Industrial Drones:
Cool Tech for Business

Michael Krigsman: Drones, they are a hot topic. Today, we are learning about drones, and we're going to learn everything that there is to know about industrial drones, drones in business.

I'm Michael Krigsman. I am an industry analyst and the host of CxOTalk. Today, on Episode #277 of CxOTalk, we are speaking with George Mathew, who is the CEO of Kespry, which supplies industrial drones and a software platform around that.

First, I want to say a heartfelt thanks to Livestream for supporting CxOTalk these many years. They supply our video streaming infrastructure, and they are great. If you go to Livestream.com/CxOTalk, in fact, they will give you a discount.

I would also like to say thank you to Laura Hoang--I hope I'm pronouncing her name right--from CredPR because she introduced me to Kespry and to George Mathew, and Laura is really great. If you need PR, go to CredPR.com. They're fantastic.

Without further ado, George Mathew, thank you for being here on CxOTalk. It's great to meet you.

George Mathew: Hey, Michael. Great to meet you. Thanks for having me on.

Michael Krigsman: George, tell us about Kespry, and tell us about industrial drones and what you guys do.

George Mathew: Sure. Kespry is an aerial intelligence platform that's been really focused on industrial work, being able to take a drone and effectively autonomously deliver data and analytics that come off the drone into industrial worksites like construction locations, roofing, mining, and aggregates, and now going into the energy sector.

Michael Krigsman: You have a complete platform that includes the drone and analytics. Just tell us briefly about that.

George Mathew: That was always the mindset for Kespry from day one. We were founded in 2013 with the idea that there should be more autonomous capability in terms of drones being introduced into commercial worksites and not only deliver the data that comes off the drone, whether it be imagery and other sensor-based input, but to be able to process that in a meaningful way so that you can derive great analytical applications from the data coming off the drone and other sensors.

Michael Krigsman: What are the components of drones? What do we need to know?

George Mathew: Michael, the way to think about drones at this point are that they are a new sensor network. They have the ability to very seamlessly be able to fly over industrial worksites into broader, commercial use cases where you can easily collect data in an effective, reliable manner. And so, drones can actually make that collection of information in a meaningful way easy, cheap, and safe in particularly these industrial locations that Kespry has been operating in for many years now. Thus, the drone becomes not only a method of data collection, but also just a way of being able to transmit all kinds of new sensory-based input into the way that analytics and models are built for a lot of industrial use cases.

Michael Krigsman: What are those industrial use cases?

George Mathew: Sure. One of the first industrial use cases that we started with was measuring the volumetrics around a mining aggregate's operation. Mining in aggregates, it turns out that you're digging things out of the ground. That's the primary product that you're managing inventory on. To be able to understand how much material you have, you effectively have to be able to do a volumetric analysis of how much material you've pulled out of the ground.

The primary method of doing that previously was taking survey grade equipment, whether that be precision laser guided equipment or being able to take a GPS backpack, climb a stockpile and take 10, 15, 20 points of measurement, and then go back to the home office and be able to measure what those volumes were. What's amazing about a drone now is you can fly over a worksite, a mine site or an aggregates location, be able to take imagery of all of the stockpiles and material and convert those into three-dimensional models. Those models are hyper-accurate because you're taking 600,000, 700,000 points of measurement on a typical site and being able to get a level of accuracy on your inventory that was unprecedented. That's where we started in the industrial use cases that we're serving today by being able to do better and accurate measurement in the mining space.

Since then, we've expanded into topological models for construction worksites around earthworks projects where John Deere is now reselling Kespry drones. We've expanded into the insurance and roofing world where we can do topological models of a roof and being able to assess the damage on a roof from weather events and, more recently, expanded into the energy sector with our recent Series C investments.

Michael Krigsman: I want to remind everybody that right now there is a tweet chat taking place. Use the hashtag #CxOTalk, and you can ask any questions you have about drones and how they work.

George, as I was preparing for this show, somebody said to me, "Well, we can get all of this information just from maps on mining sites," and so how is this different from what people were able to do historically?

George Mathew: Well, historically, there are two changes that drones and other similar sensor-based technologies are introducing into the market. In effect, if you're getting information from a map, it's ultimately two dimensional in nature. What drones are now providing is a level and a view of dimensionality in the third dimension, being able to understand elevation, being able to understand topology, being able to understand the volumetrics related to material that might be dug out of the ground. That capability of understanding the third dimension becomes quite relevant, particularly when you can do it in a super accurate way.

When we introduce precision GPS combined with a lot of the data processing that Kespry delivers into the market today, what's incredible is we can create a topological analysis that's down to three centimeters of real space X, Y, and Z. What you would have in terms of inaccurate two-dimensional maps in your mining site for years is now realized as a fully available three-dimensional topology of that entire landscape as it changes over time. That's where we start to see the benefit of drones and additional sensor-based input really impacting this kind of industrial work.

Michael Krigsman: George, it's interesting to hear you talk about drones as sensor-based technology when I think the layman, such as myself, would think of it as flying, essentially.

George Mathew: Yeah.

Michael Krigsman: And so, what are the sensors when you think about sensors?

George Mathew: Sure. Yeah, no problem. Let me actually introduce our second generation Kespry drone in that context. When you look at what we've built in terms of Kespry second generation capabilities, no surprise there's a visual sensor built right in where there's a high-fidelity camera that can take imagery on a worksite itself. But, alongside that visual imagery that we can take, we have a one-dimensional forward-facing lidar.

The lidar, as a sensor, can be used for collision avoidance, obstacle detection, as well as a terrain map. We can see use cases where, as the drone is autonomously flying on a worksite, you can actually now have the imagery autonomously taken while you can understand if there is an obstacle on a worksite and avoid it in real time. That's possible because of sensor-based input.

On the top, here you see GPS. Precision GPS was introduced into the Kespry product about a year ago. Now we can fuse the data that comes off of additional sensors like the visual sensor, the gyrotometer, the accelerometer, with the precision GPS so that you can get the topological analysis coordinated down to three centimeters of real space X, Y, and Z. This is why I indicate that the drone being a new sensor network can start to apply all of these insights in a combined fashion that you, frankly, couldn't actually do most seamlessly before technology like this was brought together into the market.

Michael Krigsman: I'm assuming that this degree of both accuracy and the types of sensors, for example, the lidar, are among the distinguishing features that are different from consumer drones.

George Mathew: Yeah, you hit the nail right on the head. When you think about the difference between industrial capabilities that Kespry has introduced into the market for ruggedized work areas like a mining location or construction location, you can potentially fly a consumer drone, but the challenge is that a consumer drone will have difficulty being able to be operated on a mine site that's 8,000 feet in altitude. It'll have difficulty in flying in 25-mile-an-hour winds. It has difficulty flying more than 15 minutes, and our drone today flies for almost 25, 30 minutes and covers 150 acres when it flies at about 150, 200 feet in the air. And so, these qualities of industrialized work being accomplished with a drone needs a different type of product in the market than a consumer grade drone that has typically been in the market for quite a few years. This is where Kespry's focus has been in not only delivering that industrialized drone, but also the data processing, the applications that support the use cases that are necessary in the markets we serve.

Michael Krigsman: You think of the drones as, say, the data source, and then you take that data. You do various types of analytics on it so that it can then be used. Can you talk about the types of analytics that you use that you operate on that data?

George Mathew: One of the things that we primarily care about at Kespry is really integrating and owning the physical model of how a worksite and asset area is effectively understood from an analytical perspective. One of the key things that has been a differentiating factor in the market in terms of automating this data collection and being able to generate analytics from it is a technique called photogrammetry, Michael. What I mean by photogrammetry is that you can take the 2D images that are collected off of a drone and, if you have the right overlap available of imagery and the right angle that you've actually captured that imagery, you can convert those 2D images into fully realized, three-dimensional models.

When Kespry went into market and produced some of the first generation of industrial applications, we started with that idea that, first and foremost, generate that 3D model, generate what's known as 3D orthomosaic, and then layer in all the aggregations, calculations, machine learning algorithms, artificial intelligence directly on top of the three-dimensional model. And so, we see this as a very natural progression of how industrial work continues to get accomplished because you just have better decision making that's available because the physical model is now most easily exposed with a level of unprecedented data and analytics that support that physical model to make better decisions within the organizations we serve.

Michael Krigsman: George, there are so many different technologies that are involved in this chain. Can you summarize for us the kind of skills and capabilities that you have on your team, the different areas of domain expertise that are necessary?

George Mathew: This is an amazing part of my experience, particularly being at Kespry for a year and change now. I come from a pretty significant software analytics background, and that's what I'd been doing for quite a few years. Coming to Kespry and learning more about what the hardware systems look like, the robotics, the control systems, the IMUs, the mechanical engineering that we have entailed, the flight control systems that are in place to be able to generate an integrated product like this, it's an amazing learning curve. Particularly when you add the factor that Kespry is now manufacturing our drones in the United States, we now have a manufacturing facility that is producing the drones that we introduce into the market.

It's been an incredible personal experience for me in just learning and being able to understand how converged systems like this can be applied in the industrial world. For the team, it is a very cross-disciplinary team that works on producing the best product for this kind of industrial work, and so we're really proud of what we've done here with 100 people at Kespry today that continues to grow in scale as we speak.

Michael Krigsman: It's a small group of people producing this type of technology with all of the different components. How are you organized? How do you organize the company? What are the teams, the composition of the teams?

George Mathew: Yeah, so when you think about the organization of our product itself, a lot of our product, first and foremost, starts with engineering that's really coupled with hardware and software engineering. Within the context of even software engineering, we really break down that software engineering by systems and control specialists, as well as platform and data specialists and an organization that, of course, delivers the Kespry cloud for a Web application experience for the end consumption of the data that we're delivering. These disciplines are effectively interacting with each other with the help of a product management organization that really supports the timing, the release of an integrated converged solution into the market as we bring the needs forward for our customers by industries that we serve.

When we have an integrated solution that goes to market that we have to manufacture the drone itself, that is really important that we have manufacturing very close to the work where the engineering function continues to iterate as we go through multiple releases of hardware, control systems, and software. The beauty of where Kespry's location is in Menlo Park, we happen to have our manufacturing facility right across the parking lot. Literally, our hardware and software teams can go over and influence the design specification and the production of how we manufacture at any point in time. When we want to introduce another capability set to the current hardware platform, it's much more seamless for us to be able to do that.

As we bring the product into the market, the other pieces of the organization are what you'd typically find in most companies that are focused on delivering technology to typical markets like the ones we serve. There's, of course, a great marketing team. We started to build out a sales and business development organization. We have a customer success team that really manages our customer success and renewal of a subscription-based offering we're delivering into the market. Of course, finance and operations and our HR and talent team continue to support the entire function of really being able to build out and scale.

Yes, it's a 100-person organization, but we're tightly focused in terms of delivering an integrated set of capabilities to our customers. So far, our customers are incredibly delighted by what they receive into the markets that we serve.

Michael Krigsman: We have a couple of questions from Twitter. Arsalan Khan asks, "Are there privacy concerns if your customers are operating the drones near residential areas or they decide to start flying these drones with such precision equipment, precision sensors in residential areas, away from their industrial sites? Are there privacy concerns?"

George Mathew: Yes. The beauty of the introduction of some of this precision capability in terms of even flight control that we've introduced into the market is that even when we fly over a residential location, we can actually construct a flight plan that only flies over the areas that we have full permission to fly over. When both the superstorms hit between Harvey and Irma, we had our drones as some of the first drones that were responsible for the recovery effort, particularly when it came to claims adjudication around just damage that's occurred within the area, particularly wind damage and other weather-related damage.

We were literally flying or enabling our P&C, our property and casualty, insurance carries, as customers. They were flying in this region with catastrophic response teams where they could actually articulate a flight plan that only flew over properties that were under coverage by that carrier and had the explicit permission to fly over it because of the way that the system technology can orchestrate the geofence and the flight area that you would collect the information from. I believe that we have the technology at this point to be able to securely, safely, and with a level of privacy deliver this kind of analytics into the market for the industrial use cases that we really serve. Really, it's about making sure that the person that's on the ground making this decision is, of course, responsible for operating within the guidelines of what is both safe, secure, and private in nature, but the technology is fully there to support that to occur today.

Michael Krigsman: Obviously, you're thinking a lot about the various types of regulations. What are the restrictions that regulations impose upon you or how do you think about these regulations or guidelines?

George Mathew: Right. For commercial drone operation in the United States, there was a watershed moment in August of 2016 where the part one of seven regulations were brought forward by the FAA. The context around part one of seven was it had three pieces of the overall framework. One is that commercial drones have to be operated below 400 feet of airspace. Two, that drones that are commercially in operation have to maintain a visual line of sight to an operator. Three, that any operator would be working in the context of this regulation has to take the part one of seven pilot's exam, which is basically the equivalent of the written portion of a state driver's test.

Once you had that framework in place, what it really enabled the market to operate around is something that just enabled commercial work to be accomplished without wondering, "Hey, is it legal to do this? Do we have the right authority to do this in the proper manner?" The good news is, since the timeframe of August 2016, commercial use cases both for autonomous solutions like Kespry's or just pilots that are manually flying drones for commercial work, have blossomed tremendously because now we have a framework to be able to operate within the airspace in the United States.

Michael Krigsman: With these government regulations allowing commercial drone use cases, it's really opened up the opportunities for investment. To what extent did that spur investment and growth of Kespry?

George Mathew: Yeah. To put it in perspective, we saw, in that period of time, our revenue more than triple because we, of course, had a view of that regulatory framework really supporting the commercial operation of Kespry being scaled up in some of these key industrial use cases that we'd been building up even before part one of seven regulation was effectively passed.  And so, it's been great for us.  If you look at where Kespry's growth trajectory has gone since that timeframe, it's been completely up and to the right.

Because there is now a framework to operate in, we were able to expand beyond our mining aggregates, the use case going into the insurance and roofing sector. We, in that timeframe, also signed an exclusive relationship with John Deere to effectively bring Kespry drones into the market around earthworks construction projects within their dealer network. Most recently with the funding announcement with Series C with Shell and other industrial technology-focused providers being interested in what Kespry is delivering, there's a natural entrée into the energy sector.

I cannot be more delighted with the fact that there was a clear framework to be able to operate commercially within the United States. It's opened up an opportunity for Kespry and many, many other companies in the commercial drone space.

Michael Krigsman: Tell us more about John Deere because that sounds to me like they're looking at their core business model of supplying equipment and saying, "Okay. How do we surround ourselves with an ecosystem that adds higher, greater value to the hardware itself?"

George Mathew: When you think about John Deere's future, they're really considering what the future of that worksite is, the worksite being where the construction effectively occurs and John Deere's heavy equipment is brought into the worksite. If you look at the advancements that have occurred on the worksite, there's a lot more telematic data that are now being used to make decisions on how you would, for instance, conduct an earthworks project where leveling, grading, and getting the topology analysis around the leveling and grading needs to be hyper-accurate.

A few years ago, John Deere introduced a number of grade-control solutions in the market where literally you can bring GPS coordinates and send that to your smart dozer so that, as the dozer's blade is hitting the earth, you can articulate the angle of the blade based on the GPS coordinates that you've been able to send it. The ability to now introduce highly precise topological models, as I mentioned earlier with the use of Kespry drones, was such a natural complement to the smart grade equipment that John Deere was introducing into the market. Really, that's where the dealers within John Deere's network, as well as John Deere corporate, became very interested in not only drones, but the ability to have a drone that delivered a highly accurate topological model that could then be applied to where their smart grade equipment was being deployed into the market. Really, that's where the relationship started this time last year. We introduced it exactly a year ago, and we've now seen an expansion of our technology and product being in the channel of John Deere's dealer network for a good portion of this past year. So far, the uptick has been amazing.

Michael Krigsman: Are you actually integrating with their equipment, or how does that work?

George Mathew: Yeah, so the first phase of the work was to be able to bring the solution together side-by-side where Kespry would be sold into the market alongside the heavy equipment and be data that was generated where Kespry could be leveraged by the smart dozer and additional equipment that was able to receive this kind of telematic, geospatial, GPS based coordinated information. The long-term vision is that the data can be automated in terms of how information can flow directly from the Kespry drone onto the heavy equipment. That's project work that we'll be taking on with John Deere in the not too distant future. But, we're in a good place on phase one in just introducing the core technology and the product into the same market that needs this kind of insight occurring day-to-day on a construction worksite to complement the smart equipment that John Deere has already introduced into the market for several years.

Michael Krigsman: I'm always interested in how new technologies like the drones can impact, disrupt, make more efficient, and bring innovation to established industries, and so I think it'd be interesting to hear more about the use cases that you're applying the drones to and describe how it's changing or enabling new business models.

 George Mathew: Sure. We have always looked at this as an opportunity to change the future of industrial work, and that is a lot of where Kespry's vision continues to stand differentiated in the market. When we've looked at the opportunity to change industrial work, you're absolutely right, Michael, that there are key processes that have been in place as far as the use cases that we serve today that have been a certain way for many, many years. We look at this as a way to say, "Can we improve those processes, or can we completely disrupt those processes so that there's just a better way that the new status quo can emerge with the viability of drones and additional sensor-based input that just wasn't possible before?"

In the example I had mentioned earlier in the mining aggregate space, we went from topological models that were 20, 30, 40 points of survey grade equipment, basically collecting manually, to 600,000, 700,000 points of measurement that were effectively decimated from a point cloud that was generated through a three-dimensional orthomosaic that Kespry was delivering through an autonomous flight plan.

The ability to do that kind of measurement that accurately with a level of safety and the timing that was involved in it was a complete step function change in the mining aggregate space. We look at those opportunities similarly as we've gone into construction where I mentioned the use of topological models being highly accurate within three centimeters of real space to do better earthworks projects.

In the insurance sector, what was really fascinating to see was that the primary mechanism to be able to measure what the amount of damage would be from a weather standpoint on a roof and then be able to make the consideration whether you would effectively replace part or the entirety of that roof was mainly done through manually climbing the roof, taking a ten-by-ten measurement of a portion of the roof, counting the amount of damage manually inside of that ten-by-ten square, and then extrapolating what the rest of the roof would look like as far as the level and extent of damage. That was perfectly fine for being able to get that first generation of claims process in place. If a drone can fly overhead and generate the entire roof model, the entire dimensional model related to how much material there is on a roof and detect all the necessary damage to say that this portion versus that portion of the roof needs replacement, you can actually have a more accurate view of the decision you make of whether it's a total or partial roof replacement. We see that happening today not only in the level of accuracy in terms of that data collection and the decision that's made around it, but the timing because previously it would take a day to get up on a roof and check out the damage on a roof, get off the roof, and take a few days to process that claim.

Well, what if you could actually manage that entirely as a touchless claim within a drone flying five minutes directly on a roof, then process that data immediately, and then giving the adjudicator, the adjuster that's on the ground, the information so that the customer can have their claim processed right then and there? That's a fundamental game changing experience in the insurance sector when you see what the introduction of a drone versus doing it the way the status quo in that market was. Every time we go into these markets, we look for these opportunities to either disrupt the status quo or just simply make it better because the drone can assist the human in terms of the work that's being accomplished.

Michael Krigsman: What about adoption? We have a comment again from Arsalan Khan on Twitter. He must be reading my mind because I was going to ask the same thing, which is, "How do you convince potential customers in these industries that are not very tech savvy and use lots of manual labor to accomplish these tasks? How do you convince them to adopt this new, super sophisticated thing?"

George Mathew: When you look at the industries that we are in, heavier industries where you would think that the technology around these industries isn't as savvy, what we're seeing is a generational shift in the core industries that we're serving today where technology is becoming more and more prevalent. Frankly, technology has been in these markets, right? Let's go back to the mining space for a moment. In the 1950s, there were solutions around survey grade equipment that were using products like the adelite. That was in the market to just be able to enable a surveyor to do his or her work faster. You flash forward into the '80s and '90s, and you see the introduction of GPS-based solutions being introduced. You push forward into the early 2000s, and now you have precision laser-guided equipment for survey grade assessment.

In that market, the introduction of a drone is just a natural extension of the progression of technology that's occurred for the last four to five decades. I think we see that over and over again in these industrial markets. As much as we would like to believe that these markets are not as technologically forward as we would assume, they actually have had technology for quite a while. It's more a question of when these leaps occur in the space, are you ready to provide the right technology and the right solution to serve the market as it progresses forward?

Michael Krigsman: Drone technology, in this case, is a kind of natural progression exactly in the way that, say, GPS. You could almost say inevitable progression.

George Mathew: Well, that's where we believe the market will continue to evolve for the next decade. Drones are a part of industrial work. It's the early innings, as we're seeing these use cases emerge as we speak. But, we think that this is just the way that work is going to continuously be accomplished for the foreseeable future. In my view, it's just a natural progression of how technology has evolved for easily the last four to five decades in particularly these industrial markets.

Michael Krigsman: Well, you brought up the evolution of technology. Where is drone technology going--let me put it this way--drone technology in general, along with the sensors attached to the drones, and then, more specifically, in the industrial market that you serve?

George Mathew: I think where the market has been historically is that you've taken sensors, you've flown over worksites, you've flown over commercial locations, and you've figured out how to manually get insights out of that information. I think that that's where the market will effectively need to have better automation, better data processing, better capabilities to be able to get those insights off of the sensors and make automated sense out of them using machine learning, using artificial intelligence, applying it as an application and a full, complete experience, and deliver a more complete offering into the market than someone just manually flying a drone into a worksite. This is where Kespry has been really focused.

We've never built a solution that even has a joystick. It's effectively built with autonomous capability where you punch in the coordinate that you would want to fly by casting a geofence and then being able to, with your fingers, draw out the area, that you would want to fly, on an iPad, hit the start button, and the drone autonomously takes off and does the work that it needs to do. We see this as a natural automation and set of applications that support the data that's coming off the drone versus someone manually flying, which has been historically what the drone market has looked like.

It's not that the two are in violent conflict with each other. There are perfectly adequate needs to be able to manually fly. A good example is if you want to do a bridge inspection. It's probably best suited by a pilot manually flying a drone to be able to collect that insight. But, if you wanted to look at the shipping containers that might come to a port, if you want to look at the dimensional analysis of a roof, if you want to look at how much the solar potential of an entire solar farm is operating at efficiency, those things can be more naturally automated without having to manually intervene with pilots flying drones. This is where Kespry sees a very viable future for an autonomous solution like we delivered into the market.

Michael Krigsman: You're not out there supporting people taking joyrides and taking photographs of the beach. [Laughter]

George Mathew: You know there are plenty of people that do great work there. We really fully support that amazing work that's been done for taking joyrides, flying along the beach, taking wedding photography. As you can see, there's plenty of consumer and prosumer uses of drones, and we love all those use cases. Many of us are personal hobbyists in terms of the use of drones for these cases. But, at work, we're focused on the nature of industrial work being improved by the use of technology that we're delivering into the market.

Michael Krigsman: It sounds like your future is not just the hardware, but equally or almost equally as much the kind of analytics and data analysis, whether it's graphical data analysis or other types of analysis, on the software side to enhance that data and make it actually useful for the industrial customers who are purchasing.

George Mathew: I think that's the only way it becomes a complete solution in the market, Michael, because if you're just generating the sensor-based input and not driving the insights, not automating the machine learning algorithms, not being able to package that up as a complete software-based application experience to users that are then consuming that content whether that be operators on the ground or decision-makers in the front office, you're not delivering the value that really can be enabled for this kind of industrial work to be fully realized. You're just providing a partial or small sliver of the overall solution to market. This is where, for every use case, Kespry has gone super deep on the use case versus trying to go broad against all of the possibilities where drones could be used today.

Michael Krigsman: It's not just a matter of collecting the data, although, obviously, that's a crucial foundation. But, it's how you are operating on that data, which means then that, again, going back to the skills composition of your workforce, you must have hardware people and then subsets of hardware people--I'm not trying to put words in your mouth--for the various subsystems. Then you've got to have software people, data people, right? I'm assuming, again, going back to that workforce composition question.

George Mathew: Yeah, so think about it this way. We've flown over 40,000 missions for our customers or our customers have flown 40,000 missions, more precisely, using Kespry's end-to-end solution for the last 3 years. Each one of those missions is generating gigabytes of data. All of that data is being fully automated and processed in our Kespry cloud that then is exposing the analytical models, the applications that are supported by those analytical models to users in the markets that we're in.

Yes, it absolutely takes a village of cross-functional capabilities on both hardware and software, and data processing and cloud infrastructure to be able to deliver the end-to-end experience that we do today. That's what makes the mission as incredible as it is. We're an ambitious company going after a trillion-dollar market opportunity in terms of the digitization of industrial work, and we see a lion share of it being able to be descriptive of creating a physical model and using sensor-based input to do it. The more we can go deeper into these use cases, we can capture more of that value in the next decade.

Michael Krigsman: To what extent are your system integrators taking off the shelf components and bringing them together into a solution, as opposed to developing your own technology for each of those source compounds, the many source components?

George Mathew: On the hardware side, we've become very strong at the sensor fusion, the componentry, and the systems integration around that to package this up properly for just a foolproof way, an easy way to be able to deploy this technology into the market. You don't have to have massive expertise in terms of being able to fly and operate. You do, of course, have to pass the part one of seven license; but you still don't have to be an expert in manually flying a drone to be able to collect this information in a meaningful way.

Now, that area, we've actually done quite a bit of what is the systems integration as we've now built a lot of these applications for claims management in the insurance sector, for inventory management in the mining aggregate space, for earthworks topological analysis in construction, and then going into some of the asset management scenarios in energy. What we're now seeing is that data also needs to flow into other internal systems in the enterprises that we serve. And so, we don't wake up every morning and I don't think we're necessarily the folks that are doing the integration from Kespry's cloud directly into the endpoints that the enterprise systems serve today. We're exposing programmatic APIs, REST JSON-based services, so that you can do that integration, or a systems integrator can do that integration, but that's because we believe that there's a strong ecosystem that'll benefit from the fact that this kind of sensory-based input can be processed. The applications and the data, the models, the analytics that are delivered in this infrastructure and platform can be brought into other systems more seamlessly. That's where we think a broader set of friends and members and an ecosystem will continue to support Kespry for the foreseeable future.

Michael Krigsman: I guess, clearly, that is one of the distinguishing features of an industrial drone solution as opposed to a consumer one that's obviously not aware of the enterprise systems.

George Mathew: That's right because, if you're bringing a consumer drone in, you can potentially collect all that data, but then how do you process that? That's going to be manual, right? How do you make the insights possible? Well, you're still going to be going through a bit of a kludgy broken experience. Then how do you get that data into an application that's consumable or a set of APIs that could be exposed to downstream applications? All of that tends to be laborious work that we help effectively prepackage and deliver to the customer base we're serving.

Michael Krigsman: We have just a few minutes left, and there's another interesting question, this time from the @CxOTalk Twitter account, which is asking about data security and privacy, both the drone data that's collected as well as the customer data. You're collecting very sensitive, commercial and, in some cases, I'm assuming very confidential commercial information.

George Mathew: We think about that privacy and security pretty significantly when we deploy our solution into the market, and so we'll look at those two endpoints. In our cloud infrastructure, we've built a multitenant cloud infrastructure that has a fully cordoned off set of privileges and access points so that only customers within the context of that portion of our cloud, our multitenant sort of infrastructure, have access to the data that they have, of course, access to. No one else can see nor have access to that information if they're not part of that tenant.

In the case of the data collection, I had actually mentioned earlier that we've put a lot of capability into the products so that we can precisely collect information without breaking privacy. Even when we're flying over commercial rooftops, when we're flying over industrial worksites, we're flying over residential properties, we have to have explicit permission, and we make sure that when we're working with our customers that that permission is in place. We only fly over the places that we're allowed to fly. We can set up the flight plan; we can set up the autonomy on the drone to just make that possible and seamless so that we're not collecting more information than we should be, frankly, doing when we're actually on these worksites.

We've had that mindset from day one to be able to only collect the data that we're allowed to collect and to only expose the data that's securely delivered on a multi-tenant basis to our customers as they've been able to scale out operations. That continues to be the way that we operate, and so we've built a product and a solution with that frame and that mindset from day one. As we continue to expand customers and industries, we'll continue to operate that way for the foreseeable future.

Michael Krigsman: Okay. As we have about a minute left, what advice do you have, George, for organizations that want to adopt drone technology? They're looking at this from the outside, and they're thinking, "Hmm. This could be useful for us." What should they do?

George Mathew: I think a really well-known science fiction author once said that the future is here; it's just unevenly distributed. William Gibson actually said that. I take that to heart when you look at these opportunities. If you are an individual, a leader, a decision-maker, an analyst, an operator within the context of some of these industrial sectors that we happen to serve, what I will say is that the technology surrounding drones is absolutely here. It's not in the future. It's not something that's a pie in the sky dream that people are assuming is going to come later. It's here now to be able to deliver industrial work in a meaningful way. The more that you just start to learn, start to get yourself educated, start to understand what the possibilities are and to pick people that really have been working in these markets to be  able to deliver complete use cases to the needs that you have in your respective organizations, you will have an amazing experience being able to use drone technology for the future of the industrial work you're doing.

Michael Krigsman: George Mathew, CEO of Kespry, thank you very much for teaching us about drones today here on CxOTalk.

George Mathew: Super fun. Thank you for having me, Michael.

Michael Krigsman: Everybody, you have been watching Episode #277 of CxOTalk. We've been speaking with George Mathew, who is the CEO of Kespry, which supplies industrial drones.

Next Friday on CxOTalk, we're speaking with Aaron Levie, who is the CEO of Box. I hope you'll come back and join us then.

Thanks a lot, everybody. Oh, before I forget, please, please like us on Facebook, subscribe on YouTube, and tell a friend. Thank you very much, everybody. Have a great day. Bye-bye.