The Startup Defense

National Defense Data Analytics, Building Talented Teams, and Royce Geo with Dave Sterling

December 06, 2023 Callye Keen Season 1 Episode 33
The Startup Defense
National Defense Data Analytics, Building Talented Teams, and Royce Geo with Dave Sterling
Show Notes Transcript Chapter Markers

Dave Sterling of Royce Geo and Callye Keen (Kform) discuss the fusion of commercial technology, complex data, and national security. Sterling's unique perspective on the intersection of defense, technology, and startup culture offers invaluable insights for innovators and leaders in the defense sector.

Topic Highlights:

[00:00] Introduce Dave Sterling
Callye Keen introduces Dave Sterling, CEO of Royce Geo a leader within the IC and DoD in enterprise IT, advanced analytics, and intelligence modernization, rapidly increasing intelligence production, situational awareness and delivering answers to some of the hardest issues currently facing US national security.

[05:08] The Convergence of National and Commercial Intelligence
Discussing the integration of national technical means and commercial data, Sterling emphasizes the need for practical technical expertise. He details how Royce Geo leverages this convergence to provide actionable intelligence, illustrating the company's strategic shift towards comprehensive, tech-driven solutions.

[09:00] The Role of Advanced Analytics in Intelligence
Sterling shares insights into Royce Geo's core competency in advanced analytics and its impact on agile data collection and processing. He reflects on the journey from traditional intelligence methods to pioneering real-time, automated data analysis, revolutionizing intelligence gathering.

[26:32] Talent Acquisition and Training in Intelligence 
A key focus for Sterling is harnessing untapped talent. He discusses the strategy of employing individuals with strong technical backgrounds and then immersing them in intelligence work, effectively bridging the gap between technology and defense intelligence.

[32:13] Future Trends in Commercial Space and Intelligence 
Looking ahead, Sterling predicts significant developments in commercial space, emphasizing the need for faster data transmission and processing. He foresees a growing reliance on commercial assets for national security, underscoring the importance of speed and resilience in intelligence operations.

"Really understanding the problem, I think, has been a big part of our success... If you really want to make it in this industry and have that enduring name... you've got to understand the problem. And if you do that, then I think the rest of it will come." - Dave Sterling

Callye Keen - Kform
https://kform.com/
https://www.linkedin.com/in/callyekeen/


Dave Sterling - Roye Geo
Dave started Royce Geo back in 2015 with the idea of making analysis more powerful with greater speed through automation. Fast – forward to today, Royce Geo is a leader within the IC and DoD in enterprise IT, advanced analytics, and intelligence modernization, rapidly increasing intelligence production, situational awareness and delivering answers to some of the hardest issues currently facing US national security. Sterling has over 20 years of geospatial expertise serving as analyst for NGA and building a GEOINT portfolio for KEYW (now Jacobs). It was this combined mission experience gained through government service and corporate capabilities development at KEYW that set the tone for what Royce Geo would be today and for the future… where unrelenting mission focus is combined with force multiplying innovation. Today, Sterling leads operations, strategy and sets corporate vision for Royce Geo.

https://twitter.com/Royce_Geo
https://www.facebook.com/roycegeoconsulting
https://www.linkedin.com/company/roycegeo  

Speaker 1:

Machine learning, ai all those things are here to stay. That is going to become the new normal. If we don't get out of this now, as a company, work going to be completely playing catch up the entire time. We made a pretty hard stance about two and a half years ago. We were trying to be the next dot AI company or be Royce Geo the experts, machine learning no, it's just going to be an active part of what we do. It's not the only thing we do, but it's something we're starting to do pretty well welcome to the startup defense.

Speaker 2:

My name is Cali Kean. Today I have Dave Sterling of Royce. Geo Dave, you have a rich background inside agency as a startup founder, as a technologist. Really, really interesting what you're doing for G, g, I, s and the intelligence associated with the solutions. But before we hop into the tech stuff and how that's all changed and you have some really interesting thoughts there, the question I ask everyone to get a start is what are you passionate about right now?

Speaker 1:

Sure. Thanks, kelly, thanks for having me, if you were to ask me eight years ago. It's all about mission, and still is very much about mission. When you're involved in the startup, it's really all hands on back me included out everything from CEO to janitor to analyst everything in between. In growing of this is very fast over the first couple of years you're kind of juggling this people, mission, tech, hiring all the things you need to do to run a company. Fast forward nine years later to where we're at today, what I'm really Passionate about is bringing in technology experts and really team improvement to really improve our ability as a company to execute.

Speaker 1:

We have found, you know early on, we have more to really primary customers Doing some very focused work as we've evolved over the last nine years. We're still very focused. We know what we do. We do, I'd like to think, fairly well, but we're starting to find that we have a lot of the same. Partners Are all raising their hand with very much the same problem, and that is really understanding the national and commercial imaging layer how to better utilize that, moreover, how to get that information back to make the decision much faster. So it used to be a we had one you know me major agency. That was our primary focus. It still is today they're a largest customer. Now we have several different do the cocom components, that kind of quit frankly, are all asking for the same thing. So we are very much focused on improving our internal tech. Bring in more tech enabled experts and leaders and experts really get after a mission set. So that's really a focus for us.

Speaker 1:

For me personally has been, is been team building and that really comes with, as you're running fast growing companies and overall this company proven how are you not getting Out of your skis and growing too fast where things start falling on the floor and you're making a message that you have to stay focused, stay oriented, really understand your mission, your goals, which you want to be as a company when you grow up. So sometimes internally pull myself to wear both ends where it's all. We have to remain very relevant the tech space. That's an imperative, very relevant mission space for more over. We have to keep and manage and maintain this company that really embraces new idea, new thought, is able to grow, is able to provide that experience for our employees so we're able to bring the best of all things together.

Speaker 1:

I've seen some, some other firms in our space that have done this very well. I've seen some that have grown, quite frankly, a little fast and you could see the wheel starting to get out of a line and they start falling apart. Growth from the defense start up sample and I think we're out of the start of phase. Maybe this point, but I argue with that internally as well growth for the sake of growth isn't necessarily always a good thing. You gotta have that very smart, protracted growth and what are we really gonna be great at the end of the day?

Speaker 1:

Then, more over, how do we take those things that we do extremely well and how do we reposition, repackage those to help answer in our case, the defense and Intel community those very light problems that are, you know, scattered all over the beauty cocom I see elements that, quite frankly, are all looking for solve a lot of the same same type of issues. I spend a lot of time, probably more than ever, staring at problems really decomposing. What are these folks when they're saying they have this issue? What is it that they're trying to get after and trying to do? There's a lot of thought early on and you know what is going to be the right information, implementation of people, data and technology, company or size. We don't have an endless checkbook, so we're gonna make a bet, we've got to make a very smart that in the way to do that is really understand what is the core problems are trying to answer and try to address and more over.

Speaker 1:

I mentioned earlier that those, those technical experts I think there's a subtitle in their practical technical expert we could go and hire a lot of deep thinking PhDs that are very, very smart in their craft and that's great. But when it comes down to it, for us to be successful business, we have to take Hi and tech high and knowledge being able to make it practical and be able to implement Pretty short amount of time. And that's something that we've done extremely well, especially in the last three years when we've kind of inserted ourselves in this convergence of national technical means, data and commercially available Imaging, rf data and really bolting that together to create this holistic collection picture of what are all the assets truly available out there to really understand the situation. That could be miles across the globe. The company that's what I'm focused in, that's the direction we're steering the ship from personal standpoint came up through academia, almost made the pivot in military, got an offer to grad school, end up getting a couple degrees in geography. So really understanding the geopolitical climate of when things are happening like Ukraine, why are they happy? What is the hundred fifty years of history prior to that? Really understanding from a tactical standpoint of history is a pretty good indicator what's gonna happen in the future.

Speaker 1:

Spending a lot of time, you know, trying to Engross myself with as much information, both old and new, and in really I think that is helped me understand, you know, from a strategic standpoint of really look at, is this going to be an activity where we need to really double down and get behind, because this is gonna be a long and during protected event. Where is this something that's gonna be a flash in the pan? Where, hey, we got guys who can cover this, this over here, like the China issue or something like that? You know, I think most of our you we're kind of in a war state today, almost like a cold war I've approached. Bullets are getting fired, but there is a lot of activity happening under the radar, if you will, where I think you have several three and four star commands. They're gonna tell you today that we are at war and this is something of a company we are going to invest in, not because we think there's just this financial boom behind it.

Speaker 1:

No, this is a major, major national security issue. We see that we have partners friends that are partners that are currently in the fight, if you will that have a tremendous amount of need, have a tremendous lack of resource. After spending 20 years fighting in the desert, have it to a blue ocean environment. This is completely different battle for me. Fighting and I quit. Frankly, I think we got a lot of, a lot of work to do to get there. So for us, as a company, this is those kind of regions, those kind of issues are something that we are truly yeah, I think it's a.

Speaker 2:

It's a conflict of innovation, intellectual property investment. It is a war of startups and technology and trade versus a war of bullets and missiles, and that's really interesting. I want to pull out because you said a lot of very interesting things, so I want to pull out some points out of this, and one traditionally, people would shy away from defense because they'd look at it as oh, that's a slow growth market. We're looking at market indicators and the area is only growing at 3% or 5%, so that's not a really good startup focus for us. Now I've found this to be demonstrably false because I know lots of people that have worked at large primes and then just started and have a 10 or $20 million company in a couple of years, which maybe that's not this unicorn story of startups, but that's a very reasonable company to have because they have deep domain experience, they understand the problem, they probably in a past life were the person that had the problem and so they're able to, without a ton of investment or a ton of startup hijinks, create a reasonable company. But from the startup world, they looked at it and said, oh well, that's a slow growth, that's a business environment, it's not a startup IP environment. I think that that's changed and it's demonstrably false.

Speaker 2:

I like your story of coming from the background, understanding the problem and then solving it really really well for one or two people and then realizing that this is a lateral growth opportunity. It's like who else is just like this? What other agency or what other group has a very similar mission but same problem? And defense is really great for that Commercial industry. I don't feel is the same way. I wanted to break that down and if we can dive in a little bit into the tech or what does Royce Geo actually do? What do you provide and what are the problems around that space that you're solving?

Speaker 1:

And our core, our business. We are an advanced analytics firm. We have a very strong IT component as well that supports large mission centers, making sure that the lights are blinking, the computers are working, because we're in the space where the fight is actually occurring today. But what we are really leaning edge on is the advanced analytics component. Now, that's pretty broad and nebulous. Let me put a fighter point on what that looks like. Then you know, about 13, 14 years inside the mission space as an analyst doing geospatial intelligence and tradecraft kind of the good old fashioned way we were doing tasking, collection, bringing in information, making products, rints and repeats. We saw an inflection point around 2013, 2014,. When we were starting to really master how to do accelerated tasking orchestration. What that means is an event occurs, a model is kicked off and then we go and collect something and we were able to do this in near real time. It was being done in very, very, very, very tiny sections of the bill and we're talking water to people. I looked at that as a massive opportunity that, look, this is the way that we're going to stay on top of the evolving landscape. We got to start looking at things differently and that was really the driving force for me to say, okay, I'm going to step out and this is what I'm going to do. Different and this is how we are not going to be just a good old fashioned run in the middle.

Speaker 1:

Intel company that you know, hires great people and provide great value at service on a button seed approach. We want to actually deliver solutions and we want to democratize advanced analytics because, at the end of the day, there's only a handful of people that understood Python or how to build, you know sort of data models and things like that. We want to look at how do we make this open up, the aperture, get more people involved? How do we show that this is something that's truly scalable? And it's taken quite a while to get to that point. We kind of hit that point about two years ago where the light bulb started popping on hey, this is something we need to really get deep and wide within. You know our agencies and community and the DoD, whatnot. So that's really where the business is pivoted in the last couple of years.

Speaker 1:

So again started off looking at advanced data modeling and analytics, looking how it affects agile collection, looking how it affects how to do Intel while you sleep, how do you turn a model on so, as things are being emitted, collected all over the world by various sensors and activities, how are we able to churn that data and make sense of it in real time? Moreover, how are we able to do that when someone's not sitting in front of their computer between 0600 and 050 and 1500, you know business hours? That was the mindset we took as a company and we had some great examples of that. When you know, the world went on its head during 2020. And we had models kicked off and then everybody was sent home. No one was in a skiff for like four or five months in some cases. We came back to where those models ran for four or five months and had troves of information collected while they were never in the building. That was extremely actionable, extremely relevant, and that said Intel why you sleep model? So when we saw this happening in real time, we were able to start taking that capability, taking it to other places, almost right inside of our own major customer base in one of the agencies we report, and we were able to start replicating that, getting them to invest dollars into. Hey, this is something we now want. That office has a great, but we want it now, and so we were able to start replicating that internal within one of our main customers Fast forward. We stepped that out of three letter agency realm into the DoD realm and use that exact same approach. Moreover, we're relying on government systems to do the majority of this work.

Speaker 1:

What we invested in about two and a half years ago almost two years to the day is creating our own commercial solution Again, not to build software to go hang on a shelf and sell the license. We wanted something. We wanted to eat our own dog food. We wanted to create a system that was just like what we were used to using inside the government space, build it on complete commercial tech stack with a very novel language like Python. Everybody codes in Python. We didn't want to have anything obscure than only four people in the world know how to code against, and we built our own tech-enabled solution.

Speaker 1:

And then, with the emergence of commercial space imaging capability or F capability, we saw a real opportunity to show the world we can do the exact same job you're doing sitting inside a skip with highly cleared people, highly paid people. We can show you how to do it with a couple of smart guys, some machine learning experts and some good data analysts young trained data analysts and do it completely in an unclassified environment. And that is exactly what we've done over the last couple of years. So now, present day, we're looking at the national collection layer, the commercial collection layer, and showing how those two merge together to create that complete collection layer. And then, moreover, when you're working with groups that are very external, at the edge, if you will, that aren't getting collection priority, aren't able to see, you know, get eyes on the ground to see what's going on in the world, we're showing them a very cheap, fast and effective way to look at targets overseas that they're interested in, and doing it very economically and very scalable. So that has been really our thrust in the last two years and it's created the identity for what our companies become today. And then, with that is, you know, obviously, all the great things like contract awards and things like that.

Speaker 1:

But in the end, it comes down to your kind of part of your first question why get into this? Well, there's no more or more important mission space than national security in my eyes, and I'm a little jaded because I've spent over half my adult life in the national security space, so really it was the only thing I knew. Moreover, as started really kind of growing this company. You see a lot of great things happening in the pure commercial landscape for other business sectors. We've been able, because we've got tradecraft practitioners and experts, they're able to grab those good parts and pieces that are out there and really show how to tech enable it and make it relevant and useful for the national security space.

Speaker 1:

The big differentiate, when you look at a complete commercial startup and I'm doing this, I'm selling these things in the commercial landscape and now I want to do the great pivot into the DoD IC realm the biggest differentiator, the common denominator, is tradecraft experience and if you do not have that in space, that is a huge bridge across and sometimes you can never do it.

Speaker 1:

And I've seen plenty of great companies out there, great tech, PhDs, smart folks, guys with patents out the wazoo of technology we've all heard of, but they cannot make that transition because, quite frankly, they've never spent a day walking alls, or at least long enough to where they know how to take their tech, price it accordingly, how to implement it in a way that it's you're not swallowing a whale, you're taking nice little bite sizes until you get them comfortable with the solution to then make it work? And then, moreover, how are you pivoting that tech and adjusting what that software and that managed service all really looks like to make it relevant for the mission? That's coming six, seven, 10 months down the road, not just what you knew existed as of today and 12 months prior. And that's one of the things I think that's given us a really distinct advantage, because the technology experts we bring in our practical experts and, moreover, they've got a longstanding history of working in tradecraft and working inside mission space. So that's been kind of our secret recipe.

Speaker 2:

It sounds like an amazing recipe to me. I definitely understand where you're coming from, because we deal with a lot of smart, very technical people, particularly people out of academia, that are going after calls for innovation and just the lack of vocabulary or understanding. This is what a contract would look like. This is how people talk about their challenges. This is what's pertinent to discuss right now versus how to develop that relationship. It's really just not there because it works in a little bit different of a way, but it's nice to see somebody coming out of that space and then leveraging commercial technology. I want to touch on that.

Speaker 2:

Two years ago, building that commercial stack and making sure that you can leverage common programming languages like Python, you feel like that positions you better for now, where everyone is really interested in AI, ml, we have this massive surge in data analytics interest. Whether you call that AI or what have you, we end up getting into a lot of interesting sensor applications and whether it's hardware, software or some kind of data convergence solution. So there's a lot happening in that space, but traditionally nothing would actually occur because you couldn't get data from one place to the other and it wasn't very actionable, and that really has to do with the way things were siloed and built. But if you're running the stack, what was the reasoning for doing that? Did you magician enough to predict the mass growth of interest in AI, or is just like? This gives us the ability to develop our own best-of-breed solution.

Speaker 1:

No, I'm not going to call myself some great fortune teller, but one of the things I knew was always a problem from day one of being in the job over 20 years ago is you've got a scale and automation problem. You've got a tremendous amount of data scattered all over the place in different silos, if you will, and really what tools or what central environment do you have to go and reach all of that data in disparate locations and then process it all at scale in real time Through a lot of novel technology and things that are out there? There's a lot of good parts and pieces out there. What we spent a lot of time doing was bringing all the best-of-breed stuff that we knew and understand together and to execute against missions. For example, how do you look at five different commsat, say, eo and SAR providers? How are you looking at RF? How are you looking at AIS data? How are you looking at all this stuff that's commercially available coming into subscription, oh, and then just scouring the good old fashioned open web for great information. In the past, that was armies of team collection managers, data analysts, data miners, all those things bringing all this stuff together, and you've seen that evolve and get a little more streamlined over time. What we wanted to do is just put the line in San saying we are going to tech enable 95% of this and we are going to build something that we can control the amount of data input. We can reach out to all the number of different data services out there, pull all this together in one centralized location and then, with good old fashioned data science, how are we building real, actual models that can repeat at scale and in real time?

Speaker 1:

I think if we tried to build this five, six, seven years ago the tax act, wait for it wasn't there. We weren't mature enough to do it today, or at least let me put this with the resources we had at our disposal Other companies definitely have, and you know, but they also know better. Back and coming from a different starting point of say that we were, we had to be very mindful and smart about our investment and how much we could really lean into. But we hit this really interesting flexion point about two years ago where, hey, there's a tremendous amount of open source stuff that's out there. The data is coming in waves size of you something in the north pacific. This is opportunity here and we also understand in the mission space what they're asking for. So we weren't trying to create a solution.

Speaker 1:

Then go find a problem. We had a very, very ready big problem and that was how you leverage commercial satellite imagery, run computer vision at our detection, all those things against that, report on that a real time. Now, that's one case study out of probably another dozen that we build inside our what's called curve. That's our environment, inside our curve environment that we get after. The point being is that we now become vertically integrated inside a company where we know how to harness all the commercial data we've got Through our environment.

Speaker 1:

It was to go and get it. We can then process it all in real time and then we can report on real time. Almost 100% man out the loop In some cases would used to be a very stepwise serial process function. We're now able to parallel process tremendous amount of data, use lightweight code, use, repeatable code and, moreover, we've made an environment that we can bring new data scientists into. We show them how to build functions, how to pre program. A lot of stuff already pre T W. They just need to add some secret sauce and then they're off and running within the same day with their own new, unique models to support their own mission set.

Speaker 1:

In the end, we knew that if we were going to grow as a firm, technology was going to be huge, huge part. And then, moreover, machine learning, all those things are here to stay. That is going to become the new normal. If we don't get out of this now as a company, work going to be completely playing catch up the entire time. So we made a pretty hard stance about two and a half years ago. We were trying to be the next dot a company, or be Royce, g, o, the experts. Machine learning no, it's just going to be an active part of what we do. It's not the only thing we do, but it's something we're starting to do pretty well.

Speaker 2:

I think baking in A I is the best approach is. I get into these arguments all the time is people right now they think that I means chat, gpt? I'm a tech guy, right, and product developer tech guy and been dealing with A, I and M for a really long time. But the example I give them is that you have a backup camera in your car, these machine fish, it's in everything it's. There's ten different ways that it's in your iPhone before you install an app. Right, great products bake in technology versus they are just a technology layer, your product and you're offering.

Speaker 2:

It really reminds me of this term that I keep seeing crop up a little bit more and a little bit more Intelligence as a service, and the premise being that the security landscape or the way that people think of remote security and dealing with data has changed enough, where, instead of me siloing out the solution, I'm a big fan of processing information at edge and having actionable intelligence, as you know, as close to being able to use it as possible. But it's not always theoretically something that can be done, right? Not everybody's carrying around transit cases of compute gear and can crunch numbers wherever they are right just is improbable, but the idea of being able to leverage a consolidated resource and then be able to expand that resource. We can spin up GPU clusters like well, I don't want to take that on the other side of the earth and have to like do that tomorrow because of a mission in X, y, z location. I just want to be able to.

Speaker 2:

You know, I'm here in Ashburn, virginia, very figured this data center thing out. Why can't I just use the compute power that I have on prem or right across the street at a secure data center? Why can't I just Spin that up and collect data and crunch it like whatever scale that I need? And this idea of intelligence as a service is like Dave, I don't really care, I just need to get actionable information right. I have a problem. I need to have eyes on target. I need to know how many trucks have gone down this road, or something very simple, and that could mean carting millions of dollars worth of equipment that I can't cart around. Or it could mean just accessing what you have and setting that up and it's really, really appealing. But that has been a really big evolution. Have you seen Just the change in attitudes towards like this is our thing versus we just care about the result or we care more about the result, then we care about the infrastructure.

Speaker 1:

I think the infrastructure piece. We've had a lot of partners that have realized the ability to do things at the edge and in the last, say, three years, went from it bring all your kit, your toys, your big compute, your satellite dishes, all those things you need to be, you know, for the four man fire team that's at the very, very remote edge to now. We know we can mission plan on a cell phone and do some very good things like direct tasking on collection, can run processing, can generate reports on a very low-weight computer environment. And then you've got Thanks like starlink that are out there, you know, internet connectivity worldwide in a backpack, this whole concept of big hardware to small hardware. We've seen a very fast evolution of our partners wrapping their brain around. Right, we don't need all this stuff. We can do this in a small form factor.

Speaker 1:

However, the point which I'm making with Intel is a service. One of the things that we spend a lot of time with educating, you know, our partners on is looking at the buying model, and what do I mean? It used to be hey, we are going to develop a thing. We want to have Intel reporting on this thing, but we are going to manage it under services and we're gonna have to buy data and buy this compute and buy all this stuff. It's like time out what you're buying as a result, right by the result. So let's start pivoting these engagements to more like what we call. You know Furbick's price, to where you're the deliverable. Is this Intel report or this active API? You know generated pushed Intel message report, whatever is going into some command and control center downrange. Don't worry about all the compute, data and man hours involved to get you to that point. You're buying really that every eight hours, every four minutes over the time period, is some sort of report on it, on a detection around the globe. We seem big pivot in that model and that's been part of what we have really focused on as well.

Speaker 1:

Some of the prime contracts we hold today. That is literally the directive. We're buying Intel as a service. We know you'll go and handle the data procurement which, quite frankly, is one of the more expensive parts of that type of mission, especially when you're buying commercial data. And then compute has gotten pretty cheap and then there's all kinds of methods and things you can do behind the scenes to make that more efficient as well from a cost standpoint.

Speaker 1:

And then labor is the best part of this, because when you're working under these like I mentioned earlier, doing this commercial Intel as a service, you can bring in raw, unclear talent, high tech skills Most of the young guys were bringing out of college. They already have Python background, they already got degrees in math. They're very, very sharp folks. But now what we're doing is teaching them Intel. So apply this resident knowledge of coding and mathematics and all those things to Intel and then we're seeing this evolution of you now have a weaponized Intel analyst that's got a deep math and coding background. Oh, and same time we're getting them cleared through other program so they're learning in real time. They're just sitting in a think tank writing papers for six months waiting for their clearance to go through. They're doing real mission mission drop work and getting that knowledge and getting cleared, and then we can take them and deploy them into a mission center somewhere and then rinse and repeat that model.

Speaker 1:

A little bit of a shift from your question, but really wanted to hammer this home is that I think the more that more government partners out there realize that they can get a better bag for their buck at a lower price, with less mechanical nuance from a contract standpoint of just buy them Intel result. Let the companies, let the guys like us really handle the mechanics of what goes on behind the scenes. We're comfortable doing that. We run businesses. At the end of the day we have to manage against profit, but at the end, by that result we will get you said result. And, moreover, what they're finding is that our folks are getting a better result at a lower price, much faster, and that's a win In my eyes. That's a win-win for everyone.

Speaker 2:

I think that approaches a quiet revolution in contracting is thinking about what are we actually purchasing? Who owns this thing? Who's maintaining it? Can we just focus on the end result and then the pricing is more clear and it's much more scalable. It's like I understand. Now I can replicate this without going through a big lift about hardware and services and a lot of the big organizations. They make their money mostly on the services. So maybe there's an argument against that as a business owner, but from an actual needs perspective it makes perfect sense as a service model for intelligence.

Speaker 2:

It seems to be like this quiet revolution, very interesting to put in perspective, and I love what you're saying about getting bright talent in and then teaching them the gap. There's not going to be a school unless they've gone to very particular schools while being in service that they're going to learn the tradecraft piece or the Intel piece. So if you want to get really great talent, you have to like you know where is the thing that I need. If somebody has math and they have coding skills, let's go get those people. Let's filter them for culture, for the desire to tackle this shared mission requirements, like if they're interested in that. This is a way better space to work on than, say, like, tweaking the Facebook ads algorithm. It's probably the same level of intellectual difficulty, but one you're going to be one of thousands of people that just change this way that ads get served to people. Not really much to write home about.

Speaker 1:

We had an example of that. We actually, during the meta layoffs I believe it was last winter that occurred we picked up a PhD in aerospace engineering with a focus on orbitology Pretty important when you're looking at the commercial space layer. And now he's all in on national security. He will never go back to working at a Facebook or an X.

Speaker 2:

You just get to work on more interesting problems, right, and things that where it's clear to find possible impacts. You might not want to post those on Facebook and might not want to post that on LinkedIn, but to me I look at people's CV and X Google, x Facebook I'm like yeah.

Speaker 2:

I mean there's a lot of people that work for those companies of varied talents. But when I see somebody in a very fast growth high technology, intel space, I know that they had to be a very multi disciplinary person and they had to be probably pretty good, otherwise it wouldn't last too long, because it's like high difficulty problems, very interesting problems to solve.

Speaker 1:

Yeah, and the Intel is a service piece. To really hammer home the point I mentioned earlier about, what are you passionate about? You know the people improvement, team improvement, one of the hardest things that not just my company, a lot of companies in our space are getting to available talent. This Intel is a service model really up guns a company's capability of bringing in sharp, unclear folks and getting them that resident experience to where now you no longer have a people problem because you know it's always a chicken egg. You have someone cleared it. They can't get the clearance unless they go through the process and it takes time.

Speaker 1:

This cuts all that noise completely out. Now you're able to use vetted US citizens, put them against really hard problems, get them the training they need, get them cleared in real time. The company is making money, they're not stopped, just an overhead burden. So this whole approach fixes so many problems from a technology mission standpoint. But it fixes one of the biggest problems I think a lot of companies across the entire Intel and DOD sector have is the availability of talent. And by having these type of constructs where you have this unclassified component meets classified world, for a company our size it gets really no better than that.

Speaker 2:

That's amazing insight. Definitely the hardest thing that any growth company experiences is how do I get talent in the door? How do I get the right talent in the door? How do I get the right talent to have the right culture fit and work really well as a team? You can only grow to the same extent that you grow your team right With capability, capacity, not just size. I mean that's probably the most common thing that people look for is how can I get some leverage in growing my company? Is there a better approach to getting talent in the door? There's a really, really good insight for people that are listening. Dave, I want to future pace a little bit before we get out of here. What are you predicting or excited about in the next six, 12 months?

Speaker 1:

I think we're just getting started in the commercial space layer. I think you're going to see other players get involved. Space is hard and expensive. I think it's going to come in different ways and forms, though You're going to have probably more sensors get put in orbit. We know we're tracking a whole bunch of companies that are all planned for 2024, 25 lodges that have yet to put a single thing in there. More is coming. There should be.

Speaker 1:

There's going to need to be a massive boom on ground station and transport to consider how are we getting this information down from space Space Command? Sda are investing a lot of money in that today, with Space Base Combs and getting information to ground faster. I think there needs to be that commercial answer to that. There are already some today. Azure has that. We work on this ground station model and that's opening up. The Azure, if you will, is getting more stuff to ground.

Speaker 1:

I think, as we put more in space, we're going to need more direct connectivity. Why do I mention that? Latency and speed are the critical issues right now? If you take an image and you can't see that image until three to four to six hours to eight hours later, is it really valuable For us it's going to be a direct mission, imperative for the commercial world, us included. How do we figure out how to get that information off the bird down the ground to make decision in that? Some three minutes opposed to some two hours, because that's where the new information is getting it's dominant. You have to have that and you have to have it fast. Right now, we've got partners with branding officers that I need to have Joyce to control the bird. I need to be able to do everything I can possibly do to understand what is going on in a foreign, remote area and their speed is I need it in three minutes. Right now, that is virtually impossible. There's a demand signal there to get that latency compressed. Moreover, there's going to have to be a tremendous amount of technology and new companies that come into place that are really cracking that code To me is what I see is the next big opportunity.

Speaker 1:

We can't really affect what National does. They got their own priorities. They're putting their own assets in space at their speed, and so on and so forth. Commercial has the ability and they've already done it to weigh all of their capacity out of the water in terms of what they can collect an image and look at and listen to on a daily basis. I don't see that slowing down, because when the bullets start flying, it is our opinion, my opinion, that it's going to be commercial. That's going to rule the day. You're going to need more information in the ground and more over, more resiliency, being able to protect that commercial space layer as well, because, albeit it's commercial asset, it's going to be a critical asset when it comes to national security.

Speaker 2:

Yeah, there's definitely tangential problems and opportunities associated with that right. There's the physio cyber layer for SATCOM and then there's the EW problems that are associated with any type of wireless communications. There's a really interesting one that we're predicting is the circular economy or the cleanup requirement, looking at the full lifecycle, which traditionally the space economy hasn't had to address the total product lifecycle. We just let things stay up there as we need the space because the real estate is limited for a number of reasons. That's going to become more and more important is looking at how something is taken down elegantly. Yeah, I fully agree.

Speaker 2:

We've had a couple of friends of mine on the show talking about space economy. I'm really interested to learn more about that. But the same problems that we have in just wireless communications are essentially the same but greatly accentuated. A lot of the data, transport and security layers on that. That's really interesting insight. A lot of movement and companies kind of going after that. I'll probably be on the sidelines of just doing the electronics work making stuff, but I am really curious about that space. Very interesting. Dave, I really appreciate you taking the time to be on the show. Can you give us just a quick insight or words of wisdom to take us out.

Speaker 1:

I get asked a lot by folks that are wanting to try to do what we're doing or folks that have already started growing a business in the defense and tell space. This is a start-up podcast, so I think I should leave it. On a business building note, don't try to do everything. Do the one thing that you're really good at and pour a lot of energy into it. As I said earlier, really understanding the problem, I think, has been a big part of our success, because you only have so much energy you can exert in the course of the day when you're building a company, because you're literally working 80, 90-hour weeks for the first couple of years. If you're going to invest your time, make sure it's something that you really know. You can never be too close to mission. Moreover, probably I would catch some heat from this from our pure chronic guys. For me, I was pretty risk-inverse, which sounds weird. If you're going to start a company but do something that you know that on day one you're going to get paid for, if you can start bringing in just to get one customer to give you $1, that you would be amazed how your confidence and your ability to go and try and do other like things within what you want to be. As you grow up as a company, you'll let your guard down and be more aggressive and go after new targets. We were humble beginnings. I started this whole company with a bonus that I got from my old firm right when I left, which wasn't a whole lot, but it was enough to pay the bills for a month and wait for that first invoice to get paid. From there we grew it as one to two, to five, to 20 to 80 people in the first couple of years. I think in the end it was because we were doing work we truly understood and a mission. We truly understood we weren't trying to build the next novel thing and trying to figure out who was going to buy it. We understood. We really got down to the core of what are the current needs and problems of a customer. We understand and that's all my focus was directed to. From there, everything else took care of itself.

Speaker 1:

Once you get to that point where you've got that good, solid base of that recurring business and paying for the bills and you're growing on a nice clip, start taking some real good risks, then there are very few people in the defense and intel space. I think the list is exponentially longer of those who failed than those that have succeeded on taking those moonshots within that first 12 to 18 months. If you really want to make it in this industry and have that enduring name and one that really is just not flashy tech but it's something that you're doing, something that matters, you've got to be in the mission center. If you're not that person but you've got the need and desire to do something in defense and intel, find a partner. Find somebody that believes in your vision and your strategy, that really can speak all the acronym soup that comes out of the military and defense world. It can really help you translate what is truly affecting mission and then figure out what is those things you're about to build or those people that are going to hire that affect possible change in that mission.

Speaker 1:

It's really not terribly complicated at the end of the day. It's just kind of taking all the external noise of running a company, putting the blinders on, filtering that out and saying, all right, this is what we want to be growing up and not really deviating from that. But how do you know what you want to be? You got to understand the problem and if you do that, then I think the rest it will come. Just put in the reps and back and wait. It'll come to you. That's phenomenal. Thank you again, dave.

Speaker 2:

Hey, callie thanks for your time. Appreciate it. My name is Callie Keen and this has been the Startup Defense.

The Future of Technology in Defense
Data Analytics and National Security Solutions
Leveraging Commercial Technology for Defense Intelligence
Revolutionizing Intelligence as a Service
The Future of Commercial Space Exploration
Commercial Opportunities and Challenges in Space
Understanding and Growing a Company