Welcome back to those in the room and anybody on the webcast. I have the pleasure this afternoon to welcome... Oh, my God, my brain is doing a complete brain fart. How do you pronounce your last name?
McGeown.
Okay.
Irish.
Yeah. So Chris and I have known each other for a long time, and I've never articulated his last name out loud before, so apologies for that.
Thanks for everything.
So, I'm welcoming to the stage Planet. Chris is Vice President?
Yeah.
Of Investor Relations.
Yep.
We're gonna go through Q&A here. At some point, we'll open it up to the room to see if there are any questions from the floor. You all are in your quiet period, so I will avoid asking questions about the numbers.
Appreciate that.
We'll stick to the narrative around the story.
Great.
Okay, great. So look, I think, I think a nice place to start with these kinds of conversations, particularly for those that may not be very familiar with Planet, is to ask a really big-picture question for you.
Yeah.
which is, you know, what is the problem that the company's trying to solve?
Mm-hmm.
How do you go about solving it? And you know, if you are successful in solving it, kinda what does the overall market look like for you all and kind of what the go-to-market strategy is? So this is kinda like, you know, top question here, get a little brief description of what Planet is, but kind of in that context.
Sure. Sure.
Yeah.
Yeah. So we were founded with the mission to image the Earth every day, to make change visible through our imagery and accessible and actionable. And so our... We were founded in 2010 by a group of NASA engineers and scientists who were looking at the space industry and saying, "You know, there might be a more efficient and faster way of building and launching satellites.
If we can leverage the history of the space industry, all the knowledge that's built up there, and also leverage advances in other industries, particularly Silicon Valley, strapping Moore's Law to space." And so our founders set out to miniaturize satellites, to build them much lower cost, and to launch lots of them up into space to image the world every day, with the vision that this sort of dataset, a dataset that grows daily, an image of the world captured on a daily basis, would be valuable to customers across industries, across government and commercial markets. And so that's when we were founded in 2010. That was the vision. And we captured our first light, our first image from a spacecraft, in 2013.
So we successfully miniaturized the spacecraft down to the size of a shoebox or a loaf of bread. We built that satellite for a fraction of the cost of a traditional satellite. We got it up into space in just a few years, and we actually started capturing imagery. By 2017, we were imaging the Earth every day, so we accomplished what we called our Mission One, and that's where we started building this archive of daily imagery of the Earth. That was a landmark year for us. We also set the world record at the time for the most satellites launched on a single rocket, 88 Dove satellites on an Indian PSLV rocket. And we also acquired the SkySat assets from Google, and so we acquired satellites for high-resolution imagery from Google.
These satellites are larger, about the size of a mini fridge, compared to the Dove satellites we built that are the size of a loaf of bread again. They capture imagery at two different resolutions. They're very complementary. Fast-forward to today. We went public in 2021 on the New York Stock Exchange. We have over 950 customers across commercial and government. We're about 1,000 employees. Trailing 12-month revenue was about $250 million, and we have $350 million of cash, cash equivalents, and short-term investments. So that's the founding vision we got today. We are today.
Okay, great. Maybe we could talk a little bit about some of the use cases,
Sure
...for the imagery. So you mentioned in 2010, there was a vision to be imaging the Earth every day. Thought that that data would be useful to the world.
Mm-hmm.
So maybe talk to us a little bit about, you know, how that imagery has been useful today. What are some of the use cases that you like to highlight as being, you know, both successful for your customers, but as well, you know, drive- help drive the financials of the company?
Yeah, definitely. On the commercial side, so the largest sector that we serve on the commercial side is the agriculture sector. And so we're aiding in precision agriculture and helping large ag companies optimize the inputs that go into the field, as well as optimize the output from the field. So, optimizing seeding and fertilizer that goes into the field and then managing the health of your fields, and this is on a global basis. These are large customers, like a Bayer or a BASF. Monitoring the health of your field through the growing season so that you can identify if there's ever risk of crop disease or infestation. You can act quickly, and you can also optimize the timing of your harvest.
In the insurance sector, we have customers like Swiss Re or AXA that are using our data to provide drought insurance, parametric insurance... to customers in the ag sector. So looking at historic occurrences of drought using our data archive, identifying the frequency of drought, and then being able to predict the likelihood of drought occurring on a go-forward basis, so they can build insurance products for customers around that. Shifting over to the government side of the business. So in defense and intelligence, it's about monitoring broad area plans. And so understanding how change is developing in a national situation, to understand where things are moving, how things are changing over time. It's about searching, scanning, and monitoring and identifying new threats.
And then in the civil government sector, it's about regulation, permit enforcement, and also disaster response. So we have a very diverse customer set that we're serving. This daily image of the Earth captured on every day is a new capability for humanity that hasn't existed before. So we're creating a lot of new markets and opening up new use cases for the geospatial industry.
Mm-hmm. Okay, great. That's a great segue into one of the questions I think we were meant to cover here this afternoon, which is the go-to-market strategy.
Sure.
You said, you know, you came out as a public company, a few years ago. I think you said '2021, right?
Yeah.
Late, late 2021.
That's right.
had some capital to help drive growth in the company at that point. I think part of it was into the B2B side of the business-
100%.
into the go-to-market strategy, right?
That's right.
And fast-forward a few years now, and here we are at the beginning of 2024. And I think maybe starting sometime second half of last year, you started to talk about some of the learnings from-
Sure.
that initial, you know, investment that you made in the go-to-market strategy.
Mm-hmm.
Hey, now maybe it's time to make some tweaks.
Mm-hmm.
Can you talk a little bit about some of the changes that have gone on with the go-to-market strategy? What were you focused on before? Where are you heading now? And maybe some of the motivations for those changes.
Yeah, 100%. So we've made a number of changes on the go-to-market side. It's really about focus. So, with our direct sales force, we get a lot of inbounds.
Mm-hmm.
There's a lot of interest and enthusiasm for satellites, for the data that we produce only for humanity. Customers wanna, you know, explore what is possible, the art of the possible. But that doesn't always lead to the you know, landing accounts quickly and expanding those accounts over time. And so we have focused our direct sales force on those vertical markets where we see the most opportunity, where we see the most repeatability, where there's very clear customer ROI, and that's primarily the three core markets that we mentioned previously: defense and intelligence, civil government, and agriculture. So we want our direct sales force focused on large customer accounts in those sectors. For some of the more emerging sectors, that's where we are leveraging our partner network, the network of partners that help to solve customer problems.
We, you know, we can't develop all of the analytic solutions in-house to solve every customer problem, particularly in some of the verticals that are still in the early stages of adopting geospatial solutions. And so that's where we can leverage partners to help bridge that last mile to customer value. We've also acquired a platform called SignalHub from a company called Energize that is providing the foundation for a self-service channel to serve small customer accounts. So there are lots of customers that come in and wanna spend four figures or five figures with us, and that's probably not the best use of our direct sales force's time, but we wanna be able to serve those customers.
And so having a self-serve platform where customers that it's lower touch, doesn't require a sales rep, where they can go and access the solutions and data they need, and with very clear pricing and packaging, that's how we wanna serve that market. So those are some of the go-to-market changes that we've made in the last couple quarters, and we're also just more generally simplifying sales processes and streamlining them.
Mm-hmm. And maybe if you could talk, you know, about any early successes that you might have had since this go-to-market strategy was implemented. I'm not sure if you've made any particular announcements that you wanna highlight to everybody, or I know you're in your quiet period, so you can't talk about numbers. But just any kind, any highlights that you might have on or positive proof points on how that's going?
Yeah. So last quarter, we talked about some of the large accounts that we, large wins that we had in some of those core vertical markets. So that's... We saw a large expansion with BASF in the ag sector. That's a seven-figure account. That's a large account. We talked about a large Ministry of Defense large contract that we won with the Ministry of Defense customer. These are the examples of landing these large seven and sometimes eight-figure deals that are driven by our direct sales force in our core markets. We also on the we've done a lot of great work with partners, including, like, an ERM.
So ERM, Environmental Resources Management, they are a SI in the sustainability space, and they're helping us to go after opportunities together to solve problems around things like: How do I comply with EUDR? And so making progress with those types of SIs that can help us address those issues that require an extra partner to solve that last-mile problem is very exciting for us. And EUDR, as you know, is a large opportunity for our business.
... I was gonna say, for the benefit of those in the room and on the webcast, maybe talk a little bit about what EUDR-
Yes.
-is.
Yeah. So, EUDR is the European Union Deforestation Regulation that is going into effect at the end of this year, where companies that are importing goods and selling goods into the EU are going to need to prove that those goods or if raw materials or derived products did not cause deforestation in the sourcing of those products. And geospatial location is a key means of proving that you did not cause deforestation. The products that it covers include cattle, cocoa, soy, wood, rubber, and a number of other everyday products that are in and many different consumer packaged goods. This type of regulation helps to drive adoption in the commercial space, where you have not seen geospatial really.
It hasn't been adopted to the same degree that we've seen in the government space yet.
Mm-hmm. So let's see here. If I can remember, you mentioned 900-some-odd customers. Can you remind us of where that customer count might have been maybe a year ago, off the top of your head?
Off the top of my head, no. It's grown quite a bit, in an order of magnitude in the hundreds since-
Yeah
We went public.
Yeah.
So we've added a lot of customers. Just for context, our business today is roughly 70% government, 30% commercial. I think it's actually 42% DNI, 30% civ gov, and 29% commercial.
Mm-hmm.
So it is weighted towards the government, which is the traditional customer of geospatial solutions, but we are driving a lot of adoption in the commercial sector, and that's where we see a lot of long-term opportunity.
Okay. So as we think about kind of growth going forward for the company, the expectation is that the mix of that business between government and commercial will become more equally weighted over time? Or is it they grow both of them equal amount each year?
Yeah. In the near term, we see a lot of growth coming from the government sector.
Mm-hmm.
And we're pursuing a number of opportunities on the defense and intelligence and civ gov side. We have a large pipeline of 7-figure plus opportunities that we're going after, and many of them are government. But longer term, we see a significant amount of opportunity in the commercial sector, and that'll be driven by partners, our partner network, our low-touch channels, the analytic solutions we're building on top of our data, and then also some of the regulations like EUDR, which we mentioned. So yes, over the long run, we would expect our mix of revenue-
Mm-hmm
by sector to be roughly equally weighted, a third, a third, a third.
Right. Okay. You just mentioned some of the analytical things-
Yeah
that you're kind of layering in-
Yep
So, you know, I obviously spent some time in the geospatial world myself.
Yeah.
I think that I heard a quote at one point where the commercial geospatial industry was creating enough data every day that it would take an intelligence analyst 85 years to try to identify all the trees that were taken in one day. 85 years for one guy to sit down and just pick through and figure out where all the trees are and all the geospatial data that's being generated, just by commercial companies, much less what's going on with the government. Along comes high performance computing, learning algorithms that can do that in a matter of seconds.
Yes.
Maybe even minutes, but a very, very short period of time. So, talk us a little bit about some of the analytical tools that, you know, Planet has built, around, you know, the datasets, that you all have. And, maybe paint a picture for those in the room and on the webcast about, you know, what that, what that kind of does for the end user, of it, maybe a use case or two,
Yeah
to demonstrate it.
Yeah, absolutely. So we have a line of products we call Planetary Variables. These are analytic solutions that can abstract away the satellite imagery, and the data we deliver starts to look more like time series data that anyone, any analyst, can interpret. You don't need a PhD in geospatial. That's where we see the data analytics really going. It's, it's making this data more accessible, more usable, usable to the non-technical, the non-experts. Opening up the market to data scientists, to software developers, and eventually to any business analyst. So today we have Planetary Variables for things like soil water content, soil temperature. Those are important for the insurance product we discussed.
Mm-hmm
With customers like Swiss Re. We have crop biomass detection, we have building and road detection, and we recently announced a global forest carbon product, which is really exciting. It has sustainability, forestry use cases, as well as applications for carbon markets. So being able to look at forest canopy, forest structure, and estimate the amount of carbon in a given tree, and then look at a whole forest and understand how much carbon is contained in the forest. Having scientific-grade, reliable data for that is important for supporting carbon credit markets. So those are some of the solutions that we have today. We acquired a company called Sinergise for the Sentinel Hub platform. They have geospatial tools and analytical solutions that make working with these datasets easier.
We just announced that our Planetary Variables, the ones we just are now available on the Sentinel Hub platform. That's just continuing to make the data more accessible, more usable. And then there's AI, which is sort of what you were talking about in terms of taking all this data and making it easier to search and gain context from. The Planetary Variables solutions, you can think of them as training and running models for individual things that you're trying to understand. But with generative AI, it's very exciting because you can feed a generative AI model the data once and then run it to search for anything. So it could be you feed the data to AI, and then you feed it, let's say, the United States, and say: Okay, here's data of the United States.
Here's the archive going back in time. Now, find me all of the wind plants in the US and how they developed over time, or all the solar farms, and how has solar farm development happened over time? And instead of taking months to be able to train a model and refine it to do that, you can do it in a matter of minutes. We, we shared a stat at our investor day where we produce 13 trillion pixels across 8 spectral bands on a daily basis, and we estimated it would take an analyst 7 years to look through all of that.
Mm-hmm.
With AI, you can look through all that in a matter of minutes. You can find that needle in the haystack that you're looking for in a very short amount of time.
Mm-hmm. Talk to us. You just mentioned Spectral Bands.
Yeah.
That might be a new word to the layman in the room.
Sure.
What do you mean by that?
Sure.
What's a spectral band? And why is that important to what your customers need and want?
We think of the geospatial industry as pushing on three axes. It's temporal frequency, it's spatial resolution, and then it's spectral resolution. Spectral resolution, there's the visible light spectrum, the things we can see with our eyes, but then there's all of the stuff that we cannot see with human eyes that's outside of the visible light spectrum, and that's where having sensors that help outside of the visible light spectrum is really exciting. And so we have eight spectral bands available on our PlanetScope fleet. A daily scan of the Earth allows us to look at things like crop health, valuable for the ag industry. We have a future fleet in development called Tanager-
Mm-hmm.
-that will be hyperspectral and have the ability to look up to over 400 spectral bands and be able to see things like methane and CO2, which is very exciting and very important as for sustainability applications and obviously monitoring emissions. So, yeah, that's a little bit on spectral bands.
Okay, so let's think back for a second. We started in 2010 with this vision of mapping the world on a fairly frequent basis. We get to fast-forward to 2017, we're doing it on a daily basis. We are signing up some government customers-
Yep.
in the DNI world along the way. Having some success in the ag and the insurance markets.
Yep.
$250 million of revenue, roughly. You're still burning some cash, which is, you know, something we'll get to here, in a minute, but it... Part of that is driven by the investments that you're making in your go-to-market strategies.
Right.
It's also in the investments that you're making on the fleet itself. Today we've got low-resolution satellites and some higher-resolution satellites, right?
Mm-hmm.
The Doves and the SkySats.
That's right.
Right? So we can take, you know, broad areas, and then we can focus in, right?
Yep.
is the right way to think about it.
Yep.
We've got $250 million of revenue, and we're trying to figure out ways to accelerate revenue growth through adoption.
Mm-hmm.
You know, increased customer adoption. We think that might happen through some of the regulatory stuff you talked about in Europe.
Yep.
Right? DNI, that seems like a really natural place, and so I do wanna double-click a little bit more on what we can do to accelerate DNI kinds of revenue streams in the future. But why don't we talk a little bit about some of the investments the company is making to, you know, move this revenue from $250 million up to something higher, gets the company to EBITDA breakeven and eventually to cash flow. So go-to-market, we've made the investment. We're making some tweaks. We're seeing early success with the go-to-market changes that you've all made.
Yep.
But let's talk about the constellation itself.
Yeah
-and some of the changes that you all are making there. You mentioned Tanager. There's another one called Pelican-
Yep
... that you're working on now as well. So talk a little bit about what Pelican is, what it's meant to do, what you think that's gonna do for, you know, adoption and revenue acceleration for the company, and then do the same thing for Tanager.
Yeah, happy to. So, we have two new fleets in development. Pelican is our high-resolution optical fleet. That will replace the SkySats over time. It's designed for higher capabilities than the SkySats at a lower cost. So better resolution, lower latency, and more revisits, compared to the SkySats. And what a SkySat costs, on an individual basis, between $10-$12 million. That's build, launch, and materials. And we estimate a Pelican will cost between $5-$6 million. That's build, launch, and materials. We just launched our first tech demo of a Pelican satellite. And the fact that we do tech demos is probably sets us apart from many in the traditional aerospace sector, because our cost of satellite is so low, and we iterate so rapidly, we can do things like tech demos to gain on-orbit learning.
So we've been learning a lot about the Pelican satellite through the tech demo that we're incorporating into future Pelican satellites, as well as Tanager. Tanager is our hyperspectral satellite. It shares the same satellite bus as Pelican. So we have a modular satellite bus that can host different sensors. Pelican has an optical sensor. Tanager has a hyperspectral sensor. Tanager is funded by a nonprofit called Carbon Mapper. They have brought together a coalition of partners that includes NASA JPL, Arizona State University, Bloomberg Philanthropies, and the Rocky Mountain Institute, among other partners, with a mission to detect CO2 and methane emissions globally at the point source. These are our two programs, different sensors, same satellite bus.
The Pelican program is about replenishing, increasing our SkySats over time, our high-resolution satellites over time, and there's a broad range of applications across defense and civil government and commercial that we can serve with those satellites. And then Tanager is about bringing a new data set to the market to solve sustainability problems, as well as serve use cases across defense, ag, and also biodiversity. So these are the two new programs that we're working on. We see improvement in resolution and revisit time is helping to drive the high-resolution adoption, the adoption of high-resolution imagery. And then bringing on new datasets like hyperspectral is opening up new use cases across different markets.
Mm-hmm. And, maybe you can, to the extent that you all have articulated, how that ties back to the numbers and what kind of growth rates we would expect,
Sure.
Just to kind of help accelerate. Maybe just kind of walk us through the business case behind all of this that you've, you know, given the quiet period you've articulated to date. How's that?
Yeah, yeah, sure. So it's, it's about, on the Pelican side, it's about continuing to grow our high-resolution business. So we have a strong high-resolution business today. A number of customers there, across defense and commercial, and it's, it's about bringing the capabilities that those customers are looking for, higher capabilities to, to grow those accounts, expand those accounts, and also drive more adoption. On the Tanager side, it's about opening up new markets. So we see a lot of opportunity on the Tanager side, particularly with energy and regulators. If you want to be able to identify point source emissions as a regulator so that you can enforce good conduct around emissions.
If you're an energy company, and you want to monitor your emissions so you can mitigate potential issues ahead of time, this is an incredibly valuable data set for you. So, these two programs are, you know, they're in the development phase right now. The tech demo for Pelican's up, and we're very excited. Yeah.
Tanager, you mentioned some customer funding related to the build of it?
from a nonprofit called Carbon Mapper.
Right. So who, who is the owner of the satellite when it's all said, when it's launched and-
We'll continue to own the satellite.
Okay. And then you-
We're delivering the data to the nonprofit.
All of the data or a certain... They got some sort of SLA to it?
The portion that is-
Mm-hmm.
Yeah, so there's a certain agreement that we have with the nonprofit, and they receive the data that is used for CO2 and methane detection.
Okay.
But we will still be able to commercialize that.
Uh-huh.
And then the data that we capture outside of the spectral bands, it's only a few spectral bands that you need to do-
Okay
for methane or CO2.
Yeah.
We'll be able to commercialize that for other industries, and that's where you start to open up applications in defense-
Mm-hmm.
applications in agriculture, applications in biodiversity.
So it sounds to me like, okay, you've got customer funding on that. You're gonna deliver the data to them once it's operational. Is there an opportunity, to your knowledge, to sell out some of that capacity, or light up customers ahead of the actual launch of the satellite? Or is it one of those things where we're kind of building it, hoping that we're gonna build a case around it?
It's a good question. We actually have an early access program-
Mm-hmm
... for that program with a number of customers across government as well as commercial sector.
Mm-hmm.
So think energy companies, think, regulators that are helping with the development of the—they're providing feedback on the data. We have synthetic data that we have produced for the hyperspectral imagery, as well as data captured from airplanes, so aerial data.
Mm-hmm.
They're providing feedback on that, and so we're developing the customer strategy with the customers ahead of actually having those satellites in space.
Mm-hmm. So you're kind of doing product development with them for a product that you hope-
Right
that they're gonna buy in the future.
Right.
Right. Okay, good. What's the timeline of Tanager, do you know?... top of your head? How many years will it last?
I don't know design life of the Tanager.
Mm-hmm.
The Pelican-
Yep
satellite is designed for about a five-year useful life.
Five-year useful life. Okay, so let's go, let's switch over to the Pelican then really quickly. So let's see here. You're going from SkySats were originally designed for, I believe, 90 centimeters. Is that right? 100?
They were originally designed for, I believe, 75 centimeters.
Okay.
Then we lowered the fleet-
Yeah
-to an altitude to capture 50-centimeter resolution.
Right. Okay, and, the design of Pelican is 50, I think, out of the gate?
Uh, no.
Thirty.
Pelican will be designed for higher resolution, up to 30 centimeters.
Uh-huh. Up to 30, meaning, depending on what altitude you're flying, is that the idea?
Depends on a number of different factors-
Mm-hmm
with the satellite.
Okay. Um.
Altitude is one of them.
Yeah.
Obviously, the closer you are to the ground, the higher the resolution.
Right. Right, but the less land mass you pick up as you're doing it.
Right.
Yeah.
Exactly.
Yeah.
I could take-
Do you remember that from your-
Yeah, geometry in freshman year of high school. I remember that.
Oh, yeah. It's almost like the penultimate math class I think I can remember. Okay. So, you mentioned Pelican is meant to replace SkySat. Can you talk a little bit about, you know, the potential growth capacity that Pelican might offer to you all?
Mm-hmm.
So good to replace things and defend the revenue that you have, but I'm just kind of curious how you think about revenue growth that would be attached to Pelican. And I know historically, you've, you all have been focused on, you know, taking one picture and selling it a bunch of times and not really doing capacity sales, but I'm wondering if part of this go-to-market change that you discussed earlier might contemplate, you know, just outright capacity sales to people and guaranteeing them some level of access to the satellites to kind of increase your capacity utilization out of the gate.
Yeah. Yeah, so with Pelican, so there's two things. So there's... offering more revisits on a daily basis-
Mm-hmm
allows you to serve more customers.
Mm-hmm.
Having higher resolution, lower latency allows you to deliver more customer value.
Yeah.
So those two pieces can help drive incremental revenue-
Mm-hmm
-beyond your existing book of business.
Mm-hmm.
Right? We've also made improvements in our software on the high-resolution side to optimize collections so that we can serve more customers with our existing satellite fleet on the high res side. And so we've talked about that in the past, but optimizing collections in order to serve more customers is a great way to grow revenue without having to put an incremental satellite up into orbit. So that's how we think about pushing on multiple different axes in order to derive our business in the high-resolution space.
Mm-hmm.
We have, again, a large pipeline of opportunities with customers across defense and civil government that we're continuing to go after. Whether they're signing up for SkySat today or Pelican tomorrow-
Mm-hmm
We wanna be able to serve those customers. And so making sure we have the assets they need today and they're gonna want tomorrow is very important.
Mm-hmm. Look, I know, you know, Airbus lost a couple of their satellites on a launch last year? I'm losing track of the time.
That's right.
2023 or 2022, I can't remember exactly. I don't believe Maxar's got any of the Allegiance satellites up yet. The world's not getting any safer and calmer.
No
There's more need for, you know, geospatial data for defense and intelligence.
That's right
... not just here in the United States, but with a lot of our allies. So I'm wondering if, you know-
Yeah
There isn't a pretty interesting opportunity here for the company on the DNI side to kind of go fast with Pelican and, you know, get some... Hopefully, you guys are sharing some of this demo data with some of our allies that are pretty thirsty for this kind of knowledge. So-
Yeah
... as we think about Pelican and I mean, do you think that we're more likely to see, you know, announcements about DNI-type customers, either growing or becoming new customers for you all, after we get Pelican going?
Yeah. So, certainly there is growing demand for high-resolution imagery-
Mm-hmm
-that Pelican can serve. And, the government sector in general, has been an area where of demand and growth. We talked about on our last earnings call, growth in defense as well as civ gov, was both north of 20% in terms of revenue on a year-over-year basis, and so we're seeing healthy growth in both of those sectors.
Yeah.
That's high resolution, also PlanetScope. PlanetScope is helping to serve those customers. When there's... Yeah, certainly the loss of some Airbus satellites and, and, delays in other programs, and so, you know, we want to be able to serve customers as quickly as possible, and that's we're focused on.
So, you mentioned PlanetScope. Maybe you can tell us a little bit about what that is and—
Yeah, PlanetScope is that daily image of the Earth captured every day by our gov fleet of satellites. So, it's a capability that hasn't existed before. It can act as a time machine for the Earth because you can scroll through an archive of daily imagery to see how things have changed over time. That serves customers across defense, civ gov, and commercial markets. We're really excited about its capability. It complements high-resolution imagery nicely. Just to give you an example of the power of PlanetScope, last year there was the Chinese surveillance balloon that showed up over U.S. territories, and there's quite a lot of media around it.
One of the first questions that government officials and others asked was, "Where did it come from?" With PlanetScope, we're able to look back through our archive and actually identify where that surveillance balloon originated from, and we worked with a AI partner called Synthetaic to do that. They ran an AI model on our PlanetScope imagery to find the balloon as it crossed the Pacific and figure out where its origin site was from. That's an example of getting to the left of an event. So with a traditional tasking system, you need to know where you want your satellite to look.
You say, "Okay, you know, I'd like an image of New York City at this time, on this day, because I know, you know, the Macy's Day Parade is going to occur, and I wanna see it with my satellite." So you task the satellite, you take an image, and then you get delivered your image. With the daily scanning system, you're capturing things that you didn't know that you wanted to see today, but a week from now or in the future, becomes very valuable. So when a surveillance balloon shows up above, over your borders, you can actually have an archive of imagery, consistent imagery, you can go back and identify where it came from.
Or with this daily scan, the broad area that we're capturing with our dataset, when you have troops building up around a border, like we saw with Ukraine, having that broad area coverage and being able to go back in time and look at, okay, where have troops built up ahead of an event occurring, is incredibly valuable. Also in terms of, for example, building damage detection. So we've run building damage analysis in Ukraine to understand where has conflict affected cities in different ways. We've run it in Lahaina after the fires to understand where have the fires caused the most damage to the city. Having that archive to be able to compare before and after is incredibly valuable.
Mm-hmm.
That's PlanetScope.
Okay, got it. So you've talked about some of the humanitarian stuff. Maybe we can talk tangentially about the global forest carbon monitoring product that you all launched late last year, and maybe some of the positive points on how that's been going on that.
Yeah. We've signed up an exciting... So demand for that has been growing, and we signed up some very exciting customers, for example, BeZero Carbon, the carbon ratings agency. And that's where we are able to measure forest carbon at the nearly individual tree level. Important for sustainability, important for forestry, also important for carbon credit markets. And so that's a new product. It is based on technology from an acquisition we did of a company called Salo Sciences, where they're using LIDAR data and our PlanetScope data to do forest canopy structure measurement, and then detect forest carbon stored in forests. We brought to market a 30-meter product late last year, and we expect to bring to market a 3-meter product this year.
Mm-hmm. Okay, great. So we're about to run out of time, so I just wanna ask you just one last question, which is, you know, leave something behind for those on the webcast and here in the room. Kind of what do you want investors to know as you, as you wrap up this presentation and, you know, I don't wanna say misunderstood about the story, but maybe what do you -- what's the investment thesis and, and the things that you all are excited about as a management team?
Yeah. Well, thanks again for hosting us.
Yep.
It's great to be here.
Yep.
You know, I think the approach that we're taking to aerospace builds on a deep history of aerospace, American ingenuity, and then applies a lot of principles from Silicon Valley, and that's called Agile Aerospace. The way we test and iterate often and move quickly is different than the traditional industry. We have a unique data set capability that hasn't existed before, that's powering all these different applications, and creating new markets. And then we are also scaling up our business. That data set scales in a very, in what we call one to many fashion, that is highly scalable, leads to high margins, and enables us to build a very attractive business with sustainable cash flows for the long run.
Okay, perfect. With that, we're gonna leave it. Thank everybody here in the room, as well as those on the webcast, for listening in today.
Thank you.
Nicely done.
Thanks.
Yeah, appreciate it. Yeah.