Hello, and welcome to Needham's fifteenth Annual Media and Technology Conference. I'm Ryan Koontz. I cover the comm tech sector here at Needham, which includes cloud communications, broadband networking, and satellite operators as well, the satellite ecosystem. Really pleased to have joining us today, Planet, who's a leading provider of, daily data and insights about planet Earth. And I'm particularly thrilled to join Robert Cardillo with us today. He's the Chief Strategy Officer and Chair of Planet's federal subsidiary. Certainly one of the, my more fascinating guests I've ever, hosted. And he's leading what's clearly the fastest growing resilience, resilient business segment there at Planet. He's also had new responsibilities extending to international, I believe, recently.
His background is not that of a typical tech exec, having started his incredible career as a junior imagery analyst at monitoring the Soviet Union, working way up through government responsibilities to delivering the Presidential Daily Brief for four years under President Obama, and becoming the sixth director of the National Geospatial-Intelligence Agency. Welcome, Robert. How are you?
Oh, thank you. I'm wonderful, Ryan. It's great to be here.
Awesome. Well, I'll lead Robert through a fireside convo here, and we have, we're also open for Q&A, if you'd like to submit those via the webcast portal. Keeping in mind that Planet's in their quiet period and not gonna be able to discuss financials or any forward-looking comments. You know, Robert's expertise is mostly in their defense and intel side of things. So with that, you know, what a unique opportunity for us to learn from you, Robert, about geospatial intelligence. Can you maybe speak, just start with, you know, where you think the industry is headed based on your history in this space, so to speak?
It's quite a fascinating time, I think, and Planet's in a very unique position to capitalize on some strategic shifts in
Yeah
... geospatial intel.
I'm happy to, Ryan, to talk about where we're going, but I think it would be useful for the audience to... Let me give just a little frame of reference for who's presenting, what my background is, and biases, and perspective.
Sure.
But I'll quickly get to the future.
Yeah.
So literally, about four decades ago, I wandered into this profession the only way you could in those days, kind of blindly, because there was no open, you know, certainly no commercial application from space. It was all government-owned-
Right.
It was all government-operated. It was highly classified. It was very specific to the task in the 1980s, which was a major confrontation in a bipolar world between the United States and the Soviet Union. And so people will be familiar with the Space Race and-
Right
... all that that entailed. And I came in and joined that merry band, and as you mentioned in your intro, became actually a photographic interpreter. I'm that old. I was even there before it was called imagery, which meant kind of what it sounded like. You know, we used to drop buckets of film from space. I kid you not, which is an amazing engineering feat when you think about it. How are you gonna get film back from space in a way that's useful? And it included airplanes with trapezes on the back of them to catch the falling buckets over the Pacific Ocean. Again, just huge kudos to those wizards who imagined such a world.
Having said that, you know, midway through my career, so around the turn of the century, there became the advent of what we now call commercial imagery, right? These, this, these are, you know, you know, you know, U.S. and international. France was and is a leader, for example, in that industry, that began to pursue non-governmental markets. And, you know, you can imagine many: agriculture, insurance, supply chain, logistics, et cetera. Environmental obviously became more and more important as it is today with ESG monitoring and greenhouse gases, et cetera. So, midway through my career, I'm still in the federal government, but now I'm trying to figure out, well, how do I work with these companies that aren't in the government?
And again, frankly, it was a huge learning curve for the government, and I'll speak to it today. It still is in some ways. But the good news is, the U.S. government made a decision, it's called a Presidential Decision Directive, that declared it's in our U.S. national interest that the U.S. commercial imagery be competitive worldwide, right? 'Cause that's economic growth, those are jobs, that's advancement, et cetera, and that's obviously a component of U.S. national security. So the U.S. government, you know, when they set up those objectives, there's a funding process for that as well. And when I was in government, I actually managed what is now, and I'm quite sure about this statement, what is the largest commercial imagery contract in the world, and it's called Electro-Optical Commercial Layer.
That's amazing.
It is now managed by the National Reconnaissance Office, but a very, very large contract, 10-year contract. We're just starting the third year now. Three companies were awarded as primes, Maxar, BlackSky, and Planet Labs.
Yep.
But that's just the frame of reference. So now let's get to your question: Where are we going? So that, you know, if you think of that contract and you think of that government interest, think of it as fuel, right? That's the government saying, "Hey, I need more fuel for my ecosystem. I need to understand the planet. I need to be able to, to assess changes and their meaning with respect to national security questions and potential threats and opportunities." Where we're going... Oh, and by the way, this, that fuel will always be needed, so please don't take my answer as, you know, you can forget about the fuel. You always have to have fuel for the system. But where the government's going is on the other side of that equation now...
And more and more, what we're seeing now is the government, and mainly in defense and intel, but I think this is gonna broadly span other departments as well, is the market for answers. Because let's remember, you don't really need an image, you really need an answer, right?
Mm.
We've used the image for a long time to get to the answers. So there's some really exciting opportunities that are both here today and growing tomorrow that, along the lines of... So at my old agency, the National Geospatial-Intelligence Agency, there's a contract called Economic Indicators Monitoring-
Hmm
... which is phasing out. It still exists, and it's being succeeded by a contract called LUNO-
Mm
... being broken up into As and Bs, and that's under competitive source selection as we speak. Admiral Whitworth, who's my successor there, just announced last week at the GEOINT Symposium that the combined total now for the—they call it LUNO A and LUNO B—over the next five years is $490 million.
Wow!
Now, that's real money, even in the government still. I will say as a director who started EIM almost eight years ago with a $5 million investment that I had kind of at the end of year, you know, the budget was closing out.
Yeah.
You turn to the director and they say, "Hey, boss, we've got a little bit of money." Now, I know $5 million is more than a little bit, but the government, it kind of rounds out some edges here. But I kicked off the contract at EIM going for those answers, and I just couldn't be prouder now to, you know, again, hear Admiral Whitworth say $500 million.
Mm.
So a couple of orders of magnitude in six, seven years. Now, I'm not telling your audience, I know that that's gonna continue, and you can just scale that out. I mean, the government works in mysterious ways sometimes.
Sure.
But to me, and I'll finish here, Ryan, this... What excites me is that movement towards the- to the outcomes and the output side of the equation.
And LUNO is for to procure the kind of tools that they want to. What are they asking for in LUNO?
No, they're asking for answers.
Right.
So, and again, everything I'm about to say is hypothetical, 'cause there are no LUNO contracts right now.
Sure.
I'm pretty confident there will be things like a LUNO competitive opportunity for maritime activity.
Mm.
It'll give you the region, and it'll give you some specificity, specificity, we're interested in ships of this type or this size, and we want you to report them with this accuracy in these timelines. All right? And so then companies would bid and say, "Oh, I can provide you maritime data and tracking, and information with this accuracy and these timelines," and the government will select,
Wow!
So, think about of categories of information that the government's interested in. You know, you could think of, you know, economic activity like trains and truck movement. You could think of-
Sure
... roads and buildings. You know, construction could be one as well.
Are these classified, Jim?
No, no, no, no. That's... No, that's, that's the exciting part now.
Yeah.
Well, obviously, when I began my story, it was all classified, right? But-
Sure
... and let's face it, obviously the government still operates in classified environments, but this is an unclassified open feed, which, by the way, is perhaps not as appreciated as it might be to the audience. Because, you know, we live in an unclassified world mostly, right?
Yeah.
And we interact, and freedom of information, et cetera, et cetera.
Right.
In government space, while... Look, I had the privilege of using, you know, government-provided information and intelligence, it would have something stamped on it, right? It's either secret or it's top secret.
Mm.
Once that it got that, it became very hard to share, right? I could only share with people who had that same clearance.
Yeah.
It really got hard to share with allies, right?
Mm-hmm.
You know, you know, we're doing a relief operation, you know, in Asia or something, and it's-
Yeah
... 18 countries are participating. Well, I can't use that secret imagery because the, you know, it's not shareable. So not only is it unclassified, which, to answer your direct question, but it's, it makes it much easier to share, on the other end.
Fascinating. And an amazing position for Planet to be in, for that opportunity. Can you give some maybe some examples of, you know, recent... I mean, Ukraine obviously stands out, but maybe you have some specifics you can share about particular projects, for your, defense and intel, clients that Planet has, you know, publicly participated in. I do recall seeing, you know... You guys do a great job of branding some of imagery when it goes to the media, but maybe you can highlight a few really important, outcomes or, you know, data collection that you were able to, to bring to your, your customers, your government customers.
Yeah. I'm happy to, and I'll start with Ukraine. You brought it up. It's, you know, obviously a tragic real-world event.
For real.
But if, but if you go back now, what are we in the... We're unfortunately in the 26th, 27th month of this war.
Wow.
I almost said Soviet invasion, so Russian invasion. But if the audience will remember the run-up to that, right, when there was a lot of threats being made, and there was a lot of posturing about potential operations, the U.S. administration, the government and allies actually used a lot of the commercial imagery capability, to include Planet, to really provide some transparency around that question: Will Putin invade? Will he not invade? What Planet and again, you know, many commercial components were contributed or contributed to that outcome.
Sure.
The way to highlight kind of what Planet was able to do is because Planet has what is still today a unique global capability to do a daily scan.
Yeah.
So it uses roughly 200 very small satellites that don't task or point, they just scan as they go in their polar orbit, and they. And they've been doing that now for seven years, so there's a seven-year now archive of the Earth's land mass. Well, the benefit of that approach is that you image everything. Now, I need to remind, it's electro-optical, so it doesn't work at night, and clouds do get in the way, but other than that, it images everything. And turns out that the day before what became the actual invasion of Russian troops into Ukraine, President Putin had made an announcement that this was all an exercise, and he was redeploying the troops home, right?
Yep.
On that day, Planet imaged a what's called an engineering bridge. Think of it as a pontoon bridge from Belarus into Ukraine. It was in, quite frankly, in the middle of nowhere. It was not a place that we would think to go look at, but because the daily scan is looking everywhere, that was caught. Now, that bridge didn't prove that the invasion was tomorrow, but it certainly questioned whether or not that deployment that President Putin announced was credible. And Planet's very proud, along with our other commercial partners, of that kind of transparency that we can add to just-
Yeah
... understand what's happening.
Yeah.
Then, unfortunately, once the war began, Planet has been quite proud of being able to contribute to a better understanding of that threat.
Mm-hmm
... to Ukraine itself, obviously to the U.S. and our allies, about, you know, the status of the war, where the next threat could be coming from. And remember, too, sometimes people just like to... or just imagine, you know, kind of the front line of troops, and you've got tanks, and, and, and missiles and whatnot, which obviously are the, the key hardware. But frankly, a lot of the war, the important part is the supply chain. You know, factory, production levels, right? And resupply, and shipments. And again, I go back to the global scan. What Planet is proud of its contribution is that scan's happening every day.
We'll talk about it more later, but with the huge advance in compute and the huge advance in computer vision, especially AI-generated computer vision, the ability to pull out rather nuanced information from that dily scan is really accelerating the value proposition. So that's kind of the Ukraine case.
Yeah.
The other areas that we're quite proud of is the audience will be aware of some recent natural disasters.
Yeah.
I know a lot of them are part of the climate change and climate crisis induced, but they, you know, either the rash of wildfires and extreme weather conditions. The ability to provide the baseline before the event-
Right
... is critical for the first responder to decide which roads are open, you know, which bridges are down, how do I get, oh, and by the way, where are the refugees? I'm going back also a couple of years, massive earthquake in Turkey, and because we had done the scan across the whole country, we were able to inform their version of FEMA where the water needed to go, where the tents needed to go, because they had a snapshot immediately of, well, because of not just the immediate damage to cities and structures, people were egressing those because they weren't safe.
Yeah.
But the government didn't know where the people were, I mean, not, not in any holistic sense. And again, the daily scan is a way to do that. And lastly, you know, there's a supply chain. We're able to, if the interest is in something like a potential threat from China across the straits to Taiwan-
Yep
Obviously, that's a major point of interest, right? That's a... It's a flashpoint, and not just for national security. Global economy is riding on that calculus, of course. What Planet's able to do, again, is not just those in-close, what's the port activity, what is the airfield activity? Which obviously are key indicators. But what could be occurring days and weeks in advance on increased petroleum production? Or imagine a stock up of medical supplies. You could imagine different indicators that might tell you that we're moving into an area of increased, you know, risk, et cetera. And again, as a 40-year intelligence officer, I'm very loath to say, you know, "You can do it," say anything with 100%, 'cause you can't, right? The world just doesn't work that way.
But what I like to say is, you know, are we able to scan the horizon and identify threats before events dictate, and just give a little bit more time to the decision-maker? And to me, that's the sum up of the value proposition.
Yeah, and that's where the value of that archive really comes in, because you can look back in history, and you can see change.
No, I appreciate you saying that, because I rather quickly skipped over it. I mentioned the seven-year archive, but again, with compute and computational capability now, you really can, and I'm gonna turn my fingers like I'm turning a dial. I am not, you know, I don't write code, I just thank the people that do, so I'm not trying to say it's that easy, but you can really reverse time, right? And, and-
Mm-hmm
... for example, say we're, quote, "surprised" by something, and it could be an economic surprise, it could be a security surprise. Oh, when did that start? Okay, let's go back a year. Let's go back two years and see what was occurring, to do two things: one, it gives you now kind of a pedigree, so you can either... Oh, go back to Ukraine. There was an unfortunate incident early in the war where the Russians had occupied a town-
Yeah
... and then the Ukrainians recaptured it. And then there was the question about war crimes and, you know, who had committed them. Well, you know, again, you can't be dispositive because you're still from space and whatnot, but it's you can help people like The Hague as they're doing the reviews of complicity-
Sure
... about who was doing what when, you know, with that, with that time machine. So it's a... And I gotta tell you, I have been interested in the archive for years, both in my government and now obviously private sector, but it really has been the past 12 months that it's been unlocked in a way that makes it, you know, really come to fruition.
Yeah.
It's a very exciting time.
Very exciting. Maybe just shifting gears to numbers real quick, just in terms of some numbers your segment's put up. Really strong growth, I mean, pushing on 30%, I think, the past couple of years?
That's correct, yep.
Really impressive. Can you kind of walk us through that?
Yeah. Here's... Look, I would break it down this way. And again, kudos, you know, to the founders who had the vision, originally some 12-14 years ago, based upon their NASA experience. So our founders came from NASA, had great, you know, experience and expertise in building very big, very complex and very capable, but one more thing, very expensive, satellites, right?
Yeah.
They said, "Hmm, wonder, wonder if we can do this, you know, in a slightly more economic and efficient way." And I'm gonna raise my smartphone, which came out about the time that they had this idea, and they go, "You know, there's a lot of components in this smartphone that we might be able to just say, 'Thank you. Let's just-
Mm-hmm
... put those.'" So they built... And by the way, that's about the size of the Dove, so very small scale, satellite with, quite frankly, originally had a smartphone in one end, right? Just to see if it would work.
Yeah.
And again, I'm way oversimplifying the complexity of what they achieved, but getting to your question, to me, that kind of agile tech approach is critical to the growth you describe. Because almost every quarter, Planet is relaunching and refreshing that on-orbit architecture.
Mm.
So, you know, I think it's over 500 satellites have been launched by Planet now, in their history. There's about 200 on orbit right now.
Mm-hmm.
But, you know, 20-30 or so go up each quarter. Every one of those satellites then has the latest chip, right? The latest comms device, the latest sensing, you know, improvement, et cetera. So that obviously is of value. So you can turn to a customer and say, "No, no, it's not two-year-old technology, it's not five-year-old technology, it's two-five-month-old technology," and so that, that's a discriminator. The other thing too is that-
I used to work on a decade at a time, if I recall, like-
Oh, please-
... concept to.
Please, you're being generous to the government. Sometimes it took us... Because, frankly, we would do a study for a few years to think what we would need, then we would compete it with industry for a few years, right? So now five years have gone by before industry even got the award, right?
Yep.
And then you can imagine, at least another five, before it got on orbit. Having said that, Ryan, I have to say, those people are heroes too, all right?
Sure.
It's an amazing application, but it's a different value proposition. But to your question, when you're dealing with people who have economic questions and environmental questions, right, and sustainability questions and security questions, they have to have that confidence that you can keep up, quite frankly, with whatever the challenge is. Challenge could be Russian aggression, challenge could be deforestation, the challenge could be supply chain management, et cetera. And what I love about Planet's approach, and it has sustained that approach its entire time. More recently, and here's where I think we've really been able to generate the kind of numbers you referenced, is we're doing a much better job with partners now.
Yeah.
I'll give you one example. Last November, Planet was proud to compete and win a contract with the U.S. Navy. It's actually the Navy Information Warfare Center Pacific. And basically they said, "I need this maritime domain awareness capability, so shipping, traffic, monitoring, et cetera, but I need it in the South China Sea." Okay, so pretty difficult area, and I mean difficult because of how busy it is and how tense the region is. "Oh, and by the way, I need it for the U.S. Pacific Fleet." So to me, it's about the most daunting area of the world, and probably one of the most demanding customers, thankfully, right? The U.S. Pacific Fleet.
Mm.
Planet won that contract. Now, we won it with a partner called SynMax. They create the algorithms that run on top of our daily scan-
Right
... and basically pull out the detections from our scan, right? Can't do it without the fuel. Remember, the fuel's gotta be there. And in this case, we found the application not inside of Planet, right? This was something we found at our partner. And now we're providing that throughput. And this is a seven-figure ACV result, and it is again an area where I strongly believe if we can do it in that region for that customer, this right should be able to be exported-
Yeah
... and expanded.
Yeah.
So obviously we're looking for those opportunities as well. But that's a couple of reasons that I think have driven the kind of growth you've seen.
That's great. You know, I had a chance to meet the SynMax team at your customer event, it was the year before last, the first time they were there. And what's really interesting, I think that investors find curious, is that that technology came originally from a hedge fund. It was developed for a hedge fund to assess, I think, natural gas production or what-
Right
... some of the big energy commodities. And they spun the technology out of the hedge fund, and now are building a company around this AI detection capability, and going after dark vessels at that time, and it's great to see it turned into this contract all the way through.
It's nice to see hedge funds getting a little good PR, right?
Yeah.
Look, you know, and there's another example that I like. You know, there's a partner with a piece of software, they were called Synthetaic, they've rebranded to RAIC, R-A-I-C.
Okay.
They were born... Again, software firm, they were born out of radiology, right? How can you help doctors do better radiology exams? And makes great sense, but what is an X-ray but an image, right?
Yeah.
And so if you can, if you can discriminate pixels and find anomalies there, you can do it. So I just love those kind of stories because it's those kind of just partnerships that I think are part of not only of the scale that we've seen to date, but what's ahead of us.
Well, it's a real amplifier on your capabilities of your data that you have, and layering on that cap-
Yeah
... So maybe just following that up on, you know, maybe stepping back, from an introduction of AI, how do you see that affecting your business, the product today, and how do you see it evolving in the future? And that's a loaded question, but even in the next, like, I'm talking the next 24 months, 'cause I think the sky's the limit on AI. It's hard to tell where it's gonna take society. But within your business lane, I think incredible things are happening.
Yeah, I love the question. I'm trying to be careful in a couple of ways. One, I don't wanna go on too long, 'cause I'm just-
Uh-huh
... I'm overexcited about the possibilities here. But I guess, let me put it this way, and again, please, for the audience, I'm not the technologist. If I misstate how it actually works, I apologize, but this is how I resonate with what I think is the compelling potential for large language models, is that... And how that translates to how Planet can contribute and scale is, you know, again, these wizards have found a way to write algorithms and derive from the advancement in compute, a way to extract useful information. And again, you gotta be careful with everything, right? There's left and right bounds, and there's hallucinations and whatnot. But generally, useful information out of a corpus of letters, right? Not even words, right?
They're literally trying to figure out which letter is best, you know, most logical to follow the next one, in order to address the question or the challenge. I apologize if I'm, you know, misrepresenting the science underneath it, but in Robert's mind, pixels, like letters, are ones and zeros at their base case, and they come together to form an image that is friendly to, you know, human interpretation, because this is how we experience the world.
But if you think of, you know, spectral bands within, you know, our vision, and you think about near-infrared and shortwave infrared, and you think about, you know, the value of this color band and what it might tell you about either the health of that plant, the moisture in that soil, or the camouflage paint on a tank, right? I mean, many things could... But for a human to do that, it's very, very difficult, right? And even if it's possible, it takes a long time. And what excites me about this LLM approach, and now the move to multimodal, so don't just submit a question with text, but submit two images, right?
Yeah.
From two different time points, and just-
Yeah
... tell me what's changed, right?
Yeah.
Oh, by the way, don't tell me everything that's changed, because that's gonna be too much. Just tell me what's changed with respect to parking activity, right? I wanna know if there's more or less cars. I wanna know, you know, what days of the week or what times of the day. I wanna know what's changed with respect to a construction activity over time. And what I like to say, because I used to employ about 5,000 humans when I was at NGA, that did that analysis for a living.
Yeah
... that we need to become much more comfortable with letting the machine and that fuel answer three questions: what, where, and when. Because they're quite good at doing that. Now, they're not perfect, right? And we obviously need to put some error bars around these and do checks and reviews. But if you can get there, save the human for the two really more difficult, and I think more important questions: why and what's next?
Mm-hmm.
And again, that can be from a national security point of view, it can be for disaster relief point of view, it can be from a, you know, food yield point of view. How do I make sure that we, you know, get the best crops given these conditions?
Yeah.
But going back to your question, I just love the fact that because of this kind of mindset about bringing it all together, and I, you know, used the term corpus before. So again, as I understand this, this wonderful competition between the big LLMs now, a lot of it has to do with, well, you know, I've got this corpus, right? It could be Facebook, right? You know, and I've got this. It could be Google searches, and right. Both of those have discriminate value, right? They have... You know, your fuel is better, different, et cetera.
Right.
What I love about Planet is there's a corpus of imagery, seven years and growing, every day gets another layer on it, that to me has got to be, I guess, pun intended, a rocket fuel, okay, for the advancement of how these multi-models will work. Now, having said all that, Ryan, I think we're at the beginning of that exploration. I think your 24 months is probably too far. I think, you know, I think we will be learning, you know, weekly and monthly here-
Yeah
... and we'll be discovering new applications. But it's hard to... I need to be careful, but, you know, it's hard to limit where you think that could go, and so, just very exciting point in time.
Yeah, it just feels to me like, you know, the old way of doing things required bodies, right? And that was kind of the limit to the consumption model, was, you know, how many people you had to read and compare and, you know, these sort of things, and go identify what that means. And now, with AI, it's just it really simplifies and accelerates the consumption model.
Yeah, I rather, rather famously, I think it was 2017, I did a public speech at a symposium, and I just had my agency, NGA, I said, "Hey, just go and add up every image we got today," right? "Just add them up," right? Now, many of those were classified, but a lot were commercial. And by the way, some were taken for unmanned vehicles, some were taken for airplanes. But they, they said, "Okay, boss, it's, here's the stack of imagery we got today.
Mm.
I said: Okay, put our traditional exploitation model, meaning Robert Cardillo squinting at an image and telling you what's on it-
Yeah
... tell me how many people I would need to work through those, that amount of imagery. The answer was six million.
Wow!
six million humans were needed.
Wow.
I mean, I knew obviously we didn't have enough people, but it became a great way to think about or kind of a bracing way to think about, you can't pursue it that way, right? You have to get the machine out front. And by the way, let me say, I'm a big, big believer in what I call human on the loop, right? So I'm not saying just turn it over to the machines and let them tell us, you know, what's happening. You do need to have expertise around it. You do need to, you know, be watching for those left and right bounds. But just an inordinate amount of potential's in front of us, you know, as we unleash the power of that, of that machine-human interface.
Wow.
Yeah.
Incredible. And maybe just finishing up here, can you maybe tell us about what some of your future work you're doing to take some of the learnings you've had with the U.S. government to other governments worldwide, and kind of what your role is there?
Yeah
... and how you see it evolving?
So two things. One, you know, I mentioned the maritime domain where, you know, the SeaVision win that we had with the U.S. Pacific Fleet. It seems clear to me that there, there will be scaling opportunities,
Mm
... because very few countries, Switzerland might be one of them, that don't have a maritime domain, you know-
Mm
... some sort of component. And look, it doesn't have to be national security. There's very much a commercial component to, you know, to traffic and to safety and, and to, and to navigation, et cetera. So I'm quite optimistic there. On, you know, on the... I also think on the analytics front, there's opportunities because, you know, not too long ago, if we were out with, especially a you know, a country that perhaps, you know, wasn't at the same level of technology development and education, et cetera, you know, building a ground station and/or delivering a large amount of kind of raw imagery and pixels to them-
Yeah
... really being like: Uh-oh, now I've got another problem, right? Thank you for all this, but what do I do with it?
Mm-hmm.
And not every country, you know, can afford, right, to build the ecosystem that then goes along. So the ability to now to go to allies and partners and talk to them about the other end of that equation, right? You know, what are your objectives? You know, whether they be economic, whether they be security, transportation, insurance, et cetera. And then let us work with both what we bring in-house, because, you know, Planet obviously builds applications that run on our imagery source, but let's also go find the partners.
Yeah.
Speaking of partners, the other thing, even though we've kind of stayed in the Planet lane today with electro-optical, some very interesting use cases when you expand it to synthetic aperture radar, right? So-
Right
... you know, whether it's the Umbras or, you know, Capellas or ICEYE of the world, think of the complementary activity between, okay, I've got the daytime cloud free recovered. Well, it's nighttime, it's cloudy, you know, having that interface. And then, you know, now with commercial radio frequency, HawkEye 360 being the U.S. leader in that regard-
Mm-hmm
... I guess what I see going forward, Ryan, are more of those kinds of partnerships where you take a, if you will, a tailored or a packaged solution-
Well-
Not just a picture, not just a signal, not just a radar return, but "Oh, I now have confidence," right? That I about the activity. I have confidence about the location. And really, I've always thought that the intelligence profession, you know, from whence I came, was really all about that. Because you just wanna give the decision maker an increment of confidence when they have to make that decision. And then, you know, life happens, and then you refresh it, and you give them more information so they can make the next decision. And to me, what excites me going forward is both, we've talked about the compute and the computation, but I also think that the partnerships are gonna really help with this, with the global market as well.
Yeah. Sounds like tremendous, synergistic opportunities with these partners.
Yes.
You know, together with other partners, you get it, the... And so again, this consumption model eases, I'm sure, to kind of get to the answers-
That's right
... that particular customers want in a real-time way.
Mm.
It's really exciting.
Yeah.
Um-
No, I just want outputs on my screen, right?
Right.
Now, obviously, I wanna have confidence in the output, so you need to give me some, you know-
Uh-huh
... some increments of confidence in there, but just outputs.
Yeah, you can double-click on it. It's there if you wanna see it.
Well, well, that's right, too, because, you know, you know, not everyone needs the image, as I said, but you might want it to be, quote, "sure" or more sure.
Mm.
Thank you for the spreadsheet, Robert. Planet, I'd like to see that image as well, right? Okay, it's right here. You know, scan it, download, available, et cetera.
Excellent. Well, it's really great to have you today, Robert. Anything you wanna say in closing up?
One, thank you, Ryan. Always appreciate these opportunities. Just I love chatting about, talking about not only where we are, I'm just couldn't be more excited about where we're going. And again, like I said, just given the history of my arc, to be able to have, you know, lived and enjoyed and learned, you know, from those early days. And that's, and I have to say, I've earned this gray hair. That's a 40-year arc. What's in front of us, you know, four months, you know, 14 months, 24 months, is just crazy exciting. So-
Yeah
... it's a great time to be at Planet. I look forward to having our next conversation, Ryan, and we can review those next sets of accomplishments, but just a lot of excitement ahead.
Look forward to it. All right, Robert, thanks. Thanks for joining.
Thanks. Be well.
You too.