Okay. Good afternoon, everybody. I'm Noah Poponak. I'm the Aerospace and Defense Equity Analyst at Goldman Sachs, and I'm very pleased to welcome to the stage with me, Robert Cardillo, who is the Chief Strategist and Chairman of the Board of Planet Federal. Robert, thanks for being with us today. Great to be here. Thanks for having me. Maybe just to kick things off, give everyone a little bit of an introduction of who you are, what you do at Planet, a little bit of a unique position, I think, at the company, relatively new to the company, a pretty impressive background at the U.S. government, maybe using some of Planet's capabilities. Please. It'd be great to just kick off with that. Thanks. No, I'm happy to do that. I'm a big believer the audience should know. I wonder if you could give me some point of reference for who's speaking to me. So yeah, I'm actually quite proud of the fact that I'm about four decades into this business. Now, most of that, 90% of that, was inside the U.S. government. And when I say this business, I talk about the ability to use space and assets in space to make better decisions here on Earth. Most of that time, as you mentioned, I was in government either as an analyst or a manager, and ultimately an executive, and finished my career as the director of the National Geospatial-Intelligence Agency. That's the entity that does that value creation for the government, whether it's mapping, charting, navigation, or intelligence provision from those assets in space. You're right. I was exposed to Planet Labs when I was in government. Planet Labs is about 10 years old, and so it actually came into being about the time I became director. Broadly speaking, the government was in transition, and we should talk more about where the government is today in that transition between using their own bespoke capabilities that they are and should be quite proud of, but also finding a way to leverage commercial innovation and applications in a way that can create both efficiencies, so reduce costs, but also effectiveness. So, a long way to say, I was pleased, some three and a half years ago, now almost four years ago, when I was able to join Planet and to begin to chair the Planet Federal Board, as Planet was looking to apply its capabilities in a way that would go to the value proposition I just described. And so, it's been a great ride. Thrilled to be at Planet on this ride and to help them and us create additional value across all sectors. But, I'm focused on the government sector. Excellent. Okay. That's great. Appreciate that. Maybe, maybe you gave us a few examples there of kind of the categories of how you would use the imaging. Maybe go a little further on some, some examples of ways you used geospatial imaging in your role, if you use specifically Planet's product in your role. You know, that could be helpful as well. Yeah. So, as I mentioned before, the government's got a proud history of its capabilities. And for most of my history, they kept that pride to themselves. Highly classified. And so, it was a different ecosystem, if you will, when you think about that use of space. And by the way, that use of space still exists and should exist because the government always will have activities or interests that it doesn't want publicly known. The difference that Planet makes and the commercial imagery industry writ large is it gives government two things. One, it gives an amount of physical coverage that the government doesn't have on its own. So. Right. You may know, but to let your audience know, Planet is and has the largest remote sensing constellation in history. Right. Over 450 satellites that we've put in orbit. And part of that constellation does what we call a global scan. So just basically line scans the Earth once a day, the landmass of the Earth. And we've been doing that for over seven years now. And so that kind of potential value, and we should talk more about what the real value is in that potential, is what, when I was in government, I found because most interesting and most useful because while I had capabilities to let's say to focus on a particular hotspot. Right. Imagine an area where there may be U.S. forces engaged around the world or a high-interest area such as a disaster recovery event. No matter how you cut up the world, that's gonna be a small portion, even though they're very important in those small areas. Planet's looking everywhere. I like to say Planet's the company you turn to when you didn't know the question you had yesterday that you'll need tomorrow. Yeah. Because it's always there. Right. And what's been exciting for me is how we turn that potential into real value. Yeah. You know, we've seen, I guess, recently there's been geopolitical conflict where, you know, the U.S. government, intel agencies would need to go to those areas, monitor the borders of those areas. And so there's, you know, sort of a clear-cut reason to go to them, that, that sort of bespoke work. Can you maybe walk us through some examples that have occurred recently or that you saw when you were in those roles in the government where, as you just described, the question that you didn't know you needed to know, came up and, and Planet really had the constellation and the imaging that was the only answer where Maxar or whoever else wouldn't have been able to do it? Sure. So, the broad answer to your question is what we use that and, and when I say we, either my old self as a government official or currently in commercial industry, is how can you best use that space access to either and/or both increase your confidence, reduce your confusion at your point of decision? And you asked about what kind of decisions are we reducing, you know, confusion about. Yeah. In some areas, you know, let's talk about some, you know, border security issues, you know. You know, we're now, unfortunately, into the third year of Russia's invasion of Ukraine. In advance of that invasion, there was a lot of questions about what are Russia's intentions and what are their capabilities and what's Ukraine doing in response to the threat that exists in and around their border. Back to my government world, you can imagine, well, you don't have to imagine. I can tell you there was a lot of attention being paid, right, in the government circles about answering those questions for the White House, for the Pentagon, for our allies. The world needed to know, needed answers to those questions, too, for many reasons. One, just, you know, basic democratic freedoms and sanctity of borders and respect of, you know, rights and those kinds of things. And what I love about what Planet does specifically is it adds a layer of transparency to a chaotic and cluttered world. Now, transparency doesn't mean perfect awareness and that you see everything and sense everything, but it just, again, brings down the clutter a bit. And for example, this was reported in the press, the day before what turned out to be the actual invasion, Planet used that daily scan to detect a bridging operation that Russia was doing in and around. And it was a combat bridging operation. They were building a temporary way to cross a river that could threaten Ukraine. Well, they were doing that at the same time that President Putin was declaring that, "No, no, no. This is just an exercise and we'll be soon returning to base," and so now that bridging exercise didn't prove that Russia was going to invade in a few hours, but it certainly added another piece of information to the question about, you know, how safe and how secure are we. So that's. Yeah. An example of the kinds of things that again Planet's able to provide, that holistic view, okay, not unblinking but holistic view that allows both diplomats but also civilians and populations to make better decisions. Right. And so it may not have applied very specifically in that situation necessarily, depending on how many eyes were on the region at the time. But you could envision a scenario, I suppose, where you see something like that happening, you see something being built, and with a bespoke snapshot, you don't know if that has been there all along. Right. Or if it's normal, whereas the backward-looking library that only Planet has. Right. Allows you to see the change. Right. Yeah. The one way to explain, and I'm glad you brought up the library, is that, you know, archive, right? Yeah. That's seven years of looks now, and I also, as excited as I am about that archive, it's also a bit daunting because, you know, it's, you know, the terabytes of information. Right. That are collected, right? And look, I used to run, I think, arguably the world's largest, you know, imagery exploitation business in the world, NGA, and I didn't have enough people to do it. Matter of fact, I publicly stated one day that if we needed enough humans to exploit all the imagery that are coming into our agency every day, the answer was six million. And. Okay. I was pretty sure at the time, and I'm pretty sure today Congress was not gonna authorize me to hire six million humans. Labor's pretty tight. The labor's pretty tight and it's expensive. Look, the point was and is, we really need to enable the machines to do what machines are really good at. And they're really good at answering three questions: what, where, and when. And now that we can talk more about the computer vision technology and the advanced computing that's coming to include artificial intelligence, but basically, machines are really good at that. Save the humans, save the experts, save the person for the really difficult, but I would argue more important questions about why and what's next. And in the intelligence business, the biggest question was what's next because you needed to help make decisions for tomorrow. So back to your question, what excites me most about where we are in the movie now is that the technology and the compute and the algorithmic applications that are, you know, being demonstrated, yes, in these large language models, is now helping to unpack that digital archive. And so. Yeah. You know, you mentioned turning back in time. That was the theory of the case. Today, it's now the reality. Okay. What's exciting is that you tell me what you're interested in, and it could be crops, right? It could be forestation or deforestation. It could be, you know, urban development. Whatever it is, you can now tune that algorithm to be able to give you alerts of interest given that history and to help you decide what's next. Interesting. It's, I guess, it might be hard to quantify or. Well, I'm curious to see what you'll say, but I did wanna ask where Planet is and I guess also the customer set is. I guess part of the question is who's really going to run the analytics, but where are you in the process of using AI and machine learning to sift through this mountain of data? Because, you know, for me, as a, I've covered Planet now for maybe five or six years. At the beginning of that process, there wasn't as much discussion about AI as there is today. I remember, you know, Kevin was at this conference a few years ago and kinda just only wanted to talk about AI up here. And it seems quite clear that it could really enhance what you offer the customer because I can envision, in some ways, I wonder why Planet's customer acceptance, revenue growth hasn't taken off faster because it seems like there's so much value to add from the imaging and the data that you have. And it would seem like one of the biggest hurdles is. Mm-hmm. Meeting six million people to sift through it. And so, at the end there, you sort of mentioned that we're in the reality now of using the machines to perform the data analytics. But I guess what inning are we really in on Planet doing that, the customers. Yeah. Being able to read and use what Planet does or the customers doing it themselves? Yeah. Top-level answer is yes. Okay. To all of those. Yeah, yeah. But let me explain why it's yes to all of those. So Planet is, one, again, quite proud of the original vision of the company, scan the Earth every day, increase transparency, reduce confusion, make the world a better place. Planet is still that company, right? That's who we are at, at a core. The way that we've been delivering that over years, and you've talked about it, we've talked about it, is applying that entrepreneurial and innovative and adaptive spirit to technology. So quite frankly, our founders came from NASA, were a little frustrated, no, very proud of the work they were doing at NASA, but, like any large government methodical organization, it's a little slow and it's a little, you know, to be kind, it's thoughtful, right, and deliberate. Yeah. People like Will Marshall and Robbie Schingler said, "You know what? These smartphones are coming out. They seem to be pretty capable. Why don't we just put one of these things up and see if it works, right? Right. Now I'm obviously making it sound a lot easier than it was, but basically, they, they did that first at NASA and then at Planet. That spirit is still in the company. As excited as we are and happy to talk more about it, about that archive that's been created, that seven years of scan, you know, Planet is continuing to iterate and to evolve its capabilities on the technology side. You know, we have now Pelican on orbit, we now have Tanager, the hyperspectral sensor going through its final testing and experimentation phase. To get to your question is, you know, what, you know, when does it, when does it break open, right? And I'll use my experience. You know, when I was in government, you know, and we were experimenting with that daily scan, now that I look back, 'cause I'm now seven, eight years ago when I was doing this, as a government official, I probably was too early from a compute and a computation point of view, meaning as much as we knew we weren't, didn't wanna put this in front of those humans, to analyze, we really didn't have the compute at the time, and especially in the government, which tends to be a little bit behind, commercial industry in that regard, and so while I would call the experiment successful, it didn't really scale. What excites me now, and you mentioned, you know, Kevin, having been here a couple of years ago, we're steep into the curve with respect to what's happening in that AI world. What you're asking about, though, is, you know, when does that potential, you know, co tie into that reality? Yeah. I'm gonna cheat and say now, okay? Okay. Meaning not, you know, 9:30, 9:00, you know, Eastern time. But it literally is happening. And what's very exciting to me now is that we interact with these large language models and we begin to do both our own in-house experimentation because you said, you know, "Are you gonna do it or are your partners gonna do it?" And I said yes, and I still mean yes. We certainly wanna create more value in our data set. So we call it analysis-ready data. So we're making it more ready for you. But we love the fact that companies are also coming down and research institutes are coming down into our space. And so I see a meshing of that happening. which means I wouldn't be able to give you an exact answer, "Oh, that's the line at which we'll stop, you know, lifting that data set up and. Right. That's where the partner will come in." I think we'll be pleasantly surprised, you know, when someone goes deeper than we thought they would. And likewise, I think we'll also be excited when we have an internal application that creates, you know, that turn of value that then begins to blossom in the scale that you described. I imagine there's going to be over time customers that want the raw data and wanna do the data analytics themselves, and there's gonna be customers that. That's right. Have no interest in that and want your analytics and then stuff in the middle over time. Let me say too, to that point, Noah, the government, my former, you know, life is also in that space because if you think about, again, the arc of my career in the early days, basically, we would just put out, by the way, at the very top secret level, a contract opportunity for somebody to build us a satellite, say, "Hey, look, it has to be this good. It has to be this capable and whatnot. Right. You know, you and by the way, those would go to the usual prime contractors. Right. Who built big satellites. They would then deliver the satellite and we would say thank you and then take it, right? And then just go do our own thing. Right. Right? So that was kind of the first phase of my life. Then about halfway through my career, commercial imagery began to start to happen. This is the late 1990s, early 2000s, and, you know, companies began to explore commercial launch, right, and commercial satellite development. Well, the government then took a look and said, "Oh, well, I'm interested in that data as well. So if you're gonna collect it," and we might wanna talk about what the buzz, you know, the additional value of being unclassified. You know, there's certainly a value in having something no one else has, but there's also a value in being able to share widely to add to transparency, so the government then moved in that phase. Planet, as you well know, is a proud provider into the largest government contract to do that acquisition, Electro-Optical Commercial Layer run by the National Reconnaissance Office. Very proud of our contribution there. But that's now that kinda we're now in the second bucket. Okay, we'll buy your data, raw data, if you will. Images go into the government. They then add value to them. What's exciting to me now is where we are today, which is the government is beginning to explore, maybe I don't have to buy the satellite. Maybe I don't even have to, you know, acquire the image itself. Yeah. I really just want answers. Yeah. Or I want detections or I want alerts and whatnot. And, you know, I call these subscription services. Yeah. You know, where, you know, think of you as a, you know, a pull-down menu and says, "You know what? I really, you know, I, I, I'm a I manage forests for a living or I manage, you know, wheat fields for a living," you know? Yeah. So pull down what you want and need. And again, to me, I think, well, Will, and by the way, Planet will always be in that, but each of those chunks of business, we will continue to build and evolve our satellite capabilities and our imaging. This last piece, the answers piece. Yeah. Is what excites me most. It sounds like you're saying the government customer buying that in size is just starting to happen. It is. And, you know, and I have to remind my friends at Planet, government never moves as fast as you'd like them to move. Mm-hmm. It's a little frustrating, but yes, I mean, we're seeing pilots. We're seeing experimentation. We're certainly. I say, too, is that if you listen to the speeches of the leaders of the National Reconnaissance Office and of NGA and the Director of National Intelligence, you will hear much demand signal in the speeches on just this. We just want analytics, right? We just want answers. Yeah. That hasn't completely got to the contracting office yet, you know? Yeah. So, there's a little. It takes some time for that to get downstairs. So you have long windows of time between the speeches on YouTube that the CEO's sending you. Thank you. And look, I resemble that remark. Yeah. I mean, I you know, made those speeches myself. Right. Look, I mean, in defense of my former government colleagues, there's a reason the government moves at the pace it moves. Yeah. It should be thoughtful. Yeah. It should be delivered. We don't want it to make big swings and misses. Now, yes, would we like it to be quicker and more adaptive, of course, but that was a long way to answer your question, really. Yeah. Yes. The government is moving into that space. I'll just say though, the government still is way better at acquiring that hardware than it is services. Yeah. It's still learning that second piece. Okay. You mentioned EOCL and EOCL's multi-vendor, and I was curious to hear you talk about your competition and the other players. Mm-hmm. Where you fit in the ecosystem. And then you also mentioned classified, unclassified. Yeah. And so maybe, maybe we could tie all that together. How do you think about the competitive landscape? Do you really even have real competition in exactly where you are in the ecosystem? Why does the customer buy multi-vendor on something like EOCL? Is it spreading out the capacity or, or is it different capability? And does it tie to classified, unclassified? So there's a lot in there. Let me unpack it a little bit. Remember, you know, I managed that contract in my government job for a number of years. Mm-hmm. meaning EOCL. Yeah. You know, it was called EnhancedView at the time. Right. But same intent. When that contract started, we had two vendors, GeoEye and DigitalGlobe. Yeah. So this is going way back now. Yeah. This is 20 years ago. Those two companies merged, and eventually became, you know, Maxar Corporation. So for all the time that I was managing the contract, I had one vendor. Now, I was pleased with that vendor. I mean, well, we wouldn't have paid them if we weren't, right? We had requirements. We had specifications, and Maxar delivered to those specifications. However, though, when you have a vendor, it's also a concern, meaning, you know, their viability then themselves. You know, you can have issues with vendor lock, of course, with one vendor. By definition, you have that. So when the contract was recompeted under EOCL and we added, we, the government, added two additional vendors, in this case, Planet Labs and BlackSky, I think that's really good for the government. Yeah. And I think if I was joined on stage by, you know, our friends at Maxar and BlackSky, they'd all agree that EOCL is, yes, good for our companies and also good for the ecosystem. The fact that the government has that long-term demand signal obviously answers some investment questions about, you know, where is this all going. Right. So, a long way to say, I think that multi-vendor is broadly good, and I think. Pure diversification. Yes. And look, I didn't create this view, but I like it. The one that says, you know, as competitors, we should be looking for a bigger pie together and then fight like hell over the pie, right? Yeah. You know, when it happens, and so I think we're aligned in that. What's also interesting though is the piece that you asked about, you know, classified versus unclassified. There's obviously good uses for both. On the unclassified side, the real differentiating value proposition is shareability. I mentioned the issue with, you know, Russia and Ukraine. And obviously, that was feeding into some pretty weighty decisions about, you know, U.S. and NATO and, you know, military responses and how do we move forces around to deal with what we're seeing on the ground or sensing on the Russian side. Let's face it too, there was a need to inform the public about what was happening because that was February. It was winter. It was clear that if there was going to be a Russian invasion, there would be economic consequences. Yeah. There would be sanctions, and those sanctions would come back to, quite frankly, impact our own citizens, especially our allies in Western Europe if we were gonna cut off oil and gas. Right. provision. Well, you want your public to be well-informed about, "I want, you know, why is the government turning off the heat?" You know, essentially. You know, "Why is my apartment colder this winter than it was last winter? Why is my price of energy going up?" etc. This, again, is where I think that transparency can help. You know, and again, I'm not, it's not Pollyannish, you know, if we all just see the same picture, we all can then just, you know, get along and have no disagreement. No. It, it to me though, it just, it raises the level of shared context. Yeah. So that at least maybe we can have a little bit more informed debate about what the meaning of that is. Yeah. Look, I. That makes a lot of sense. Yes. And so that shareability, the transparency, I think helps not just on the, you know, on the government side, but I think it helps on the public side as well. Yeah. No, seeing something is different than hearing about it. It is. As a matter of human nature. I wanna ask about the commercial side of the company. I guess just as a start, I mean, how much time do you spend with the commercial side of the company? more and more. Mm-hmm. When I'm talking to colleagues and we're catching up, they, I tell them that I'm pursuing an informal MBA. They go, "What?" and I go. Yeah. So I said, "Yeah, at Planet, I'm starting to learn how real businesses are run. Right. Right. 'Cause people, they read my resume, they say, "Oh, you've run a large business." And I said, "No, government agency. Yeah. Which is not really a business. I mean, it is. It's different economics. It's different economics. And so, one of the things I really enjoy about my role at Planet is, yes, they look to me to help, you know, the sector that we've talked about and how can we grow this. And by the way, while we've talked about U.S., you know, I'm also involved in our international. Okay. Business for the same on that government and defense and intelligence market. But on the commercial side too, it's a steep learning curve for me, but one that, you know, I'm finding more and more parallels because at the end of the day, while the use cases are obviously different, in some cases, you know, there's a very particular outcome that a government, especially a defense or intelligence consumer, is pursuing. There's a lot of commonality, right? Yeah. Yeah. You know, people just wanna be a little bit more confident at that point of decision. Yeah. And again, it could be, you know, do I plant today or do I plant next week? Do I harvest, you know, two weeks from now? Do I employ a certain new strategy? So while yes, I spend most of my time on that government side, I'm seeing and feeling and experiencing more and more crossover. Part of your bio discusses increasing utility of commercial innovations for government customers. So what does that mean? Is that really just taking the fact that Planet's really a commercial enterprise and taking it to the government, or is that working the other way to the commercial side as well? It means the former. Yeah. Okay. Again, we talked earlier about the methodical nature of government, you know, decisions and moves. While that is broadly a good thing, but the way the government works through its requirements and budgeting cycle. Yeah. It's broadly speaking a two-year horizon. Meaning, if you and I were in government today and we had this, you know, critical need. Yeah. We'd be planning to submit a budget about a year from now hoping Congress would work on it and send it back in two years from now. That's challenging when, you know, let's go back to our AI discussion and, you know, weekly, you know, if not daily, changes are happening in that market. Now, to the government's credit, they have things like the Defense Innovation Unit and In-Q-Tel. They've got these different ways that can maybe compress that multi-year time period that I discussed. Yeah. Planet is a great partner at DIU, and for just that reason, we are constantly exploring those test and evaluation opportunities where governments can at least begin to demonstrate the capability. If nothing else, what it then becomes is good justification for the cycle I described at the beginning. Yeah. So you can have a meaningful set of data that you can then turn in and say, you know, "My budget is X today. Look what I've been able to do with it. Here's the scaling we could get. Okay. You know what I mean? Yeah. Some of it, understanding that government process helps us help them get the budgets then that we want, right? Right. Which are that. Right. That larger pie that then I'll compete like heck against my competitors. That makes sense. Okay. Do you have a view on, on the commercial side, the, you know, the next end markets to really take off or what some of the faster-growing parts of that business could end up being, just given your knowledge of the capability, or is it, or is it sort of out of your purview? I have a view. I'll share it with you. And it does go back to our brief conversation around AI. And so, you know, as I've been exploring, as we've been exploring these foundation models, these large language models, it's exciting to me to find out, to experience myself what they can do with, you know, letters, words, characters, etc. You know, just look at the history of the human language or the, you know, journalistic archive or whatever it is, whatever that corpus is, and apply some amazing, you know, algorithmic, you know, sensibility to it to help predict, you know, what words would most help me next. Add images to that equation, right? You know, or video or, you know, let's face it, at the end of the day, pixels are ones and zeros. They're just a different character, different gray shade. And so to answer your question, what excites me is, you know, how is that going to come together? And at least my answer is, I don't know today. What I do know is it is going to come together. And I guess from a Planet point of view, what I think's most important now is how do we set ourselves to be both, create the baseline that is, if you will, strong enough, but also agile enough to deal with, since we don't know the answer, the direct answer to your question, we need to be ready to move left, right, center quickly. And so I'm confident, you know, if we were to speak, you know, a year from now, there will be developments that I had no idea were coming. Okay. And, perhaps the company didn't know were coming because, again, it's happening outside. But what excites me is how those two things are coming together. Mm-hmm. I mean, as we speak. And again, it goes to the core of who Planet is. We're agile at our core. I think that agility is what's gonna serve us most well here in this period of, you know, quick changes. Agility. Yeah. Interesting. Okay. We just have a minute or two left here. I, I wanna give anyone in the audience here a chance to ask a question if anyone has any. Yeah, just right here. If you could just wait for that microphone. Thank you. Thank you for doing this. Could you talk a little bit about privacy laws? Mm-hmm. I'm sure that's come up a lot. And then secondly, just, you know, there's obviously been a lot of activity, with Starlink and some of the other constellations. I just wondered if you had, any sort of holistic view as to how the communications market might evolve and how that's gonna impact the terrestrial market. Sure. Thanks. So first, on the privacy question, that's another core value, right? Again, Planet exists as a company to use space to make better decisions while respecting that core value, right, of our core principles. And let me remind you too, especially the imagery I've been speaking about today, we are not seeing people. We're not seeing individuals. We're not tracking at that level. These are grosser level movements. Now, can any technology be misused? Of course, it can. And we're well aware of that. We work hard to ensure our customers what the licensing, what are the use cases they're using our data for, and how do we follow up on that? So we're both diligent on the front end about who we work with and how they use our data. And likewise, we track that through. So we take it all very seriously. On the broader question, look, I wanna spin it positively. I shouldn't spin. I wanna say it positively 'cause I mean it. Meaning, constellations such as Starlink open up a way for us to deliver value that we just quite couldn't on our own. Again, I used to live in a world where, you know, you'd capture an image. You'd literally have to wait for the satellite to move over a ground station. So that there's some delay. You would downlink it to that ground station, right? Then there'd be more delay in process and transfer and whatnot. And in a world in which I lived in then and still care about now, timeliness was quite critical. So that was a long way to say I love Starlink, okay, because it provides that mesh, you know, net, on top of it. With respect to the competition piece, I prefer to focus on let's get the pie as big as it can. And then, you know, then just lean into that, you know, good old, you know, competitive market. And I think we're, we all get better that way. Thank you. Okay. With that, we're out of time. So we'll wrap up there. Robert, thanks so much for being with us. Thank you. This was great. My pleasure. Yeah. Thank you.