Spire Global, Inc. (SPIR) Earnings Call Transcript & Summary

Welcome back to the Deutsche Bank Global Space Summit. Next up, we have Spire Global and the senior executive management team there. One thing before the formal presentation begins is I would love Peter, the CEO, to talk about his background. Because in addition to being a former Deutsche Bank alumni, he's done quite an array of interesting things. So Peter, if you don't mind, could you maybe start off by talking about kind of what drew you to Spire and also what drew you to space in general?

Thanks, Edison. It's my pleasure to be here, and I'm happy to share the story. So I'm originally from Austria. I was fortunate enough that at a very young age already, I knew that I wanted to be a physicist. So I was a high-energy infusion physicist, spent a little bit of time at CERN and Max Planck Institute and always had this fascination of how can we leverage space to improve things on Earth, improve understanding of what is happening on or around Earth. But it was a very, very slow industry as you, of course, know. And so for someone who has been writing code since a teenager, that was a little business going on the side, that was just not dynamic enough for me. So I ended up working for the Boston Consulting Group in Europe and then in Asia. And then they sent me to Harvard Business School. And I looked again at the space industry actually with a couple of my classmates. And unfortunately, at that point in time, it was still a very, very slow industry. And so I ended up spending almost a decade on Wall Street as a quantitative investment manager, focusing mostly on emerging markets, equities, currencies, commodities, some debt for that period of time. And amongst others, I was fortunate enough to work at the desk of Deutsche Bank in their internal hedge fund. And through an event that NASA aims in 2009, I believe, I felt that space is now ripe for a more dynamic trajectory. I was fortunate enough to be there and have conversations with people like [indiscernible] Peter Diamandis, Salim Ismail, Neil Jacobson and others and really got convinced that the rate of change is happening here on a more and more exponential trajectory and less and less on this very slow linear one. And so after a few more thinking and research, I actually left Wall Street, and went one last time back to graduate school in France for a degree in space science and management. And for that degree, I had to do like a little mini thesis. And I did a piece of research where I analyzed on one hand what has been happening with this small form factor satellites. And on the other hand, interviewed about 100 people from the space industry, what they are thinking is starting to happen with those small devices. And it was very stark because the generally accepted wisdom of the experts was a very slow improvement curve but slow and linear. And what I saw in the data that was something very, very different. I saw a pretty stable 10x every 5-year improvement curve, something that is actually faster than was long. By that point in time, it had been stable for 1 decade, 1.5 decades already. And boldly I projected and predicted forward what capabilities of those small form factor satellites will be in another 5 years, another 10 years, 2015 and 2020. And it was very clear that based on those capabilities that they will solve crucial real-world use cases. And that was the starting point of the company back in, really the proverbial garage in San Francisco, grungy, dirty in which we built our first satellites. And then, of course, the story over the next 10 years was a very fortunate one. As you see here, we are now one of the largest constellations on orbit. We're the largest one using radio frequency and other type sensors to observe the Earth with over 100 satellites. We got a massive global ground station network, over 70 antenna systems in 16 countries, 30 locations. A few hundred years of cumulative space heritage, a few hundred employees, over 700 customers that consume our data and our solutions and we are on track to hit over $100 million of ARR as per our guidance by the end of this year. Especially for those that don't spend every single day in the satellite industry, we find this classification system quite useful. There, of course, are an increasing number of companies leveraging space to solve problems on Earth. That was indeed the premise that we had when we started the company. That law that I uncovered of 10x improvement every 5 years has held steady now for almost 2.5 decades and Spire has been able to leverage that law to increase our capabilities. But sooner than a lot of other companies. And it's actually not as one big grab bag of things as it might sometimes appear. I sometimes use the analogy with the logistics industry where you have ships and planes and trucks, and everyone understands how they're different. Even though when you think about it, they all have wheels, they all have engines, they all have windows, they all have passengers, they all have cargoes, they all have pilots, they all have steering wheels. And so there's a lot of similarities. But just by the nomenclature, it's obvious that they're different, and they are everyday objects. Unfortunately, satellites are not yet everyday objects and we call everything a satellite, even though different types of satellites are as different as a ship is from a plane. And we categorize them into talking satellites, looking satellites and listening satellites. Looking satellites is probably one of the most familiar ones and the easiest that come to mind for a lot of people. You basically have a camera in space that looks at the reflection of the sunlight as it hits that camera, and that's the data that we collect. And you have companies like Maxar and BlackSky and Satellogic and Planet and Airbus and ICEYE, a whole bunch of other companies that use that looking methodology. Then you have talking satellites. Often, some people call it communication satellites, but they basically transport a piece of information, a piece of data from one space -- spot on Earth to another spot on Earth. And you have companies like a Viasat, AST and Starlink, Iridium a whole bunch of companies like that. And then there are listening companies that use radio frequencies to observe what is happening on or above Earth. And you have companies in there like a GeoOptics or HawkEye or CLEOS or Spire. And then radio frequencies have a couple of unique features namely they operate day and night and in all weather conditions and through clouds. So that makes them quite flexible and quite useful as you try to understand what is happening on or above or around Earth. Spire is probably by any metric, the largest company in that listening segment. From a satellite deployment perspective, we are in a fortunate position of being fully deployed with our constellation. So we're not looking to grow the constellation or launch a large number of satellites in that perspective. So that puts us in a very fortunate and strong position of maintaining and operating what we have. That constellation covers all of Earth 100 times a day. So every 15 minutes, we are covering just about every spots on Earth. And that is indeed the coverage that we would like that our customers are asking for. And so that's why we are fully deployed. It's also a technology that we have built that in -- is differentiated from some other approaches in a sense that it is software-defined meaning we can change from the ground what the constellation does or how it does something. The type of data it collects, the amount of data, the quality of the data. So that gives us a lot of flexibility in augmenting our offering and responding very, very quickly to customers' demand on immediately at global basis. To give a recent example there, when there were some changes happening in the global security sphere starting early this year in February in Europe, the demand for solutions that answer that change and that challenge was becoming very obvious. And so Spire ran a software upgrade program for our constellation on orbit and now today has the largest deployed RF geolocation-enabled satellite constellation of any commercial company with over 40 satellites being able to geolocate signals on earth. I think that's probably a good segue to talk about how we are set up as a company in leveraging that fully deployed constellation. We're operating across 4 different data solutions. Maritime, Aviation, Weather and Space Services. Our satellites, every single one of them fulfills multiple purposes through multiple sensors serving at least 3 and in certain instances, 4 or more of those data solutions. We track just about every large vessel there is on the planet moving about, about 0.5 million or so on a regular basis. And we collect a multitude of relevant and valuable data points, exact location of the ship, speed, heading, type of cargo, where it's coming, where it's going, it's turning so change in direction, how the [indiscernible] riding in the water, how much cargo it has, type of cargo. It's about 37 different characteristics of every single vessel that we collect data from space. Very similar in aviation, where we do just about the same for aircraft, tracking where they are, where they're going, the altitude, all those kind of relevant information. Weather, about 1/3 of the global economy is impacted by weather. So I saw a massive, massive opportunity set where we collect data about the weather. But as you will learn in a second a bit more also predicts the weather as we use that data. And then Space Services is the equivalent of Amazon AWS. People renting our infrastructure, our capabilities to derive value for a particular business model use cases they have through a piece of software, piece of [ art ] that they have given us and leveraging our infrastructure. You put it all together, you operate in a $100 billion market with some 150,000, 200,000 target customers. Now one thing that is special about Spire is how we were set up from day 1 to capture and serve our customers across the full value chain. We collect the data from our constellation once, and then have the opportunity to sell it many, many, many times, just like other data and solution subscription companies you might have heard of. But we don't just stick with that data that we are collecting, data that mostly describes what is happening right now. We infuse that data with our third-party data. We add analytics to it and make it smart data and then make that available as a subscription. And then as a next layer, we add AI, machine learning, big data algorithms to it to make predictive analytics what is going to happen. I made a reference point earlier on the weather side, this is the weather today, but this is what the weather is going to be. Same thing on the maritime side, this is how global trade looks today, but this is how it will look today. This is the state of the supply chain today, but this is how it's going to look like in the future. And then the last one, of course, is solutions where we help our customers understand what you should most likely do. And it's really the totality of that capture of the full value chain that allows us to serve our customers not just in one instance, but in many instances, a metrics that I believe Tom will talk about here in a second is how much customers increase their spending with you as you continue to solve additional use cases and it's a metric that we are certainly very proud of because it is substantially above 100%, meaning that we continue to solve more use cases year in, year out for our customers. And with that, maybe Tom, you can talk a little bit about how that strategy, that market and that competitive positioning has translated in some of the most exceptional growth stories that subscription business companies have seen?

Thanks, Peter. Yes, if you look at this chart on the left-hand side and focus there first, the far, far left is our starting point of when we started ARR for the first time. So steady $1.6 million in that first year. And then an amazing growth that we've had all the way up through our 2022 projection. Now we're getting off most of that number just by itself. We just had our earnings yesterday and we hit $98.1 million in our ARR number. We exceeded our guidance in that range by a lot and we came awfully close to hitting the mark of $100 million at the end of the third quarter. So really trying well to hit that $103 million number, which is the midpoint of our guidance by end of the year. And so you can see the huge trajectory of ARR and the opportunity that we've had to land customers and then expand them and drive these numbers. If you switch over to the right side and translate that into a line where we are, which is the red one, of going from that year 0 to year 5 on our path to $100 million and how fast we've done it compared to other players out in the market. And you can see there's very few good names in there, but they're also to the right, which means they took a lot longer to get there. And very few that's still left of us that got there a bit faster than us. So an amazing path to get to $100 million ARR at a very short period of time. Looking at some of the numbers. Again, these numbers just came out yesterday in our earnings. So if you going to focus a bit on the middle line there because that was -- that's the current quarter. Obviously, the left is last year, and then you can see the improvement, which are a pretty amazing set of improvements. The first 2 are our top line items, our ARR. As I mentioned, we hit $98.1 million, a 117% year-over-year growth. That translated into for the particular quarter $20 million (sic) [ $20.4 million ] of revenue. Both those are record numbers for us and it's 114% of revenue. So awfully close to each other on revenue growth percentages. Then you switch gears and look at, okay, well, we've got the top line growth, that's great. What are we doing on the margins on that front? And you can see the improvements that we made from a dollar standpoint and obviously, significant standpoint from a margin standpoint from going a year ago to this year. And it goes back to what Peter was mentioning on that leveraged business structure. So getting that top line because we have 4 solutions to sell. We have a large TAM to go after. But then also translating that into a leveraged business model where we can take our head count, a significant number of our head count and our infrastructure and spread that spend across all 4 solutions, which is very, very unique, right? I mean how many companies out there are spreading themselves over multiple solutions for their technology? Most of them are doing one thing. They might be a one-trick pony, and they've got a revenue stream that's coming in and then maybe a heavy, heavy CapEx that only will fund that one solution compared to we're taking our technology and spreading it across all 4, both for the ground stations and the satellites in space. So then you can see the amazing improvement on our free cash flow at the bottom line, which is we actually cut that number in half from last quarter and a year ago. So a huge improvement on our lowering the burn on our path to both profitability and also our path to free cash flow positive, which we actually have a target out there of 16 to 22 months. I'm not going to spend too much time actually in the numbers on this one because that was on the last slide. I'm really going to focus more on the why here, why are we seeing the improvements in this case? And I mentioned it a little bit, and Peter mentioned it a little bit, and why we feel this is going to continue? So the top 2 are again the top line ones. Why we feel that this growth pattern can continue? Why are we happy with the growth that we've done to date? And again, it's because we have 700 customers, which is a lot in one regard. But when you think about the TAM that's available in all 4 of the solutions that we have to go after, we're just barely scratching the surface on all 4 of those. So we can really continually ride that wave from 4 different solutions on going to get that TAM. Just to give you a little bit of a double-click on the TAM. I think a lot of people think maritime, it's just vessel companies, that's all you sell to. Even that, there's about 50,000 vessel companies in the world, so not a bad thing to go after. But at the same token, I don't think everybody realized the ecosystem around who we sell to. Logistic companies need that data, transportation companies need that data, the ports need that data, insurance, hedge funds. All these different companies that wrap around that, coast guards, government, defense, use that same information that's very powerful for them to run either businesses or to stop illegal fishing or to stop [ hiding ] all those different things. That information is valuable and a lot of people need that information that you only can get through satellites. And so that's the maritime. You go over to aviation, same thing. I think people think we're only selling to the airlines, yes, we can. But there's also an ecosystem around there too, airports, transportation, logistics, same thing, insurance, hedge funds, travel and leisure, all would like that information. Weather kind of goes on and on and on and mining and there's -- you can do race car companies, you can do launch companies. There's so many different companies that have obviously need to live and breathe by any more accurate forecast because either it saves them money or it has a huge ripple effect. If you're a launch company, you don't have a good weather forecast, what do you have to do? You have to cancel it, move it out, very disruptive for their business, rather than getting the best accurate forecast available through us. So that's why the top line we think it's going to continue. There's so much opportunity there. But then flipping down on the other side, again, taking that growth from what we've got up there and translating it into what we can do on the bottom line because we're leveraging that cost structure across all 4 of them is why we see that chart and those numbers improving and why we feel also we're going to continue to that little box there in the middle, which is then our projected positive free cash flow, which is in, like I said, 16 to 22 months.

Great. Thanks a lot for that. Wanted to start at the high level, a couple of questions. I think we've had quite a bit of discussion at the conference about the EO side to the seeing, but not as much on the listening. And so can you maybe go over just the differences in terms of operational use case, real-life examples of why you need both or why they're used for different things and why there's not really that much for any overlap -- very much overlap?

Sure. So indeed, there is no overlap. There are some instances where a customer might want to have both and where we have collaborative with looking companies. But generally, it's very, very different use cases. And let's talk about something that has recently happened in Florida and is actually happening again, call it hurricane. So EO companies are very useful in assessing the damage after a hurricane, right? They have like a picture before and then a picture afterwards and then they're useful in assessing that. Our data is more useful in reducing damage that will happen because companies and communities are prewarned of what might happen, where hurricane will land. So having the predictive capability from our data on where an extreme weather event might land and how extreme it is going to be, that means you can be better prepared than otherwise. And it could be simple things. Maybe bring in the harvest a day sooner because there's going to be a lot of rain. Maybe warn a customer that delivery will be half a day delayed because there is so much rain that there's going to be traffic jams from your logistics supply chain. Maybe change the route of the aircraft so that you don't go through like the worst weather or change the route of a ship because it will go through a very, very bad weather creating a risk for the crew, the cargo and the vessel. So being predictive is kind of the core instrument of our data there versus describing what has happened after the effect. But there are instances where there can be a little bit of collaboration, and they tend to be almost exclusively in the defense world where Spire identifies that there is some illegal shipment activity happening. A ship is claiming to go up the coast of Africa, but it's actually breaking international embargoes and it's going, let's say, to Venezuela, was another place in Latin America. And then from a jurisdictional perspective, having an actual image of that activity is very valuable so we can then share that information or the customer of us can then task an imaging satellite to take that information from that one. I think the biggest advantage however of radio frequency is that, A, it has much higher temporal resolution. As I mentioned earlier, we cover the earth every 15 minutes 100% of all of Earth. So we can create data points more like a movie rather than a still image that you get once a day or once a week. And we can do that in the night which is obviously not working with imaging satellites and we can do it in bad weather conditions where there's cloud cover. And again, that can be very, very advantageous. So the 2 modalities have very, very different use cases, very, very different customers. And both are, I think, highly valuable as we have seen recently in the growth of use of Earth observation data, both on our side, Tom just talked about the growth trajectory, as well as what you have seen on the imaging side of others. So complementary from the perspective of Planet Earth and understanding what is happening here. But no overlap with regards to customers and use cases and certainly, no competition between those 2 groups. Maybe in certain instances, possibilities for collaboration.

So you're clearly collecting a tremendous amount of data. And there's -- I think there's a good graphic you have that the data itself isn't really particularly useful. You need insights so you generate insights. Can you talk about your ecosystem for that? Are you doing everything yourself? Is the data feeding to other people? How does that all work?

So indeed, that was one of the images that we shared earlier, Spire serves their whole value chain. I think I probably disagree a little bit with the statement of the data itself is not very valuable. There is a very wealthy family today because it has the information about the outcome of the Battle of Waterloo as I get, who won very little piece of raw data and he had it a couple of days before the rest of the world. And literally, it's the name now that everyone knows. So similarly, Spire collect data that no one else has. So I think having something very, very unique in the data space is indeed just like oil for the global economy, where, of course, the refined products, the additional value chain down from the raw oil coming out of the ground is very valuable. But I think you could all agree that those that hold the raw data, the raw oil, so to speak, are in the global economy in a quite fortunate position and Spire finds itself in a similar location because the type of data that we locate, that we collect, that we analyze and we can make available to our customers, we tend to be the absolute leading collector, provider, analyzer of that type of data. But indeed, once you take that raw data and you start to refine it, just like in the oil economy, the refinement of those products become even more valuable than just the unique and hard to get original data. And that indeed is something that Spire does. From day 1, we have been set up like that, refining our data, treating analytics on top of it and then adding third-party data sets fusing it to create what we call a smart data set. So for example, in the maritime field, not just describing where the vessels are and all of their characteristics and locations and type of cargo. Having information about the owner of that vessel, maybe having information about the route that the vessel is taking, what type of cargo might be on that vessel. All of it fused into the data stream to our customers. And then we go yet another step further by adding predictions. I talked about the weather, and of course, I think it's generally very valuable to have information that describes the weather information that is used by governments all across the world and has created many tens of millions of dollars of contracts for us consuming that data by those government customers. But that is, of course, just the start of the story. If you run an offshore wind farm, on one hand, if you're in Europe, you are right now under tremendous amount of pressure helping Europe weed itself off particular oil supplies from a particular place and do so many, many years, if not decades faster than was originally indicated but do so in a reliable fashion. Now you can only do that if you have an ever greater accuracy of prediction of how much wind is going to come. And that, of course, translates into energy that you produce very similar to solar power plants, which need to know how much cloud coverage will there be, how much solar irradiance will happen. And so the predictive nature, which is the next stage of our value chain capture of Spire solutions is incredibly valuable for those types of customers. And then last but certainly not least, our solutions. Think of a global logistics company, which has been able to benefit from that capability of not just knowing where every single ship and every single plane is of themselves but also of the competition, but also understand what the global weather conditions are and will be and where there might be delays and where there might be something worthwhile to reshuffle and they can come up with a plan, a recommendation of how they should react to that global picture of where everything is, every competitor is, where everything will be and every competitor will be and where the weather will be, which is in the last stage of the value chain, capture the solution side.

That's great insight. That's great insight. One follow-up with the couple of minutes we have left is, it seems -- you mentioned you're one of -- maybe the only one of very few people who can actually just collect the data in the first place. Can you go over what competitive advantage you have in that area in particular? Is it that the traditional legacy way is just too slow? What's the sort of advantage there that makes it hard to replicate?

So you might recall the incident a few years ago where we tragically lost an aircraft, the Malaysia Airlines Flight MH360 -- 370 and it kind of like made the world aware that once the plane leaves a shore, we don't know where it is. 95% of the world's population lives on just 3% of the world's surface area, meaning what you and I experienced off the world is about the same size as your half bathroom and the cellar of your house at home, and the rest is just not explored, not known, not seen by us, because it is so vast. And the only way to capture all the rest is through a global satellite constellation, which is a massive hurdle. So one, and it's actually not our biggest one, but it is one of the competitive advantages the competitive moats that we have built is that we have a global satellite constellation. And so the old days before Spire existed in many, many of our data products was speaking of fear into the air and guessing or simply not knowing because 80% of the time, the location of a vessel was not known even though maritime shipping, for example, carries over 90% of global trade. So that's the first layer. The second layer is the actual technology that drives those devices. For example, in the maritime field, the transponders data that we are capturing is a mandated device by law that is installed on all vessels as an anticollision device. It is mentioned in about 50-mile radius to let other vessels knows where they are. And Spire has built the incredibly sensitive listening equipment to listen to that information 500 kilometers, 600 kilometers above those vessels. Some of that listening capability is of a sophistication that when we started out the incredibly smart people at NASA said, "Peter, you will have to break the laws of physics to accomplish, what you say?" As a physicist, I can promise you, we didn't break any laws but we scurried close to the edge to make possible what we are in on our devices. That is the next layer of our competitive moat. Simply the devices that we had to invent and then the software to drive those devices is not something that you can buy. The next layer is the analytics capabilities. The areas that we operate in are not common place. Everyone [indiscernible] and I think my 8-year-old daughter is starting to do that, is buying some OpenCV and does image analysis and some AI analysis for edge detection or building a self-guiding robot that you hope you don't step over in the living room. What we do require some pretty esoteric skill sets. We're talking wave optics, we're talking RF circuitry, which is often called the black arts of electrical engineering. We're talking Fortran. We're talking metrology, we're talking dynamic ports. Those are very, very esoteric and difficult to find skill sets and we run certain sensors and capabilities where there are 5 people in the world at least that we know of, that know how this works, and we hired 3 of them. So the next layer is simply the depth of people and knowledge required to build the analytics. The fourth layer is that the actual data. Just like any data company, the more data you have, the stronger the products that you can build by mining the data for your customers. Every single day, we collect hundreds of millions of data points that feed into our growing data vault, which has now been growing for almost a decade. Meaning that our competitive advantage and moat grows every single day as we are the ones which have this data and others do not have this data. And the fifth one is the logistics and the licensing required to build an infrastructure capable of collecting this data. You do need licensees to collect data in space and do talk with those satellites on the ground on so-called ground stations. Now some of these licenses require a number of months to get, but some of them require a number of years to get. So aside of the logistical challenge of getting stuff into 16 different countries and deploying one of the largest constellation on the planet or actually around the planet, there is a licensing challenge, which is a many year endeavor. You take all of those moats together, we're looking at something to 4.5 to 5.5 years for someone to replicate where Spire is today just from a development and deployment perspective, let alone the customer relationships some of which on especially on the government side are very, very relevant and we're talking here 8-figure contracts that require many years to develop that trust with the customer that you can deliver to them at a time line and reliability and security that meets their extremely exacting standards.

Fascinating. Fascinating. With that, we're over time. Unfortunately, I feel we can continue this for another half an hour. I really want to thank the Spire Global team for joining us at the DB Global Space Summit. Thank you again guys.

Awesome. Thanks, Edison.