theCUBE + NYSE Wired: Defense Tech | John Serafini, HawkEye 360

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More from theCUBE + NYSE Wired: Defense Tech

John Serafini

Founder, CEO

HawkEye 360

play_circle_outline Three-part model: collection, processing/geolocation, AI-driven analytics to actionable intelligence

play_circle_outline Constellation of 30+ Triad Satellites for 30 MHz–18 GHz RF Geolocation with Decade-Long Proprietary Data Moat

play_circle_outline RF Space Domain Awareness Integrated into Aegis: Valiant Shield Demonstration and NASA/NOAA/Space RCO Awards

play_circle_outline Business strategy: dominate collection and end-to-end RF processing and analytics

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John Serafini, HawkEye 360

John Serafini

Founder, CEO HawkEye 360

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(INTRO)

John Furrier

>> I'm John Furrier with theCUBE here at theCUBE's NYSE studio. Of course, we have our Palo Alto studio connecting Silicon Valley to Wall Street. This is our defense tech series. We talk to the leaders who are making it happen to help our warfighters, our commanders make the right decisions to protect our society. John Serafini is here, founder and CEO of HawkEye 360, theCUBE alumni, now a public company here at the NYSE. Welcome back. Last year, you were a private company. This year, a public company. Great to see you. How do you feel? You got some gray hairs there. You went public in May.

John Serafini

>> It was a bit of a process, that's for sure, over the past year to get the company public. The IPO was back in May, and we're delighted to be a public company today.

John Furrier

>> Well, congratulations. I was on the balcony watching the bell ringing. But in our conversation last year, we really started to unpack the opportunity with platforms, but just in general, the kind of solutions that will be needed in this next generation of defense, warfare, fighting, intelligence. The game has shifted. Now it's a whole demand curve. You're seeing defense tech booming as a market. There's some spillover in the commercial side. We're seeing a lot of private -public relationships. I think we talked about some of that. What's been the biggest thing that's changed since our last conversation? besides your IPO?

John Serafini

>> Well, certainly we're in the golden age of defense technology. The political conditions are very hospitable towards the use of commercial technologies. There's an understanding and appreciation that commercial technologies from, quote, unquote, Silicon Valley can bring new capabilities, be it hardware or software or solutions, at much faster speed and at increasingly better price points to provide meaningful value to the warfighter on the ground in difficult environments. We represent an extension of that defense technology commercialization trend, and we dominate in the electromagnetic spectrum regime, where we're collecting RF data and converting that into actionable signals intelligence for our customers.

John Furrier

>> Yeah, I love how you bring in this collective intelligence paradigm to signals intelligence. Love that topic. And it's very nuanced in that world. But now if you look at AI, it's all about signaling. Data is being disaggregated, disassembled, understood, reasoned about. Again, it fits the mold. Explain how your RF platform is working these days. What's new about it? And why is it becoming a critical point for defense?

John Serafini

>> Now, the important thing to keep in mind when you contemplate my business model is that there are three distinct components. And the AI piece of that is just one of the three. That's towards the end of the value chain where we convert our data into actionable intelligence. But it starts with our ability to collect our own proprietary and unique data sets. We have 30 plus satellites in space. They're flying uniquely in clusters of three in order to perform geolocation of signals. Generally, any signal above a watt in power between 30 megahertz and 18 gigahertz, we're able to detect from space and be able to geolocate and analyze. That's block one. Block two is all the work in being able to process that enormous amount of RF data, generally down to under a kilometer for the majority of signals. And then block three is being able to connect that into actionable intelligence by leveraging AI and data science to be able to do unique things with our data and provide real product value to the end user, the warfighter.

John Furrier

>> You know, we're seeing a lot of examples where you have connectivity in some areas on the battlefield. Some are dark, dirty, congested. Explain some of these dynamics and why SIGINT and having a platform could connect to that.

John Serafini

>> It's an important criteria being a defense technology company is you intuitively understand that your capabilities have to work where the warfighter is. And the warfighter operates in difficult environments, environments where oftentimes there isn't connectivity. Oftentimes there's adversity present with an adversary, which means that your technologies have to be battle-proven. They have to be bulletproof. They have to work the first time and every time. They have to be properly camouflaged to ensure that they can meet the requirements of a warfighter who, again, they're operating in difficult environments and difficult circumstances, and your technology can't work 50 % of the time. It's got to be 100 % bulletproof, and the data always has to be trustworthy, always has to be the highest level of data integrity for the kind of capabilities that are being delivered to that warfighter customer.

John Furrier

>> The question that comes up is the why, right? Give us the why you need to exist, Department of War, other areas. They need the technology. What capabilities and gaps does it fill? What's the enablement? Talk about that ecosystem, the broader ecosystem, where it fits.

John Serafini

>> Sure. So we presented ourselves as a commercial augmentation to the U.S. government and our U.S. customers, both defense and intelligence and national security, where we're augmenting the national systems and we're providing tasking depth to those missions. But importantly, our system is an unclassified and fully shareable set of data that can be provided to coalition partners. So that's the value proposition on the U.S. government side. On the international side, which is roughly 50 percent of our business, we're very focused on delivering solutions to international customers, many of whom have never had access to their own signals intelligence capabilities, either sensors or real processing functionality. So for those customers, we can provide the full value chain where we're collecting the data, we're doing the processing with them, and then the data analytics and providing actionable intelligence products for their defense and intelligence customers.

John Furrier

>> You mentioned the proprietary nature of the signaling. Can you explain that again? I'd like to come back. I know you explained it on the first video. I think it's kind of strategic and important as an asset. Explain how the system works. You're in space. What's going on?

John Serafini

>> Sure. So part of our value proposition is this unique data set that really has never existed outside of the classified realm. What we do is we own and operate a constellation of satellites, 30 plus, that fly and operate in clusters of three. So you have a system out in front, a system behind by about 200 or 300 kilometers, and a third satellite that oscillates back and forth. And that unique geometry allows us to geolocate signals. Generally, any signal above a watt in power between 30 megahertz and 18 gigahertz, we're able to detect from space, geolocate, process and analyze and convert into actionable intelligence for our customers. That's a very unique set of data that isn't available outside of HawkEye 360. We have nearly 10 years' worth of proprietary archive of billions of different RF data points that every day we're optimizing and mining against to create our processing algorithms and eventually our turnkey data analytics for the customer.

John Furrier

>> Yeah, and it's a unique data moat for sure. in defense, there's always been conversations around the mechanism, the electronics, precision -guided capabilities. Now I see data. What's this new revolution about? How do you guys see this capability changing, those mechanisms, those electronics? Is it a disruption? Is it a changeover? Is it an accelerant to something new? Is it hardware specific?

John Serafini

>> As I mentioned earlier, this is a natural evolution of commercialization trend, where the U.S. government and allied customers are getting more comfortable with commercial capabilities being delivered at faster speed and lower price points. For us, we started off in tactical intelligence surveillance and reconnaissance in places like the battlefield, where we're able to detect, geolocate, analyze, process, and then convert into intelligence products, different signals of interest to the warfighter, be it maritime domain, radar systems, or push -to -talk radios, or GPS interference. And that's one block of our growth strategy. The second block is being able to expand into new applications and new missions, one of which we demonstrated at the Valiant Shield exercise a few weeks ago with our partners and investors at Lockheed Martin, where we were detecting certain radar systems from space and being able to download that information into weapon systems, specifically the Aegis weapon system. That's a demonstration, a critical demonstration for us of HawkEye 360 capabilities being used in the long-range fires application, which we think is a meaningful unlock for new opportunity within the U.S. government. And then second is not just doing work on being able to detect and geolocate signals terrestrially, but also being able to detect and geolocate and analyze signals in space. We have been able to announce a few awards recently, one with NASA, one with NOAA, one with Space RCO in the past few months where we've illustrated our capabilities being used in space domain awareness where we're identifying signals in space, tracking those signals and extracting intelligence about them as well.

John Furrier

>> I love your solution because, one, it's technically cool and relevant. I just love the whole RF piece of it. But it's also integrating into this new data-centric operational view, not just some bespoke platform. And you changed the equation from can I see the target to can I understand what it's doing and sensing. And it's more valuable than an image. So you can say, okay, I can look at a spot. What's going on? This is where it kind of is not a mutually exclusive situation. Talk about this thinking. How does that shift? First of all, I'm sure you agree with what I just said, but if you do, what does this do to change the human role? Because now I have more data. I can see the target on a picture, but I don't really understand unless it's full motion video. But with RF, you can see what's going on inside a bunker, what a ship's talking to, coordinating communications before any military operations even deployed or so you're in formulation you're in execution and it's kind of a big question but help us understand this importance of this dynamic

John Serafini

>> yeah soour specialty is signals intelligence rf people like to categorize that similarly to electro -optical and synthetic aperture radar where you're taking images Yeah, and the case may be that they do work complementary to one another in a tip -and -cue basis. But signals intelligence is a fundamentally different type of intelligence collection vehicle. We can do things that can't really be done with imagery. When you take a picture, a picture is a picture. You can see what you can see. When we're overhead and we're collecting signals, there may be scores of different signals that we're able to detect over a specific area. It's a layer that's not seen by the naked eye. And we're extracting all of that intelligence and we're associating it with different types of emitters and extracting intelligence about those emitters, even making estimations about what the humans who are operating those emitters may be doing or may do in the future. So to give you an example to help make it a bit clearer, think about the South China Sea. When our sensors are overhead generally every 35 or so minutes, we're collecting on different types of maritime domain awareness capabilities. It might be X -band radars or S -band navigational radars from vessels. It could be push -to -talk radio systems. It could be L -band satellite phones or emergency beacons. Whatever it may be, we're overhead. We're identifying those specific signals. We're using them to create unique pictures of each individual vessel that we can identify, and then we maintain chain of custody of that specific vessel into the future and extract intelligence about where that vessel has been and even forecast estimations of where that vessel will be in the future and what kind of activities it will be doing. So that's one domain, the maritime domain. As you can imagine, we do things similarly on the battlefield and the aerial environment. And as I mentioned to you earlier, we're now able to flip and do similar capabilities in space.

John Furrier

>> I love the multi -domain aspect. Let's go there because this is where you're starting to see coordination of resources across domains. I think AI can certainly, intelligence will definitely help. You have your own intelligence layer. How do other platforms or your platform even expand on this notion? And how can someone become an intelligent node in your network? Because you've got airspace, land, sea, cyber, and electromagnetic spectrum. that is basically your entire domain, but you don't wake up and say, we just do space. You kind of do it all.

John Serafini

>> Certainly, we anticipate over time, John, to have multiple different sensor platforms, aerial, terrestrial, etc. Today, we specialize in space. I think we're pretty good at that. But what's also interesting, as you mentioned, is the warfighter today, whether that's an intelligence analyst or a warfighter on the battlefield, they have access to intelligence modalities and capabilities that are pretty rich. And where it gets really interesting is when they're able to tip and cue amongst the two of them and combine them to create multi-INT fused capabilities. So for us, we can tip over to an electro -optical or synthetic aperture radar satellite, to say, hey, we identify anomalous RF activity in this specific area. Say it's a dark vessel that we've tracked inside another country's EEZ that we think is performing some kind of illicit activity, and we can say to whatever is the commercial EO or the commercial SAR satellite, when you come overhead this specific lat long, we want you to take an image, and then we take that image and we fuse it with the RF profile to have a better intelligence estimate of what might be going on and then deliver that to the customer at rapid speeds. It is about rapid speed. Today, the intelligence value has to be measured in minutes. It can't be measured in hours. So developing low latency, high revisit capabilities is extremely important.

John Furrier

>> Yeah, and I wanted to highlight the nuance because your asset in space translates into other domains. This doesn't have to be you guys' domain. You can help me. I'm in another domain, and that's why I like this cross -domain. Okay, air defense monitoring generally, does it get to a point where everyone's in the game? What's the advantage? How do you guys see that volume of RF data and machine learning behind it? What's the strategy? How do you guys maintain a moat if potentially everyone's trying to do this?

John Serafini

>> I see it as two mechanisms for our business plan. thing one is we want to dominate collection we want to be very very good at collecting rf data from low earth orbit space all the way to the ground and as i mentioned to you earlier we're looking at different types of platforms for us to do that collection on and then secondly we want to dominate across the entire value chain of preparing that information to be utilized by the warfighter customer or other customers and that includes being exceptionally good at the processing knowing what the signal looks like identifying geolocating that signal and then the analysis to convert that into actionable intelligence using AI, machine learning, and other data science technologies. Those are the two things that we're very focused here on at HawkEye.

John Furrier

>> I love how you're turning the spectrum into a real -time asset for AI, too, and using all that and fusing it together. You guys had a news release about your earnings coming up Thursday here at the NYSE. Any color commentary on what to expect?

John Serafini

>> We're delighted for the opportunity to present our Q2 and stay tuned on Thursday.

John Furrier

>> All right. John, thanks for coming on theCUBE on Defense Tech. Appreciate your time. Busy day. You're going to get to those meetings now. Appreciate you taking the time to share your insight.

John Serafini

>> Thank you, John. Great to see you again.

John Furrier

>> All right. I'm John Furrier with theCUBE. We are here at theCUBE's NYSE Studio, part of the NYSE Wired program and community. Thanks for watching. Thank you.

John Serafini, HawkEye 360

search

(INTRO)

John Furrier

>> I'm John Furrier with theCUBE here at theCUBE's NYSE studio. Of course, we have our Palo Alto studio connecting Silicon Valley to Wall Street. This is our defense tech series. We talk to the leaders who are making it happen to help our warfighters, our commanders make the right decisions to protect our society. John Serafini is here, founder and CEO of HawkEye 360, theCUBE alumni, now a public company here at the NYSE. Welcome back. Last year, you were a private company. This year, a public company. Great to see you. How do you feel? You got some gray hairs there. You went public in May.

John Serafini

>> It was a bit of a process, that's for sure, over the past year to get the company public. The IPO was back in May, and we're delighted to be a public company today.

John Furrier

>> Well, congratulations. I was on the balcony watching the bell ringing. But in our conversation last year, we really started to unpack the opportunity with platforms, but just in general, the kind of solutions that will be needed in this next generation of defense, warfare, fighting, intelligence. The game has shifted. Now it's a whole demand curve. You're seeing defense tech booming as a market. There's some spillover in the commercial side. We're seeing a lot of private -public relationships. I think we talked about some of that. What's been the biggest thing that's changed since our last conversation? besides your IPO?

John Serafini

>> Well, certainly we're in the golden age of defense technology. The political conditions are very hospitable towards the use of commercial technologies. There's an understanding and appreciation that commercial technologies from, quote, unquote, Silicon Valley can bring new capabilities, be it hardware or software or solutions, at much faster speed and at increasingly better price points to provide meaningful value to the warfighter on the ground in difficult environments. We represent an extension of that defense technology commercialization trend, and we dominate in the electromagnetic spectrum regime, where we're collecting RF data and converting that into actionable signals intelligence for our customers.

John Furrier

>> Yeah, I love how you bring in this collective intelligence paradigm to signals intelligence. Love that topic. And it's very nuanced in that world. But now if you look at AI, it's all about signaling. Data is being disaggregated, disassembled, understood, reasoned about. Again, it fits the mold. Explain how your RF platform is working these days. What's new about it? And why is it becoming a critical point for defense?

John Serafini

>> Now, the important thing to keep in mind when you contemplate my business model is that there are three distinct components. And the AI piece of that is just one of the three. That's towards the end of the value chain where we convert our data into actionable intelligence. But it starts with our ability to collect our own proprietary and unique data sets. We have 30 plus satellites in space. They're flying uniquely in clusters of three in order to perform geolocation of signals. Generally, any signal above a watt in power between 30 megahertz and 18 gigahertz, we're able to detect from space and be able to geolocate and analyze. That's block one. Block two is all the work in being able to process that enormous amount of RF data, generally down to under a kilometer for the majority of signals. And then block three is being able to connect that into actionable intelligence by leveraging AI and data science to be able to do unique things with our data and provide real product value to the end user, the warfighter.

John Furrier

>> You know, we're seeing a lot of examples where you have connectivity in some areas on the battlefield. Some are dark, dirty, congested. Explain some of these dynamics and why SIGINT and having a platform could connect to that.

John Serafini

>> It's an important criteria being a defense technology company is you intuitively understand that your capabilities have to work where the warfighter is. And the warfighter operates in difficult environments, environments where oftentimes there isn't connectivity. Oftentimes there's adversity present with an adversary, which means that your technologies have to be battle-proven. They have to be bulletproof. They have to work the first time and every time. They have to be properly camouflaged to ensure that they can meet the requirements of a warfighter who, again, they're operating in difficult environments and difficult circumstances, and your technology can't work 50 % of the time. It's got to be 100 % bulletproof, and the data always has to be trustworthy, always has to be the highest level of data integrity for the kind of capabilities that are being delivered to that warfighter customer.

John Furrier

>> The question that comes up is the why, right? Give us the why you need to exist, Department of War, other areas. They need the technology. What capabilities and gaps does it fill? What's the enablement? Talk about that ecosystem, the broader ecosystem, where it fits.

John Serafini

>> Sure. So we presented ourselves as a commercial augmentation to the U.S. government and our U.S. customers, both defense and intelligence and national security, where we're augmenting the national systems and we're providing tasking depth to those missions. But importantly, our system is an unclassified and fully shareable set of data that can be provided to coalition partners. So that's the value proposition on the U.S. government side. On the international side, which is roughly 50 percent of our business, we're very focused on delivering solutions to international customers, many of whom have never had access to their own signals intelligence capabilities, either sensors or real processing functionality. So for those customers, we can provide the full value chain where we're collecting the data, we're doing the processing with them, and then the data analytics and providing actionable intelligence products for their defense and intelligence customers.

John Furrier

>> You mentioned the proprietary nature of the signaling. Can you explain that again? I'd like to come back. I know you explained it on the first video. I think it's kind of strategic and important as an asset. Explain how the system works. You're in space. What's going on?

John Serafini

>> Sure. So part of our value proposition is this unique data set that really has never existed outside of the classified realm. What we do is we own and operate a constellation of satellites, 30 plus, that fly and operate in clusters of three. So you have a system out in front, a system behind by about 200 or 300 kilometers, and a third satellite that oscillates back and forth. And that unique geometry allows us to geolocate signals. Generally, any signal above a watt in power between 30 megahertz and 18 gigahertz, we're able to detect from space, geolocate, process and analyze and convert into actionable intelligence for our customers. That's a very unique set of data that isn't available outside of HawkEye 360. We have nearly 10 years' worth of proprietary archive of billions of different RF data points that every day we're optimizing and mining against to create our processing algorithms and eventually our turnkey data analytics for the customer.

John Furrier

>> Yeah, and it's a unique data moat for sure. in defense, there's always been conversations around the mechanism, the electronics, precision -guided capabilities. Now I see data. What's this new revolution about? How do you guys see this capability changing, those mechanisms, those electronics? Is it a disruption? Is it a changeover? Is it an accelerant to something new? Is it hardware specific?

John Serafini

>> As I mentioned earlier, this is a natural evolution of commercialization trend, where the U.S. government and allied customers are getting more comfortable with commercial capabilities being delivered at faster speed and lower price points. For us, we started off in tactical intelligence surveillance and reconnaissance in places like the battlefield, where we're able to detect, geolocate, analyze, process, and then convert into intelligence products, different signals of interest to the warfighter, be it maritime domain, radar systems, or push -to -talk radios, or GPS interference. And that's one block of our growth strategy. The second block is being able to expand into new applications and new missions, one of which we demonstrated at the Valiant Shield exercise a few weeks ago with our partners and investors at Lockheed Martin, where we were detecting certain radar systems from space and being able to download that information into weapon systems, specifically the Aegis weapon system. That's a demonstration, a critical demonstration for us of HawkEye 360 capabilities being used in the long-range fires application, which we think is a meaningful unlock for new opportunity within the U.S. government. And then second is not just doing work on being able to detect and geolocate signals terrestrially, but also being able to detect and geolocate and analyze signals in space. We have been able to announce a few awards recently, one with NASA, one with NOAA, one with Space RCO in the past few months where we've illustrated our capabilities being used in space domain awareness where we're identifying signals in space, tracking those signals and extracting intelligence about them as well.

John Furrier

>> I love your solution because, one, it's technically cool and relevant. I just love the whole RF piece of it. But it's also integrating into this new data-centric operational view, not just some bespoke platform. And you changed the equation from can I see the target to can I understand what it's doing and sensing. And it's more valuable than an image. So you can say, okay, I can look at a spot. What's going on? This is where it kind of is not a mutually exclusive situation. Talk about this thinking. How does that shift? First of all, I'm sure you agree with what I just said, but if you do, what does this do to change the human role? Because now I have more data. I can see the target on a picture, but I don't really understand unless it's full motion video. But with RF, you can see what's going on inside a bunker, what a ship's talking to, coordinating communications before any military operations even deployed or so you're in formulation you're in execution and it's kind of a big question but help us understand this importance of this dynamic

John Serafini

>> yeah soour specialty is signals intelligence rf people like to categorize that similarly to electro -optical and synthetic aperture radar where you're taking images Yeah, and the case may be that they do work complementary to one another in a tip -and -cue basis. But signals intelligence is a fundamentally different type of intelligence collection vehicle. We can do things that can't really be done with imagery. When you take a picture, a picture is a picture. You can see what you can see. When we're overhead and we're collecting signals, there may be scores of different signals that we're able to detect over a specific area. It's a layer that's not seen by the naked eye. And we're extracting all of that intelligence and we're associating it with different types of emitters and extracting intelligence about those emitters, even making estimations about what the humans who are operating those emitters may be doing or may do in the future. So to give you an example to help make it a bit clearer, think about the South China Sea. When our sensors are overhead generally every 35 or so minutes, we're collecting on different types of maritime domain awareness capabilities. It might be X -band radars or S -band navigational radars from vessels. It could be push -to -talk radio systems. It could be L -band satellite phones or emergency beacons. Whatever it may be, we're overhead. We're identifying those specific signals. We're using them to create unique pictures of each individual vessel that we can identify, and then we maintain chain of custody of that specific vessel into the future and extract intelligence about where that vessel has been and even forecast estimations of where that vessel will be in the future and what kind of activities it will be doing. So that's one domain, the maritime domain. As you can imagine, we do things similarly on the battlefield and the aerial environment. And as I mentioned to you earlier, we're now able to flip and do similar capabilities in space.

John Furrier

>> I love the multi -domain aspect. Let's go there because this is where you're starting to see coordination of resources across domains. I think AI can certainly, intelligence will definitely help. You have your own intelligence layer. How do other platforms or your platform even expand on this notion? And how can someone become an intelligent node in your network? Because you've got airspace, land, sea, cyber, and electromagnetic spectrum. that is basically your entire domain, but you don't wake up and say, we just do space. You kind of do it all.

John Serafini

>> Certainly, we anticipate over time, John, to have multiple different sensor platforms, aerial, terrestrial, etc. Today, we specialize in space. I think we're pretty good at that. But what's also interesting, as you mentioned, is the warfighter today, whether that's an intelligence analyst or a warfighter on the battlefield, they have access to intelligence modalities and capabilities that are pretty rich. And where it gets really interesting is when they're able to tip and cue amongst the two of them and combine them to create multi-INT fused capabilities. So for us, we can tip over to an electro -optical or synthetic aperture radar satellite, to say, hey, we identify anomalous RF activity in this specific area. Say it's a dark vessel that we've tracked inside another country's EEZ that we think is performing some kind of illicit activity, and we can say to whatever is the commercial EO or the commercial SAR satellite, when you come overhead this specific lat long, we want you to take an image, and then we take that image and we fuse it with the RF profile to have a better intelligence estimate of what might be going on and then deliver that to the customer at rapid speeds. It is about rapid speed. Today, the intelligence value has to be measured in minutes. It can't be measured in hours. So developing low latency, high revisit capabilities is extremely important.

John Furrier

>> Yeah, and I wanted to highlight the nuance because your asset in space translates into other domains. This doesn't have to be you guys' domain. You can help me. I'm in another domain, and that's why I like this cross -domain. Okay, air defense monitoring generally, does it get to a point where everyone's in the game? What's the advantage? How do you guys see that volume of RF data and machine learning behind it? What's the strategy? How do you guys maintain a moat if potentially everyone's trying to do this?

John Serafini

>> I see it as two mechanisms for our business plan. thing one is we want to dominate collection we want to be very very good at collecting rf data from low earth orbit space all the way to the ground and as i mentioned to you earlier we're looking at different types of platforms for us to do that collection on and then secondly we want to dominate across the entire value chain of preparing that information to be utilized by the warfighter customer or other customers and that includes being exceptionally good at the processing knowing what the signal looks like identifying geolocating that signal and then the analysis to convert that into actionable intelligence using AI, machine learning, and other data science technologies. Those are the two things that we're very focused here on at HawkEye.

John Furrier

>> I love how you're turning the spectrum into a real -time asset for AI, too, and using all that and fusing it together. You guys had a news release about your earnings coming up Thursday here at the NYSE. Any color commentary on what to expect?

John Serafini

>> We're delighted for the opportunity to present our Q2 and stay tuned on Thursday.

John Furrier

>> All right. John, thanks for coming on theCUBE on Defense Tech. Appreciate your time. Busy day. You're going to get to those meetings now. Appreciate you taking the time to share your insight.

John Serafini

>> Thank you, John. Great to see you again.

John Furrier

>> All right. I'm John Furrier with theCUBE. We are here at theCUBE's NYSE Studio, part of the NYSE Wired program and community. Thanks for watching. Thank you.