete. They'd essentially have to become a specialist. so the team is you know has an amazing pedigree they've been working on this for a while and it's paying off they've hit product market fit sales and partnerships are moving very quickly and they're becoming known as the industry leader in infrastructure defense and shipbuilding and i think one of the things that's really exciting about them is they've proven that this works on fixed automation but earlier this year they actually launched a mobile welder so taking their welding world model and deploying it on a mobile quadruped showing that it's not a it's not a system that is stuck in one niche it's something that they can actually expand

for into a more general solution so um lots of really exciting in in in path robotics um i want to talk a little bit about daxmate which uh is a really special part of our portfolio in the U.S. you have these big cubanoid companies which one we're really excited about but it's going to take a little bit of time before those are available for everybody and they have a very unique I wouldn't say very unique but they have a business model in which they don't really plan to sell their hardware to everybody and anybody until much in the future when they believe this thing is safe around humans. It can basically provide the exact experience that you would want from a robot. And so you'd be able to tell it to do something. You'd be able to do, you know, most of the things that you would ask for. Dexmate and a lot of the Chinese robots take a different approach, which is they say, look, we've built some really great hardware and software that make it easy for you to actually program and train a robot and so unitry took this approach you know many years ago i was a little bit skeptical of it at first right because look it's it's a little bit hard to understand the market if it's a robot that is not explicitly sold to do something but you know what? The market for research, for entertainment, right? You see a lot of the Unitree robots going around and doing backflips and dances. And now you even see robot influencers. That is actually quite tremendous. And so if we think about robots as a hardware platform in the future, in the same way that you might think about your iPhone as a platform for other people to develop apps on, you can think about your robot in the same way, right? People will eventually be developing their own skills, their own applications on top of these robots. And, you know, you might maybe have something, for example, like Gordon Ramsay training a robot skill so that your robot can cook as well as Gordon Ramsay. Or maybe, you know, you'd want to train a robot to work in a specific hospital application, moving hospital items from room to room. That platform has a lot of power. And if you're able to distribute your platform out earlier, you can start building a developer remote around yourself. You can start building, getting your robots out in places so people are comfortable building on top of that robot and interacting with that robot. And so Dexmate has taken that approach and they've sold to, you know, basically all of the important physical AI and actual AI labs around the world in the US and to some very major companies. And there are a lot of startups that are going to start appearing around the physical AI and robotic space. And a lot of them might have a lot of potential, but they might not want to be the ones that are building the hardware and the manufacturing capabilities. They might just want to develop on top of a robot. And that is the platform that Dexmate provides. And so This is the only company in the U.S. that is taking this approach right now, and that has actually sold a meaningful amount of robots. They have a wheeled robot, and they're also coming out with their lagged robot very, very soon.

Excellent team. uh we've talked to uh a lot of their customers and uh you know by far uh the customers say they rank them at the top compared to the other um hardware platforms that are available on the market um going into standard bots uh jack did you want to speak about this one yeah yeah happy to um this is a really exciting one you guys may have all seen yesterday but it was announced that they've raised 200 million series c at a billion dollar valuation and we were very happy to lead that round because these guys are going to become a national champion for the us in robotics and um you know robot arms they're the the workhorse of robotics and automation it's the first place that people go to automate a task with six six axes you can do many many different jobs you can machine tend you can assemble components you can weld it's a very very broad horizontal platform now there are two big problems though with the current breed of robotic arms and it's essentially it's based on you know let's say the legacy way of doing robotics which has been around for 40 plus years so from a hardware perspective these systems are built for pre-programmed um you know designing a set of instructions previously and then running those repeatedly live. That's not how modern robots work. Modern robots have a much tighter feedback loop of AI that's making decisions on the fly. And these old school robots just can't really do this. And they're also designed quite poorly for ease of use and just don't have those best principles. The other thing about robot arms is europe is a champion japan is a champion and china is a growing champion but the u.s has no sovereign player which is a huge gap if you think about it now standard is coming in and is great is very well placed to not only become the u.s's sovereign champion but also to reinvent how robot arms are made so they they design all their arms and assemble them in new york and they've got a roadmap to bring in the entire supply chain to the US by the end of next year so it's a it's a US sovereign made arm which is very important for a lot of manufacturers but it's not just about the supply chain they're also reinventing because they're able to vertically integrate they're reinventing the hardware the software and the AI to make them all work together to solve a lot of the problems that exist with legacy arms so new actuators that are much better at dealing with feedback, a UX that uses best practices from, you know, AI and coding to be as easy to use as possible, and also the ability to use and train your own AI models or use whatever state-of-the-art systems that exist from, you know, the leading model manufacturers. You know, you can imagine someone like Dyna creating a model that could run on a standard bar. So very exciting reimagination of what a robot arm can be and the leadership team is perfectly placed to deliver on this you've probably seen evan a number of times testifying to congress on the importance of robotics the importance of a national strategy for the u.s so they're in a very good place and their goal is to deploy 10 of all industrial arms in the u.s by next year and we think that they're in a good position to deliver on this so it's very exciting company very exciting team yeah just to speak a bit more about standard bots industrial arms and cobots have been around for some time and it's been you know a decently sized industry but it hasn't been on the scale of you know i would say

like hundreds of billions or trillions quite yet and it's because of all the challenges with traditional robot programming and installation and a lot of that is going to be solved with the advent of physical ai and these models getting better and better and just easier to play eventually as soon as just maybe just like you know direct you know just drop it into a to a facility, tell what to do, and it'll do it. We're getting really close to that. And so, you know, we're really bullish about humanoids because they are general purpose. They're essentially like the GPUs of physical labor. And, you know, robot arms and cobots are basically the same thing, because not every robot needs likes to move around. There are so many tasks in the world where you just need to be stationary. And so you can think of maybe the industrial arms and cobots built by standard bots as essentially the GPUs of industrial work. But they're also building robots that can move around as well. You can see that in the picture over here. And so, you know, I think there's going to be billions of humanoids. I think there's also going to be billions of industrial arms. And there's very few other players that are in America that are in the position to be able to build that out for the American industrialization effort. Um, so going into, you know, the rest of the portfolio, I don't think we need to spend a lot of time going into some of our smaller investments. We also think a lot of them are really interesting. I might just kind of summarize, um, that a lot of the companies that we talk about today, they're on, they're, a lot of them are vertically integrated. And so they, you know, they're working on the software, they're working on the physical AI, they're working on the hardware and they're working on manufacturing as well. And I think it's really important because as an investor, we need to think about all the different scenarios that can happen and the probabilities that those scenarios might happen. And if, for example, I'm only building in the model space, I think there might be some winners there. But what if Google or NVIDIA come out with the dominant physical AI model, just as Google has Android and that takes up the majority of the market and you have iOS, which is the other basically half of the market. We are not sure whether that happens or not, but that is definitely a scenario that people need to think about. And if that does happen, well, for these companies that are also building their own hardware and manufacturing, then they have other shots on goal. And they have a lot of moats in places that are harder to displace, assuming physical AI capabilities get better and better from some of the bigger companies. Because eventually, right, very soon, we're going to need to produce hundreds of millions of robots or more. We can't do that instantly. Like you can with AI, right? I can spin up hundreds of thousands of instances in a very short amount of time. But for me to build hundreds of thousands of robots, that takes years of planning, of infrastructure creation, of engineering work, of setting up your manufacturing processes. And the companies that have done this legwork are going to be in a very good position over the course of the next few years, because we believe that the model capabilities are on an exponential curve, which means the demand from robots, right, they might be low right now, but they're going to jump up really, really quickly. And people that want to, you know, maybe come in and become new players in this space, they're going to have a tough time catching up and competing with the people that already put in the legwork. So that's a little bit about our portfolio. I will maybe pass this off to Q&A if, Mark, you wanted to ask or deliver some questions.

Hi, Andrew.

Mark lets me know that his Zoom is currently frozen. okay he is trying to find a few that a few questions that came up in q a so let's um i can he's over here um we had one question come up so far in the q a and it folks on watching live on the first is i think one that's really important for us to address bot is currently trading at a premium to its net asset value as an investor how why should i buy

here versus waiting for the company to trade at its net asset value so it's a it's an interesting question that we get a lot and i think it goes back to the we can address this in a lot of different ways. One is understanding the net asset value and how that is calculated and how that is stated. It's a lot different looking at the net asset value of private assets than, for example, a company like Bitcoin, which might have their net asset value based on the value of their Bitcoin holdings, which is a liquid asset and there's constantly a public market price. For us, we deal with illiquid investments. And so there are a lot of different ways that you can mark these illiquid investments. And some of them are, well, you know, all of them are relatively subjective. The way that our process works is our auditors and admin, they look at the last round valuation. And then, you know, maybe they mark it at that last round, or maybe they put a discount on it, depending on the share class of the investment that we have. What that means is sometimes there are things in our portfolio that the net asset value does not account for. For example, if there is a new round that is ongoing, this could be at a higher valuation or a lower valuation, that valuation in our reporting is not updated until we go through the full process of waiting for that round to close. And then for our admin and auditors to run that process, and that could take a few weeks, it could take more, to then strike a nap. And then at which point it is published. And so there is a lag which investors might need to take into account. If we look at, for example, the recent Anthropic round, that was somewhere around $900 billion. The round before that was close to $300 billion. So a 3x difference between rounds. And while we cannot communicate the status of ongoing rounds because that is private information, sometimes that information disseminates. And across public media, people understood that there was a $900 billion round that was ongoing, and that started to get priced into some of the funds that held an anthropic position. What it also doesn't take into account is if we are currently working on deals that might have what we consider asymmetric upside in the future, or we've done deals in the past that might be marked up or marked down, but we haven't gone to the time where they're reflected in our NAV. And so there are reasons for NAV to differ from the market price. And maybe we can talk through why the market price might trade at a premium or at a discount. In terms of a premium, right, this exposure is more liquid than the traditional VC or SPV exposure. The timing lag. There's also this aspect of supply and demand where that's at the end of the day how assets are priced based on supply and demand. And there's not a lot of supply for these private robotics companies or private AI companies in the public markets. And there is a lot of interest for these companies. Private valuations are also maybe not reflective of valuations of that particular company if they were to be in a different market, because every single market has a different subset of market participants. And say, for the private markets, for example, of venture capital investors, that is a relatively small subset of total investors in the world versus the public markets, which is basically the subset of a lot bigger of a pool, most of the people in the world. And so it might not be too unreasonable to think that if a company were to go public or its shares were trading indirectly publicly, that the public markets might value them differently because they have a larger pool of potential buyers. In this case, sometimes sellers. In this case, not too many sellers exist or exposure vehicles for these private robotics investments, but that might change in the future. And so that's things that investors should take into account. The other is our ability to continue to make investments in the future that perform well. We as a fund are relatively new. We have had prior experience investing in robotics over the last two to three years, and some of them have gone very well. But we still need to prove out our investment track record as a publicly traded fund. And as belief in that grows, just as with other fund managers, there might be more interest or demand for the fund itself. Unlike traditional VC funds and SPVs, we do not charge a performance fee. We charge a management fee of 2.5%. And that performance fee is not reflected in the NAV. If you were looking at the NAV of a particular their SPBE or a fund, they might have a performance fee, but they just look at the net asset value. In the future, the performance fee might have a drag on the net asset value, but that is not reflected in the current NAV. And then the final point here in terms of why a fund might trade at a premium to NAV is a potential expectation for compounding exposure per share. If you look at MicroStrategy, for example, when they started, they had, well, we don't know the exact number, but hypothetically they had one Bitcoin per share. And in five, six years later, as they executed on their strategy of accretive issuance of doing essentially this multiple or evaluation arbitrage, they increased the amount of Bitcoin held per share. I think it was around 5 to 10x. And so while our primary goal is making really great investment decisions in the robotic space, because we trade at a premium to NAV, it gives us the ability to issue new shares to raise additional capital. And we can do so in a way that is accretive to shareholders by increasing the dollar per share, right? That's the NAV per share, and then reallocating that into more robotics companies. And so if we think about MicroStrategy's goal as increasing the Bitcoin per share exposure, our goal, secondary goal, is increasing the robotics equity exposure per share. Hopefully we can prove that out. And there's a lot of factors that can influence a discount as well. If people start to get bearish about the industry, about the companies, right? People might not want to buy exposure to them as much. Sometimes companies can go through down rounds as well. And there might be some tax considerations as well. And we can kind of get into this example of what accretive issuance actually means, because this is a little bit of a confusing subject. People see dilution sometimes as something that is a little bit scary because in some cases it can be done not very well. If a company issues billions of dollars of shares and they dilute the shareholder base and then they don't invest that well, then it could be bad for shareholders. In the inverse, if a company issues a lot of shares to raise additional capital and they invest it well and there's a large ROI for their business on that share issuance, then that can add value, right, for shareholders. And so we just take this one example of, say, there's a fund that has a $100 total NAV, $10 NAV per share, 10 shares, and it's trading at a premium, a 3x premium. You issue one new share, you increase the share count by 10%. That one share turns at $30 of cash for the fund. And so you increase the NAV fund of the fund by 30%, 100 to 130. At the other end, you consider that there's one new share that is made available now. And so there's this aspect of dilution, but on a per share basis, this actually nets out to an increase, right? You go from $10 to $11.8. That is an 18% increase in the NAV per share value. And so over time, this effect can compound. As you build the NAV base, you're doing this accretive issuance on a larger and larger base. And so, for example, if we were to look at the prior example and extrapolate it out to multiple rounds, first round could be 1.8 of increase for NAV per share, while the second one could be 2.15 because you're doing this off of a larger total asset value. And over time, this can translate into larger NAV per share increases. And that is dependent on the amount of issuance that you do. If you're at a premium, the more issuance that you do, the more potential compounding that exists. And at the higher premiums you do them at, the higher compounding that can exist. And so this is not to say this is 100% possible, but it is a consideration for investors that when you're considering the NAV premium, you're not just looking at the risk of NAV compression, that is a risk that you have to consider, but it can also evolve into a positive trade-off, right? Where the fund might be able to increase the robotics exposure per share over time. And that could potentially be a larger weighing factor than the actual risk of premium compression, depending on how you look at things. Thank you for that response on the nod.

I think just for the sake of time, we have one more question. I think we're 15 minutes over here.

We have one more question about kind of the global competition between the U.S. and China in the robotics industry. um investors are curious for your take on kind of who's going to be a winner of that race yeah that's a great question there's a lot of excitement about chinese robotics um what i'll say is i think the chinese robotics industry is going to do really well there's a lot of talent there's a lot of resources going into that industry and there's a lot of government backing they've produced some great products in the past um they've produced great phones they've produced great electric vehicles uh and a lot of times they sell a lot of those as well But I will say what is good for an industry in terms of technological development doesn't always translate one-to-one for shareholder value. And so if we look at the Chinese phone industry and the Chinese car industry, those companies trade at fractions, like less than 10% of what American companies in a similar field trade at. BYD, for example, they make great cars and they sell more cars than Tesla, but they're worth maybe 5%, 10% or less of Tesla's market cap. The reason for that is because China is a really what I would consider a cutthroat environment when we're talking about competition. In some senses, it's even more capitalist than America. And the government there, while they're incentivizing the industry, their primary goal is not driving huge stock market recurrent and shareholder value. It is increasing the benefit to society. And that's what you get from incentivizing a lot of great companies to emerge in the field is you have them compete against each other that produces faster technological gains and it also produces lower prices, right? Because they have to compete on margin. And they also compete on talent with each other and that talent can flow between company and company. And at the end of the day, I mean, that might result in very, very thin margins. And when we look at the best misses in the world, they're companies that have a lot of pricing power and they're companies that have large margins. And so if there's a shock in the supply chain or they might need to reduce their prices, they still have a very, very durable and strong business. And that's American companies, right? While the robotics industry doesn't have as many players in America, that I think is a good thing from an investment point of view. I think we should have more as an industry, but it does make our job a little bit easier because there are so few really, really great founders and companies. And so when you do find a really excellent one, the competition for them is not that hard. And so your risk as an investor is lower. I don't have to worry about 90, you know, figures or Teslas popping up. You know, I can sleep a lot easier at night knowing, you know, bigger and the Brett and the team that he's put together are very special and exceptional. And the talent pool for a lot of the expertise needed to build these companies is relatively small. There's maybe a few hundred people that are really, really great at robot learning or hand engineering. or, you know, scaling complex hard tech in America, right? So because of that niche or small talent pool, it's a little bit easier for us to find the real winners and to back them. And for, you know, us to also believe that there could be a potential larger outcome because the pie is, you know, shared among fewer players. And so it works to, you know, the investor's benefit from both a risk and reward perspective. I don't think it's, you know, some people frame China versus U.S. as who's going to win. I don't think that's the right way to look at it. I think both industries are going to develop tremendously. And I think America will potentially produce bigger winners from an investment point of view.

Thank you, Andrew. And thank you to everyone for joining. We've been on for, I think, 15 minutes over the initial hour we had scheduled. We really appreciate you coming. If you want to learn more about RoboStrategy, you can follow us on X, the ticker is BOT, on NASDAQ, B-O-T, on X, we're RoboStrategy, and you can go to our website, www.robostrategy.co. There's going to be a lot more announcements coming, a lot more to share with everyone, and we sincerely appreciate all of your time. So feel free to reach out to us if you have any further questions. Thank you.