Rekor Systems, Inc. (REKR) Earnings Call Transcript & Summary

[Audio Gap] and the inclusion of such information in this presentation should not be regarded as a representation by any person that the results reflected in such information will be achieved. [Presentation]

Please welcome to the stage Rekor's President and CEO, Robert Berman.

So [Audio Gap] time. Those of you that are here in person, and we have, I understand, a rather large group listening and watching us virtually. So [Audio Gap] present shareholders, we thank you always for your continued support. And to those of you who are the company is new to, we hope you enjoy learning about us. So we're not here to just talk about Rekor today. We're here to talk what's happening in the marketplace around the world and learn and understand the emergence of a new and truly dynamic exciting global market. Can you guys hear me okay? So in any event, we're here to learn about the sector, and it's something that we're going to be talking a lot about today. So recognizing the advent of this new sector, a few years ago, Rekor set out a truly revolutionary operating system for the roadways, right? And additionally, while we were doing that, we pursued and we continue to pursue opportunities along the way, but we never lost sight of the vision to build that system. And I'm sure -- and I know that many of you because I know faces that I see here, what the hell is Rekor doing, right? So this is what we were doing, and you're going to find out about what we were doing today, and you'll see what we've been working on, and I think you'll appreciate it. But have to ask yourself why. Why do we keep our head down? Not really articulate this to the marketplace and just work on it. And the reason for it is that change is inevitable, and Rekor believes that it could be part of that change. It could help drive the change. It can help shape the discussion and the narrative around this new [indiscernible]. So to discuss the change and understand what's happening, we're going to have to go back in time a little bit. So this is something I expect everybody here would recognize. It's a 3-position traffic light, and what's important about this traffic light is that it is the beginning of a sector called the intelligent transportation sector. It was invented by a brilliant African-American gentleman born in 1867, whose name was Garrett Morgan, who had a strong conviction for public safety. So in addition to the traffic light, Mr. Morgan invented the predecessor to the gas mask that was called the smoke hood and then the traffic light, and he was all about helping people and saving people and preventing accidents and so forth. So in the spirit of Garrett Morgan, Rekor decided to put its efforts and focus on driving the world to be safer, smarter and more efficient. So when we talk about the intelligent traffic sector, not a lot has happened through most of the 20th century and even up until now in the 21st century. But for decades, there's been a lot of discussion and talk and thought leaders out there saying things like smart cities, intelligent roadways using buzzwords. And we have to ask ourselves, does any of this really happened, okay? The fact of the matter is, no, it really hasn't. There's been some progress, but not to the degree that it could be. So you have to ask yourself, "Well, why? Why were people so aspirational towards this, but why has it not really happened?" And the reason for it is technology. So again, the reason for it is that the technology really didn't exist up until, frankly, just the last maybe few years half a decade. So the introduction of artificial intelligence, cloud and edge-based processing, communications to send data wirelessly, so 3G, 4G and now 5G, the Internet of Things and so forth has made it possible for a company like Rekor to build an operating system for the roadways. And when I say operating system, I'd like you to think about your smartphone, right? It's a platform, you have Android or you have Apple, so it's iOS. It's an operating system. And on it, you have the ability, a la carte, to do a whole bunch of things. We all use tons of them, and you can do what you want with them, and you pay for them as you go. So that's what Rekor has been working on, and that's what we've had our head down and buried in this task of building this operating system. So we're going to share it with you today, and you're going to learn a lot more about it as we move forward in the presentation. I'm going to cover it from 60,000 feet, and then my colleagues here will get into the details. So let's start with the data. So much data, if you think about it, just the data that we all know about, whether it's Bluetooth and other things that are out there. But now you have connected vehicles, you have other crowdsourced data from entities like waves, and you have data coming from traffic providers and weather services and so forth. So you got all this data. But there are 2 types of data. You have, what we call, operational data, which is PII, and that involves a vehicle signature, so a plate, a state, maybe a make and model. And then we have what we call nonoperational data or de-identified data. And the reason these are important is because they both have uses for different cases while they also invoke the issue of privacy, and that's a big thing in our business, and we want to be careful about that. So the ability to have the transition from operational data through proprietary filters into de-identified nonoperational data gives Rekor the ability to do what it does. So like we talked about apps before, I'm going to explain a few of the modules that we have that the platform does now. And we're doing these things today, so you can understand what they are, but we'll start with on-demand traffic view, so that's one. And underneath all of these, there's a whole much more. We're not going to spend time to go through them. But -- then you have cross-agency incident management. And then you have public safety and contactless compliance. So some of you would know that as like uninsured motor vehicles, expired tags and so forth. And then we have real-time traffic analytics, the ability to do things like traffic studies in real time. And then this is a big one out there today about sustainability and green initiatives. That's an important thing everybody is talking about, reducing -- reduction of carbon footprint and so forth. And then just one more, so various commercial use cases. And again, under each one of these, you have the ability to have subsets. And so there's so many more, right? What's interesting about the platform is the data starts to flow in a whole bunch of different directions, and what that does is it makes the infrastructure smart. So there's the aha moment. What we want to talk about are not smart cities, nonintelligent roadways, not smart mobility. We want to talk about intelligent infrastructure. That's something that nobody has been out there talking about. So that's what this platform is all about, right? So intelligent infrastructure, what is it? Well, we think we understood it, but we also wanted to know the market. So we commissioned a study from a global consulting firm that has a very strong practice area in infrastructure, working around the world. And we wanted them to look not only at the competitive landscape so that we can figure out where we fit into this new sector of intelligent infrastructure, but also the total addressable market. This has never been looked at this way before. You can pull studies for a whole host of things around from different thing and call them together and come up with something, but nobody has ever looked at it purely from the lens of intelligent infrastructure. So let me tell you some of what we learned from that study. And I think as we go through the day here, you'll probably figure out who that firm was, so I'll let you do that. So some of what we learn, first, is that the total addressable market for intelligent infrastructure by 2026 is $148 billion. It's a big market. So really big market. The second thing that we learned from the study is that it's an emerging sector with strong tailwinds but something else. It's going to take a newcomer to bring technological disruption to accelerate this market. It's always the new company's folks, right? That's where they come from, it's usually not the legacy guys. So next is that real-time solutions drive informed, improved traffic flow, safety, sustainability and economic development. I mean that's true, right? Because as things move around the roadways, the economy can be affected by it, right? And last but not least, disruptive technology can capture a large part of this new market, right? So who's the disruptor? Where's the newcomer? And is there technology disruptive enough to capture a large part of this market in the coming years. So don't take it from me. Let's hear from the experts on the market, and then we'll come back and talk some more. [Presentation]

Okay. So you heard from me a little bit here. I'll come back later for some Q&A. But today, you're also going to hear from my colleagues, and we're going to hear from our CFO, Eyal Hen. And Eyal is going to speak to you a little bit about the company's growth strategy. We're going to give you some financial information, which I'm sure you would all love to have. And he's going to talk to you about how you might look at Rekor and understand whether or not we're penetrating the market and we're growing as expected into this new and exciting sector. So in addition to Eyal, you're going to hear from Mike Dunbar, and Mike is the company's Chief Revenue Officer. And Mike is going to tell you how Rekor is positioned today in this global market, and how we're going to continue to sell into it and how we're going to accelerate it. And in addition to Mike, you're going to hear from Matt Hill, our Chief Science Officer; and Ayala Rosenbaum, who is the company's VP of Product Management, and they're going to talk to you about products and technology. So with that, I'm going to talk about -- the first speaker we're going to have here, which is Noam Maital, who's going to talk a little bit about the current industry landscape. But Noam's also the founder of Waycare. And before I ask Noam to come up here, I want to talk a little bit about Waycare and the company and Noam's colleagues, right? So it's interesting, but when Rekor set out on this mission a few years ago, we were looking at it through one lens. And at the same time, Waycare was looking at this through a completely different lens, through connected vehicle data and other crowdsourced data. And we were aware of that at the time and knew that to build this platform and truly make it work in today's world that we were going to have to incorporate this somehow. So we had it on our road map, and we thought about it, and we also realized at a certain point that this was going to be very expensive and take a lot of time. So why not talk to Waycare? So we were fortunate enough to be introduced to Noam and his team and like chocolate and peanut butter, REESE's Peanut Butter Cups, right? It works. So with that, I'm going to let you hear from Noam, and he's going to talk to you about where things stand today. Noam?

Thank you, guys. Robert, thank you, and I'm really thrilled to be part of the Rekor team. You may hear that my voice is strained, so you'll have to bear with me. I apologize, good timing yesterday, of course, for my -- for that to happen, but we'll get through it. So I'm going to talk a little bit today about the industry and where we're going, where Rekor is going, building out the next-generation operating system. But before I do that, I think it's important that we take a step back and look at the history and where we are at today in the transportation space. And really, if you go back 67 years, not much has changed in our approach of trying to build more capacity and roads, physical roads met for the capacity and demand of our roadway system. Ever since the 1956 Interstate Highway Bill that connected our country and cities allowed for urbanization, population growth ever since that bill that Presented Eisenhower past, we've been doing the same thing, trying to rebuild our way out of the current environment that we're in. And yet, if I went around every single one of the people in the room, not one of us would think that's actually neither economically feasible nor does it make sense for us to do that. We spend over 97 hours stuck in traffic today on our route. But it isn't just about traffic and congestion. It's also about safety. NHTSA, the National Highway Transportation Safety Administration, just released their quarterly data around traffic fatalities, showing a 10% increase from last year. But what's alarming is if you look at last year, it saw the sharpest increase in fatalities per mile driven since 1926, 1926 which is the first year they started actually measuring [indiscernible]. So you guys get the sense that the industry is broken and [indiscernible] today -- can you give me yours? So let's look towards the future. When we think about the future of mobility and transportation, immediately, we think about autonomous vehicles. What that implies in terms of utilization of vehicles on our road and increasing that, what it implies in terms of improved safety. So one of the leading causes of fatalities related to traffic accidents is human error. But I think more exciting and more imminent to us is the advent of connected vehicles, meaning vehicles that are connected, OEMs are connecting them off a lot. Because what that allows us is to start having data that's coming from these vehicles, and essentially building out a digital infrastructure, moving away from that cement I talked about alone and the physical infrastructure to a digital environment. And perhaps even more important than that, it introduces an entirely new model for how we manage and operate our roadway system. Moving away from what we have today, which is a one-way communication system, an agency or a government will have a central system, communicate out to infrastructure, traffic lights, let's say, and then to the human. And that's the end of flow of data to a 2-way communication system, where the vehicle is sharing information into a centralized system, and then that information is fused together with the infrastructure itself, and information is sent back to the driver, and that cycle continues. And that small yet tectonic change has a lot of implications because now you can start using AI for real-time optimization of your roadway network. But also, perhaps also more importantly, you can start using deep learning and predictive analytics around proactively allocating resources and mitigation related to safety. And that's how we get to a place where not only are we utilizing the existing infrastructure in the best way, we're also making the best decisions on future investments related to infrastructure. All of this fits -- all these moving parts come together in the intelligent infrastructure industry. And when you think about it, I talked about the crumbling infrastructure and the current state of that environment. If we talk about the rising congestion, today, cars and congestion are the leading cause of greenhouse gas emissions in the U.S., and that's only increasing. A little more nuance but important to know is really the movement towards cloud and government, which I know is like 10 years after the rest of the other industries, but still this is happening from necessity because as connected vehicle and other third-party data starts to become important as part of the digital infrastructure, government agencies have to scale up and build in the cloud, which they can't do on-premise. And then finally, we're at a really unique moment in time where there is bipartisan support like never before for revitalizing our infrastructure and investing in that in a way that we haven't done, frankly, since President Eisenhower in 1956. And all of that is driving this TAM that Robert was talking about earlier, looking at $148 billion by 2026 with an over 16% CAGR over that time period. And that's just looking at the market structure today. As I started talking about that 2-way communication system, there's going to be a lot of new services that evolve from this market evolution that we just don't know or think about today that are not baked into some of these assumptions. So I spoke about the industry, took us back in time. Let's look at the current systems. So if you were to step into a traffic management center, for example, this is what you would typically see, an operator looking at 6 different monitors. If you have a headache already, it's understandable because I don't know anyone that can do their job this way, 24/7. But this is the environment that we're operating in today: silos of data that are mainly relying on the infrastructure, systems that are built with hardware and software entanglement, so they're patched together don't allow for interoperability and mainly regional agencies. So when you talk about transit, law enforcement, traffic management center, each one of them may think of themselves as having their unique mission. But when you take a step up and look at their overarching mission, really, they share a core mission of getting us from point A, point B safely and efficiently. And yet, they don't have the technology tools they need in order to interoperate and collaborate on that. And so Rekor is really setting out to disrupt the status quo and reimagine what that next-generation operating system needs to look like. For starters, it has to be an open architecture on the cloud from inception that thinks about how you ingest data, not only from the infrastructure, the sensors, cameras, traffic lights, but also from the environment of connected vehicle, from third party, from navigation apps, any other data source that's coming from the outside. But as importantly as that is the ability, as you ingest all these data sources and fusing them together is thinking about how multiple agencies can interoperate seamlessly on one platform to allow for better workflows and impact around safety and congestion management. And all of this data in the cloud and using the data together has to come with technology to automate a lot of very manual processes today using AI and other technologies to really build on that to allow for more streamlined and automated operating system. I want to click one more in on the data because I talked -- you heard me talking about connected vehicle data. Perhaps it doesn't register the magnitude of change that's happening today right underneath our feet. When we look at our current customer base and we look at the infrastructure data, the sensors and other devices that are installed in our typical roadway, we're collecting about 6 gigabytes of data per day. When we look at the same customer and look at the connected vehicles, vehicles that are driving around, third-party data that we're collecting today, looking about 276 gigabytes for that same period for that same day. That's over 46x more data coming in on the roadway system. Now just think about what you can do with that data and the richness of it, we will hear more later from Ayala and Matt about. But if you were to take this to agencies, really what's happening now is that the transportation agencies are drowning in data because they don't know what to do with this. The data is meaningless to them and just massive amounts of it, and they don't have the systems to turn the data into the meaningful solutions. And that's the key here is how do you leverage artificial intelligence and advanced analytics to turn these massive amounts of data that are being processed and streamlined in real time into real workflows around incident management, congestion management, interoperability between the agencies working together and sharing information out to the public. And that's the core of what Rekor is focused on in building out the operating system is how do we enable these agencies to take advantage of this tidal wave of data that's coming their way. And to do that, we're driving today impact for our customers. So whether it's around safety and reducing incident identification time with our automated incident identification by over 9 minutes, whether it's around greenhouse gas emissions and reducing clearance times by over -- close to 10% or if it's around improving the registration of uninsured drivers over 41,000 with using optical sensors. All of these are KPIs that are critical in building -- allowing us to build the relationship further with our customers to build out that next-generation operating system in the years to come. But it's also KPIs that the agencies themselves measure in terms of how they look at their ROI and funding mechanisms coming down from the federal, state, local agencies and how they show the benefit in the ROI for their taxpayers. So let's hear more about the technology, and we'll show a short video on that. And later on, we're going to hear from Matt and Ayala a little more about some of the technologies and services that we're offering today. Thank you, guys. [Presentation]

Please welcome to the stage Rekor Chief Science Officer, Matt Hill; and Rekor's Vice President of Product Management, Ayala Rosenbaum.

The Rekor platform is a uniquely modern solution administrated largely [ AI ] technology. If you think about the last decade or so, all the new types of data that just didn't exist before, things like connected vehicle data. As you're driving most likely, your car is collecting data from different sensors, it's pulling that into statistics, and it's uploading that to the cloud with actually even knowing about it. Same thing with your smartphone, various apps do the same type of thing. They upload this data. There's also incident reports. So people report there's an accident or an incident on the roadway. So all of this information is available now. We can use it. And yet this industry, for the most part, still uses things like rubber tubes on a highway to count cars. Rekor is unique in a number of ways. First of all, we use a combination of cloud and edge based processing. And by edge-based, I mean we have devices out on the roadside, and we have local AI acceleration chips on those devices where we do the computation. We're also open and agnostic. We try to pull in as much data as possible from as many different sources as we can. Because the more data that we ingest into the system, the better the algorithms become. We use these AI models in the cloud that they take the data in, and they love data. The more data we can feed into the system, the more insights they can provide, the more accurate it is. However, our customers tell us the opposite. They say there's so much data without something processing all this information, it's -- you can't keep up with it. There's connected vehicle data. There's incident reports and navigation apps. It becomes a distraction because no human could deal with that level of fine granularity data. So what Rekor does is we have a data-driven approach. We use AI and neural networks to process this information and condense it down into something that's useful. Legacy approach might be something more rules-based. A rules-based approach is sort of -- you have hard-coded thresholds, and you say, "When this data do this, we do this output." It tends to be very brittle and not very accurate. It just doesn't -- it just can't possibly handle all the different variations in data, so it tends to fail or provide low accuracy. The way we approach it is we train the software on real incidents with real data. And what that does is it allows the models to learn how the data operates and the interrelations between the data and the subtle ways that one piece of data might affect another. So sometimes multiple data types come together and they give you stronger or weaker signals. I can give you an example of one case, connected vehicles, and you see a car, slam on its brakes, just one car. That's probably nothing interesting because that happens all the time, people hit the brakes. But if you see multiple cars, all slamming their brakes roughly at the same location, that's a lot more interesting. Something is happening there. Now if you combine that with another data type like accident report. So somebody said there's an accident here. We see multiple cars slamming on the brakes, that's a very strong signal that there's an accident on the roadway right now, and somebody needs to take care of it. If instead of an accent report, it was a speed trap report, then obviously, that's just normal behavior people tend to do that when they see a cop slam on the brakes. So that's nothing that the operators need to be aware of. So that's the goal is we're taking all of this data, we're condensing it down and we're producing insights, actionable insights. So what's great about the system is it's live, it's running in many different states and cities. Our customers are using it right now. We take the inputs, we condense it down and we give them a list of events to say, "These are the things -- from all this information, these are the things you need to look at right now." So what's great about is there's -- they're actually using it. So they're taking this data. They're clicking a button for every event and saying, "Yes, this is a real issue, or no, this is a false positive." And we take that information, we use it to retrain the software, which makes it smarter. So this feedback is absolute goal because there's no other way to collect it without having a real system inside their processes with that data. So we have a real event. We have the corresponding data, and the network then learns how the data relates to each other, and we might find new inferences or reinforce existing understanding of how this data means that there's a real incident on the roadway. So that's the end result is we're able to take all this data and rapidly alert our customers about issues that otherwise they might not be aware of. And we're also filtering up the noise. So they're not distracted by all this extra data that they can't make sense of. One of the ways that we collect data is through the use of an optical sensor. Optical sensor, it's a camera. So we have a camera on the roadway, and it has an AI hardware acceleration device local to that device, and it processes the video locally. So we call it the sensor because it is replacing these legacy sensors. If you think about those rubber tubes that are counting cars, you can do the exact same thing with a camera and an AI model that looks at the video and counts the cars. But you can also do a lot more with that same camera. So you can count the cars. You can also have a different model that might look for the make and model of every car that passes by. You can say, "Well, how many of these are cars versus trucks versus motorcycles." We also have a cool feature that takes a signature of a car. And then we can match that with some other reading from some other cameras. So we can say this car was here and then it was there. So from that, you can figure out rough flows of traffic. Now what percentage of vehicles entered the roadway here and exited there. So it's really valuable data, all from just this one camera. The way we deploy it is we have the device and it has the AI acceleration device locally. And all that processing happens right there at the edge, which is great because you need high-resolution video data to do all this. And when you talk about high-resolution video data, that also means a lot of bandwidth. So all that data has to flow back to a data center, typically, which means you need electricity, you need fiber, you need infrastructure, which takes time to set up and it's expensive. What we do instead is because we have that AI device local, we do the processing. We condense that high-resolution video data down into metadata, and then that small amount of data can be uploaded over cellular. So all these systems requires is a solar panel and a cellular connection, which means they can go virtually anywhere, and we can scale it very quickly. So I'd like to hand it over to Ayala to talk about how we also integrate with other data.

Thank you, Matt. So in addition to the proprietary optical sensors that Matt just described, we also integrate with the existing infrastructure of our customers. Things like CCTV systems, digital messaging signs, inroad sensors and everything that is already being utilized and installed for our customers. On top of that, we also integrate it with a very wide set of third-party partners that brings us data about weather events, about construction zones, probe data and of course, connected vehicle data. And now let me pause a little bit about connected vehicle data because it's quite different than the other data sets that we integrate with, mostly because of the amount of data that is being generated and collected from the vehicles. We talk about -- when we talk about connected vehicle data, we need to emphasize that by the end of this year, Rekor expects to receive data from 3 million vehicles. And this means around 28 million trips a week, which sums up to 2.5 billion data points a day. This is a massive amount of data in our technology and infrastructure already supported. And as the market grows and more and more smart vehicles are being introduced to the roads and being used, this amount of data will only get bigger. And by the end of next year, we expect to triple the amount of data that I just mentioned. And in addition to the huge amount of data that are arriving from connected vehicles, the type of data is also changing and progressing. If -- up until very recently, we received information about the location of the vehicle, maybe the acceleration or the speed. These days, we receive very granular and rich data sets, things like the usage of the windshield wipers, and when they're on and off and even the fuel amount -- fuel level of a specific vehicle at a specific point of time. All of this information help us to create in Rekor what we call the virtual infrastructure that help -- that complements the existing hardware infrastructure that is installed and used by our customers and virtual infrastructure that is already being used -- the virtual infrastructure that is complementary to the existing infrastructure that is already in use by our customers, and it helps them to lower their dependency on this infrastructure and move forward to the new and more innovative space. Now these third-party integrations are not only one-sided. We also send back information to our partners. So we not only receive the data and analyze it for ourselves. We also -- every insight and alert that is being created in the Rekor platform can be sent after back to our partners and give value to the users -- their users as well. And now let's talk a little bit about the network of partners that Rekor have. We created one of the widest network in the market, and it keeps getting bigger and growing by the day. We integrate with traffic management systems, like Econolite. We integrate with the OEMs like Volvo. We integrate with connected vehicle data aggregators like Otonomo, like Wejo and Geotab. And we also integrate with complementary data sets, partners that give us information like tomorrow that brings information about weather, very granular information about weather, and even Ticketmaster that allows us to understand where there are events that are not happening exactly on the road, but can affect traffic heavily. So we all know that if there is a sports event or a big concert, congestion is built and traffic is affected, and all of these help us to understand and create the most accurate a view of the state of roads in real time. And then this view help us create very innovative and unique features that are based on AI. And I'll let Matt talk a little bit about these AI features and specifically about video recognition capabilities.

Yes. So just more generally about AI, the first thing I want to talk about was the way AI works is it's typically used to train just one task at a time. So when we're talking about AI models, they're generally just doing one thing at a time. The way we train them is we take an input and we give it a known output. And then we train -- the training process kind of helps it get from A to B. So to give you an example, if we were training an AI model to do make model recognition, what we'll do is we'll give it an image and we'll tell it that, that's a Ford F-150. And then in the training process, that adjusts the weights in the model to get to that output. And then we do it again, we say, well, here's another image, and that's a Toyota Corolla. And through training, it updates the weights and biases to get to that output. And we do this over and over and over again on millions of images with many different permutations. And eventually, if you do it right, you end up with an AI that can answer the question, given any arbitrary image that you've never seen before, what's the make model of that car. So using the right using the right techniques and using good clean data if you do a good job, often you end up with a model that can outperform a human. It's not uncommon. So how that relates to visual recognition? Typically, what we ask when we're designing these models is if a person were watching a video stream, you showed them a video of the roadway, what kind of things could they infer from that video? What kind of questions could they answer? If you ask them to look at this video, what could they see? So the first thing about video data, especially high-resolution video data, it's very, very dense. There's a ton of information in video. There's grades of color and shades and edges. There's so much data in there. If you do the math on a high-res video clip that's about 4 billion pixels every minute flowing over an optical sensor, it's a ton of information. So what we're trying to do is take different AI models and train them at certain tasks so that we can condense that high-resolution video data into things seen in the video. So we take the same video, but multiple different models, all looking for different things at the same time. For example, we might have a model that watches a video and count the cars that it sees. Another model at the same time might be looking for pedestrians and seeing if they're on the highway or for bicycles and seeing if they're in the right lanes. Another model might be looking at something completely differently, looking at the weather to see if it's raining, if it's sunny or for traffic patterns. So that concept is we're taking that same video, and we're using different models to infer information about that and condense that high-resolution video down into just metadata that is very valuable and describes what we're seeing. So we take all that data, we upload it, and then we combine that with other data, and that's kind of the process we use to combine visual recognition to make intelligent roadways.

And in addition to visual recognition, we also have our incident detection mechanism. We take a lot of different data sets like incidents, speeds, weather events, detours and construction, everything that can disrupt and affect traffic. We train our model on historical data and then use real-time feeds in order to identify incidents that are happening on the roads. The system, after identifying, alerts our customers and users about these incidents in order for them to verify and respond to them. Our product, our incident detection mechanism, identify events much faster than other solutions in the market and much more accurate on their location. And this helps our customers to reduce the time it takes to identify an event by average of 9 minutes. Now every minute, a freeway lane is blocked due to an incident result in 4 minutes of travel time -- travel delay time. So you can only imagine how much time is being said by alerting about these incidents so fast. And we not only identify incidents faster, we also identify more events that are being identified without our solution. Our customers in average identified 21 more -- 21% more incidents than before using our solution. Now identifying events is working very well to the current workflow of our customers. What they do today is that they watch cameras and try to identify and find events that are happening. They also wait to receive alerts from police or from people that witness the incidents on the road. And only after an event happened, they can be reactive and respond and mitigate the incident. But if we want to improve the safety and the efficiency of traffic, we not only need to respond to events that already happen, we also need to prevent events from ever happening. And this will help our customer do by our predictive analytics. We have an algorithm that identify high-risk areas in real time, but also in advance. We alert our customers about the specific segment of the risk of having a crash on a -- in a certain point of time is very high. So our customer can allocate resources to that specific point and try to prevent events from even happening. And now taking all of this or all of this come together in one operating platform, and it's serving multiple missions already. Our solutions are already bringing huge value for many, many use cases, from TLC operators, traffic management centers personnel that are using our smart connect solution to identify events, to respond to them and to collaborate with other agencies to highway patrol forces that, as we just mentioned, can allocate resources based on our predictive analytics and prevent events and also communicate and collaborate with other agencies about incidents happening on the road. We also bring our Rekor One solution that is being used by national parks to count vehicles that are entering and exiting their sites and in general, brings analytics of these parks and public safety agencies that are using our Scout solution to identify vehicles and do investigations. But all of this value, you don't have to trust me, I'm leading the product. So of course, I think it's great. Let's hear it from our customers and see what they have to say about the value that Rekor brings to their day-to-day job. [Presentation]

Please welcome to the stage Rekor Chief Revenue Officer, Mike Dunbar.

Good afternoon. Thank you for joining us. I recently joined Rekor as Chief Revenue Officer. My background and passion is about taking innovative product into emerging markets. So I'm thrilled to be joining at this exciting time in the company's evolution. As the video, we just watched, demonstrated, we have a strong technology platform that not only aggregates data but provides key insights and actionable information to our customers, that results in solutions and outcomes that make a big difference in day-to-day operations. The end result being safer, smarter, more intelligent infrastructure for our communities and cities. Our hardware software products and solutions are deployed across the globe. Over my right shoulder, you're looking at a map with the shaded areas of where we're deployed and executing new pilots and proofs of concept. There's major hubs in the U.S. in states like Nevada, Oklahoma, Florida, Ohio and New York. Internationally, we're doing some really interesting proofs of concept and pilots in countries such as Mexico, Canada, Brazil, Sweden, Israel and Australia. So that geographic footprint provides us a fantastic opportunity to upsell and cross-sell, not only additional products but additional data services. So it wouldn't be surprising if I told you that we are going to execute a land-and-expand strategy in our go-to-market. The strength and the immediate time to value of our product and solutions give us great confidence to do pilots and proofs of concept as a means to enter new markets. Once we're into those proofs of concept and the client sees the value in their operational context, there is literally 0 churn. And that results in longer-term contracts where we have a chance to innovate and develop solutions to problems that, that customer did not even envision at the initial time of sale. And of course, that increases upsell opportunities and the total contract value over time. That puts us in a position through our thought leadership and technology advancements to become a true trusted adviser in those accounts. The result is long-term stickiness and strong retention rates. This strategy has proven to be successful time and time again. This slide, you see a sampling of our customers. Towards the bottom, the new pilots improves the concept we have in play. But again, that process of initial pilot, moving to multiyear contract, moving to contract expansion and on into trusted adviser status. You witnessed it in the videos, we're able to aggregate data from multiple sources and use our innovative software to solve complex day-to-day problems in our target markets. We have very strong adoption rates past the pilot or POC phase, which results in long-term revenue growth opportunities. Again, it's the stickiness and the contract expansions that we see play out time and time again. Very specifically, 2 examples. In Nevada, an initial pilot $30,000 resulted in a 5-year $5.3 million contract that was signed this year. And we're continuing to innovate in that account. Similar situation, I talked about Florida being a major hub, both on the public safety side as well as the incident and traffic analysis side. In that situation, a pilot, $50,000 has resulted in a $1.3 million spend. So for those of you that are doing some quick math, that's a 161x and 26x increase in total contract value over that period. So where are we going to go hunt? Well, our market research says those large governmental entities that benefit from roadway intelligence are the most likely targets. Those are your departments of transportation where real-time traffic analysis and incident management are key. It's also additional government entities like large transit organizations that may have a multimodal planning challenge. And of course, commercial use cases, EV charging stations, real estate planning or even the larger architecture and engineering firms. So as we continue to collect data from our sensors, we'll find ways to monetize and remonetize that information over multiple use cases, that concept of one sensor, multiple missions. So on that note, I'd like to introduce our Chief Financial Officer, Eyal Hen, who will talk about how this particular go-to-market strategy will impact the company from a financial perspective.

Thank you, Mike, and thank you all for being here today in person and virtually. Isn't this exciting? I know I'm excited. It's a great opportunity, and I'm very proud to be part of the Rekor family for the last 2.5 years and go through this journey to be standing right here and present you with this new market, the intelligent infrastructure. So ladies and gentlemen, let me tell you how you guys will be able to measure and monitor Rekor's success. In the near term, we plan to execute on our land-and-expand strategy by capturing additional geographic markets, which we can monetize over time. So how big is this market? As you heard before, we engaged a well-known global consulting firm to define the address -- total addressable market for intelligent infrastructure. The results were astonishing. So how big is this market? As you can see here, this market in 2026 is over $148 billion. I will let you think for a second, $148 billion. That's the total addressable market. So as we expand our footprint, we are well positioned right now to capture a growing share of this large $148 billion market for intelligent infrastructure over time. In fact, out to 2026, we believe our revenue growth will reflect only 50 basis point, only 50 basis point. What is that in dollars? As you can see here, $740 million by 2026. Again, I will let you think for a second, $740 million by 2026. That's how big the opportunity for us. We also anticipate our gross margins to be between 70% to 80% by 2026. That is how big is this market. That's how big is this opportunity for Rekor. So you saw a lot of slides today. Really, my heart with you. And you show the total addressable market. Now I'll show you our expanding and evolving business model as we launch into new markets with our operating system for intelligent infrastructure. We now have a recurring revenue model, which will provide long-term value for the company and its shareholders. These are the benefits of this recurring revenue model. The first one, for the long term, we will have a predictable recurring revenue stream. This will provide greater visibility into our performance and create stability over long term as we expand our geographic footprint and customer base. Second, a recurring revenue model will also provide our customers a greater flexibility to choose their desired solution from a web-based platform with lower upfront cost. And last, we are taking a customer service-focused approach here. The one thing we keep hearing from our customers is that they are drowning with millions of data points and tens -- from 10 data sources, sometimes hundreds of data sources. But what our customers are really looking for -- really need these days. So they are looking for solutions. And solutions -- and Rekor is already a trusted partner for our customers because Rekor provide them solutions. And the solutions that Rekor provide them help them and help the world to be safer, smarter and more efficient. So you have to think about our future revenue stream this way. We gain advantage by implementing pilots. The pilots then become contracts. The contracts expand over time, and the end result, Rekor is a trusted partner for this customer. That is our business plan beginning now and in the future. So if there is one slide I want you remembering from this day is this one. So I'm sharing with you today a road map that you can use in the future to measure and evaluate our success. Here are a few KPIs that you will begin to see in our third quarter public filings, which will help you to measure the growth and market penetration of Rekor. The KPIs that we'll be providing include: number of markets that we serve, and we'll define markets as well; total performance obligation, which is an important one for the recurring revenue model; total contract value from customers, the last is recurring revenues annual and quarterly. This is how you will be able to judge that Rekor is a great investment. In our future public filings throughout the next 12 months, we also will add more and share with you more KPIs on the trajectory of our success and grow and enhance the visibility into our progress. So future KPIs will be average revenue per customer, lifetime value of the customer, revenue per square mile, churn rate and a few more as we expand our footprint. In summary, as I started here, I'm very excited to be here today, and I'm very excited about our opportunity and look forward providing you with additional metrics going forward. And with that, I'd like to bring back Robert on stage for some closing notes, and I look forward to answer any more questions in the Q&A session.

Death by PowerPoint is almost over. So we got through it. Why Rekor? Why now? I think it's a good question to ask at this point of the presentation. And I want to remind you about the beginning of the conversation when we talked about the report that we commissioned. And by now, you probably figured out that it was KPMG. When they looked at the competitive landscape, we found that there is, to the best of our knowledge, no other company in the world that has all the capabilities that Rekor has, especially now given our combination with Waycare under one roof. We can't even find anybody that does half of what we do, right? But it's happening. It's happening. If you look around and you see some of the data aggregators with connected vehicle data and others, this whole industry is just bubbling up, and it's right at the precipice of coming over the top. So the second thing that I'd like to remind you about is we talk about this being a strong industry with emerging sector, strong tailwinds and a large and growing TAM. We also talked about the fact that the study showed us that it was going to require to accelerate technological disruption from a newcomer. We're not saying that, that's what the studies told us. And where does that information come from? Talking to potential customers, experts, thought leaders and others about what's happening with transportation around the world, and that's what they think. They think that there needs to be a disruptor out there to help this all happen and to accelerate it. So -- and last but not least, we're out there doing this today. Mike showed you our geographic footprint. I mean, look, the company is fledgling. Don't get me wrong, right? But we're not just talking the talk, we're actually out there walking the walk. You heard it from our customers. I mean those were multiple customers, different use cases across the country, okay, happening right now using all this data, using our technology and going where they're basically showing you where this is going, right? And this is just the beginning of it. So that's why Rekor, why now, in addition to the fact that it's a huge market and it's going to continue to grow. And this company can certainly be a leader without any question. So with that I think we're going to take some questions. We have some time. And I'm going to ask Noam and Eyal to join me back up here on the stage, and we won't keep you too long. So we'll take questions from the room first. We have some help out there. And then we're going to take questions from our friends in the virtual world because there are a lot of them that have been patient, listening through this whole presentation today. So I need somebody with microphone. [ Jody ]?

Great job. You spoke a lot about your customers on the state level, the DoTs, et cetera. Can you talk about the upcoming infrastructure bill if ever gets passed and how you see you guys benefiting from more federal outlays allotted to the antiquated bridge and highway system, how do you capture that?

Sure, I'll take a stab at that. So under this administration in general, one of the things that they're trying to do already, and it's going to happen as well, I think -- I'd expect it to happen in the infrastructure bill is not trying to repeat. So as they're calling it build back better, everything that's going to be related to building new bridges, new roads is going to be tied to a technology element. So they understand that if you put down cement, you're going to have to tie it in with the technology solution along with that. So what does that mean? For example, you're building another mile a road, you're going to have work zones. Traditionally, you just put dumb cones around that lane and call it a day, and that will be the next 1.5 years of construction. Now they're starting to change requirements in the program that are going to have -- require that development to be with digital cones, connecting into cloud around permitting systems, et cetera. So all of these -- all this funding mechanisms flowing down, yes, it's going to have capital components around the physical infrastructure, but almost every single project that's going to flow through, we expect to also have some sort of attachment on the digital front and requirements related to climate change as well, which also is going to require measurement. So what's the impact of that and the constructions and legacy environment today has no way of even starting to look at that. So that's why also there's a lot of interest already today gearing up to what's to come from the typical construction design build companies that are approaching us and other technology providers in the expectation of what's to come in terms of the larger funding bills flowing down to the states and other municipalities.

Just a couple of questions. The first one, just if you think about the life cycle of a contract. You start with a pilot, put up cameras, collect the data, then come up with a strategy, a solution for them. Is that the kind of the revenue driver of the model in this Rekor One platform? Is that the way to think about it?

Well, in most cases, it starts with a pilot. And depending on the use case of what solutions somebody is looking at, the pilot can last for perhaps a year. In public safety, we've had pilots last 30 days that have grown into significant contracts, right? So the module, public safety, contactless compliance, customer usually knows what they want. When it comes to more an incident management time with those things, then maybe Noam can tell you a little bit about what they look there with regard to the solution.

Yes, I think there's 2 components, operational and procurement. So on the procurement front, the more you're able to cross that threshold quickly, you're able to build on that without having to go back to it. So even if it's a pilot and it's a lower budget amount, you do 2 things at once. One, you allow operators to start using a system, and it's a very sticky industry. So once you build the workflow, for example, incident management, you're no longer selling the product when you're looking at the expansion, it's already an operational system. The second piece of it is once you cross that procurement threshold, whether it's through RFP, sole source or other, you don't have to go back to it. Essentially, there's mechanisms that allow you to do -- associate certain budget items but not necessarily come back to full procurement. And so these are kind of mechanisms that you use to build from what would be a pilot stage onward to a contract, multiyear your contract. And then later on, I think you heard Eyal and others talk about the trusted partner level where as they're building out towards this future, and I talked about some of the frustration of the amount of data, then the use cases just open up and you become the kind of go-to trusted partner on many of these different opportunities.

And then the -- just a financial question, there's confusion about a shelf that was filed on Friday. Does the company need capital right now? And -- or is that just a normal...

I'm sorry, did you ask about the shelf?

Yes.

Okay. So look, the company is shelf eligible. We had a shelf prior, right? We filed a shelf last week, obviously. And the reason for it, [ Casey ], is that there's a lot happening in this space, and it's literally moving in real time. And there are so many changes every day and so many different things that you never know what's going to pop up. The company is not looking for capital. The company is not going into the market to raise capital. But in the event that something might happen where there's an opportunity where the company needs capital, perhaps for some M&A and other things, then we just want to be prepared. So it's as simple as that.

Okay. And then last question. I did a meeting with Wejo yesterday, and they were talking about all these OEMs are getting involved and taking stakes -- financial stakes. Is that something that like having a strategic partner to become involved with you like you guys?

So say the last part again?

Would that be interesting to have like a strategic partner kind of validate the model and the data kind of that you guys are...

Yes. So we -- part of why we built this data partnership, and Wejo is a good example, where we work with them closely, some of the OEMs that we work with closely as well: a, is they're building out a marketplace of data, and we are the solution provider for a lot of that data source, right? So there's validation on both sides for us together as we go to customers saying, "Okay, not only here is this massive amount of data that's very interesting from the Wejo side, but also here's a solution you -- that enables you to actually take advantage of that." And that's why we have a really strategic alliance. Same thing for the OEMs, but a little bit different, where I think for them, they look at what does the future of mobility look like? Today, when we drive in our environment, realistically, it's a one-way communication system, as I talked about, and they're looking for how to build and design systems of the future, and yet they don't have the capable technology partners on the government side that they know they need to connect to the infrastructure. And so they see that in us in terms of being a strategic partner, not only to look at how we take advantage of that data, but also bringing data back into their environment as well for the drivers and building the services model more that they're looking at on the automotive side.

Matt Pfau with Blair. So I wanted to ask a couple of questions on the data providers, which you just discussed a little bit. First of all, how reliant are you on those partnerships for the Rekor-Waycare system to work? And then secondarily, is there any risk around any one of those partners having ambitions to move beyond just being a data aggregator and getting more into the application business like you guys are?

That's a good question. So I think we'll split the answer between us. So the interesting thing is that half of Rekor, okay, with optical sensors using the platform that we've built, we're data provided to ourselves, right? So we're using analytics and video stream to capture tons of data that we can then use AI, panelize and create solutions for a whole host of things. So we incorporate that data into our platform as well. As far as third-party providers, I'll let Noam answer that.

Yes. I think, first of all, you may have heard us use the word agnostic, which is really important because we work with multiple different data providers that provide different types of data sets. I like to use the analogy of a puzzle where you may not have all the pieces of it. If you have 80% of it, you know what the final result is. Similarly is how we think about that environment, too. So the reliance on the data partner is we have strong data partners, some of them that work closer with than others. But I'm new to the public markets, for example, just being acquired from a private company. But the first thing you learn in the investment is diversified. And so the diverse set of data sets and partners that we have allow us to both look at the markets that are relevant and have a multitude of data sets. Robert spoke about optical sensors, they -- many times, they serve as duplicative in a good way to the data partner enabling AI to have further confidence. So the answer, I guess, is if you would have certain data partner reliance on one or the other, we have inner ability to leverage other data partners as well.

Okay. And then specifically like thinking about maybe the traffic management or smart city components, what's typically the catalyst within a city that would get them to perhaps bring you guys in and start to evaluate some solutions there to get smarter about solving their traffic issues?

I'll take that. I think there's a few, but I'll touch upon the main categories. One is, safety is becoming more and more prominent. So traffic management boils up in the end to politics as well, right? If you're in a city or locality and you're a mayor or run an agency, when you have fatalities and there's growing numbers like this, you need to do something about it. And the current systems aren't cutting it. And so they're starting to look at what else can you do in that environment. The second thing is the natural evolution of a decaying legacy infrastructure. And when I say legacy infrastructure is not just the roads, but 20-, 30-, 40-year-old systems that are end of life. And so they're coming about into new procurements, they understand they need to build out new systems and then they're looking in the market, and they don't want to redo the same thing. So that's a catalyst as well, where they're looking around and they're asking us, "Okay, how do we leverage AI with disconnected vehicle? We know it's relevant, but we don't know how yet to -- we don't have the solutions to build around it." So those 2 together typically combine can be a host of various other catalysts as well.

Got it. And last one for me, just on the 2026 targets. Are acquisitions needed to get to that revenue number? How do you think about that?

Sorry, what was the question?

On the 2026 revenue targets, are acquisitions needed to hit that? Or how do you think about the target that you put out there?

No. As I emphasized, it's only 50 basis points from this total addressable market. And as Noam said, the problem will be additional features that should come into this market that we don't know about. So it's not related to acquisitions, additional acquisitions. It's really only 50 basis points internally that we anticipate to get there.

It's been very informative so far. I'm going to ask a question that, I think, everybody wants to know the answer to. I don't know how much you can answer it. But can we talk about Mastercard?

Okay.

Kind of where we are with Mastercard? What kind of a real opportunity that is for you guys on a revenue basis?

Yes. I'm happy to do my best to answer it. As I said...

Okay, broad strokes.

No, no. Fair question. As -- when the presentation started, we talked about the fact that we've been working on a whole bunch of strategic opportunities while we were working on this platform. And Mastercard was one that came to us. They reached out looking for a vendor to build a solution that they had proposed for the fast-food industry that I am -- I guess, I can tell you that they're still working on. It's a work in progress. They are piloting it with a number of different restaurants, and we are working with them with those pilots. But it's Mastercard's product, so we're subject to their rollout. We're subject to their determination of when they think the product is ready for scale. I can tell you that they've had no issue whatsoever with our technology. There's a couple of folks in the room here that are on calls almost every week or every other week with Mastercard. Most of the tweaking that they've been doing has to do with other technology now related to what Rekor is providing. So the other piece of it is that we do have a contract with them. So it's not kind of a lucy relationship where if they move forward, perhaps it will be with us, perhaps somebody else. So we've worked out pricing. We've worked on scale pricing, and we're sitting, waiting for them to tell us that they are ready to scale. As far as what that opportunity could be, there's 270,000 drive-throughs just in the U.S., and their solution is a complete rebuild of the drive-through itself. So it involves a smart menu board. It involves AI for predictive ordering, so to speak, and involve vehicle recognition to help accelerate cars through the line and so forth. And I believe that their data science has showed them that this solution that they're selling is making the restaurant more efficient as well as making the customer experience better. So we're hopeful. We're waiting for them to tell us if they want us to go scale, and we'll gladly go do that. And they're also looking at this globally, right? So people know our pricing, and it's an old subscription model of one of our products. It's a $300 a month sensor that, depending on the number of lanes you would have, you can just do the math and then it's a 5-year contract, so it's like $18,000 over 5 years so. But we'll have to see, again, we're not in control of the product. So we had way of knowing whether it means something significant or whether it means nothing. We just don't know. But thanks for the question. So I think perhaps we're finished with the questions in the room, and maybe we can take some questions online. Charlie, are there have any online questions?

Yes. The next question -- next 2 questions come from Mike Latimore, and Mike is with Northland Capital Markets. Mike's first question, what is the most likely deployment model over the next 2 years, replacing legacy or overlaying cloud on top of legacy.

It's good question. You want to answer it.

I mean I hate to give him a diplomatic answer, but I think both. You're going to have cases where agencies will have an appetite to do an entirely new deployment and that's going to be in the cloud at scale from the get-go, and you're going to have agencies that are just trying to catch up with their existing systems. As I mentioned, they have to move to the cloud. If they're looking to partner with the likes of Wejo and other data partners, you can't do that on-premise and then their overlaying cloud environment. And we're doing already today center-to-center kind of interfaces with APIs and their existing on-prem with the cloud environment. In this day and age, it's pretty easy to have that hybrid model so long as you're able to push information back and forth in a streamlined fashion between both systems. But I guess it's going to be a mix of both of them.

Mike Latimore's last question, what limitations are there when legacy infrastructure remains in place?

What limitations of the legacy infrastructure remain -- I feel like it's a trivia question. A ton, I mean, the limitations of the infrastructure itself is the fact that you have to think differently than the way that we've been doing things from 1956. It's all the way to the basics of inductive loop sensors, which today, if you look across the country, you'd find that many of those inductive loops, which are the ones that count the vehicles under our road are not working. And yet agencies have nothing to do about it because you've got to rip and replace it. So this is exactly why I think there's a bipartisan movement right now like never before to do something at a scale that we haven't seen. And so I think part of that is going away from moving from the model of the legacy to the digital. The good news on that, I'll say, and maybe if Robert wants to add on it, but the digital infrastructure we spoke about here is not reliant on the legacy infrastructure, meaning you're not for something to happen on one front in order to move to a digital infrastructure environment. It's already happening. If I were to ask -- I mean let's ask how many do you guys have a phone right now in your hand, right, or on you? Everyone. So that is part of the digital evolution that allows us to not be reliant on the infrastructure itself.

The next question comes from Zach Cummins at B. Riley. What sort of revenue contribution should we expect from Waycare for the rest of this year and into 2022?

So. This morning, we published the 8-K with Waycare results for 2020 and the first 6 months of 2021. Obviously, we do not provide any guidance. We cannot disclose any future revenues for Waycare, but we anticipate the growth that we saw in the first 6 months will continue for Waycare going forward.

The next question is from a shareholder, [ Brian Carrigan ]. Brian asks, does the $740 million in revenue in 2026 assume any revenue from commercial applications. i.e., Mastercard? Or is it strictly from the TAM and infrastructure upgrades identified by KPMG?

The projected revenue, the goal of 2026 is strictly from the thought that we can get to 50 basis points of this market, right? So that's $740 million. And we didn't include any other contribution from any other program, be it something with -- someone like Mastercard or things that we continue to work on. We're working on those things every day. And mind you, a lot of those projects that we worked on helped us get the technology to where it is today so that we could build this platform, right? So those things were -- they were necessary.

The next 2 questions are from Zach Cummins at B. Riley. Can you speak more about some of the assumptions that were made for the 2026 financial targets?

Yes. So again, I will repeat on it, it's 50 basis points. Obviously, we look on the CAGR, the 16% -- over 16% CAGR year-over-year from 2021 to 2026. We look on the different applications this study looks at, and we thought what will be our penetration rate for this TAM, only this TAM without any additional revenues. And as we mentioned before, it's only 50 basis points.

Zach Cummins' final question, can you speak to the existing cross-selling upsell opportunities between Rekor and Waycare?

Yes, I'll speak to a few, which is also part of why kind of joining forces with Waycare makes sense. When we talk about traffic management, for example, which is -- was a bread-and-butter solution for Waycare continues in the Rekor family, really, it doesn't stand alone in a silo. It's about how you work together with first responders, service patrol, maintenance crews, transit. And so we're working now with all of these agencies, building out modules for the first time, and I think first in the market, allow for interoperability between them. And that opens you up directly into cross-sell opportunities with law enforcement, which we have contracts with; with towing companies, which we have contracts with; with maintenance divisions, which we have contracts with; service patrol. And each one of those are cumulative. But as you build them regionally, they add to the stickiness of the customer because it's a one-stop shop in terms of your ability to allow for interoperability of multiple different services working together.

How will the go-to-market strategy evolve over time with Waycare now in the fold?

I'm going to -- Mike?

So we're already looking at the Waycare team as the Rekor team. And I think we're looking at pipelines together, and we're seeing customer bases on each side of the equation start to cross-pollinate. So I don't I think very soon, you won't see a distinction between what a Waycare customer or a historic Rekor customer looks like. It's that simple.

And the final live stream question comes from a shareholder, [ Lee Schwartz ]. Are state contracts going to continue to be the focus of the business? And if so, how are you planning to address privacy and surveillance concerns that will arise from arguments in state legislatures on both sides of the aisle?

I'm going to answer the first part of this, and I'm going to turn it back over to Noam. But I think that part of the secret sauce here is Rekor's ability to take operational data, which is where most of the concern comes from, which is, again, what we call PII and convert it by running it through a privacy filter into de-identified data, but at the same time, giving it a unique cash so that we don't lose on track of that asset or vehicle, right? So that's the first piece. I'm letting Noam answer the second piece.

Yes. I think just it's something that's top of mind. So we went through a process while at Waycare becoming SOC 2 compliant, the process will continue, and that ensures kind of best-in-class in terms of how you treat data, what are the processes of how you address it, how you treat non-PII. And for us, we -- when possible as it relates to the traffic management side, oftentimes, you don't need the PII. And a lot of that removes away some of the privacy issues. So if we know a vehicle was in a crash, not necessarily for that me to know who is in the crash, but rather know of the event itself, and that helps alleviate a lot of the privacy issues that before they even come up. Same on the data network side, we work with our partners. So as the data is coming in, we're typically not pulling in the PII. We're receiving unique identifiers for vehicle attributes but not necessarily private information that would flow into our system.

[indiscernible] it happened to me just [indiscernible]. Are you able to share with us why [indiscernible] milage you're actually evolved [indiscernible] velocity? And what we expect to hear over the next couple of months?

[ Bert ], I think what we've tried to do here today, and hopefully, everyone has an understanding of what's going on here, there is this emerging sector, okay, that I believe a lot of the large investment banks don't fully understand yet, right? And that's why we commissioned KPMG to go out and look at it. So we know what the market is going to be. And we understand what our KPIs are and how we can measure and how you all can measure it. And the best that we can do is commit that by the third quarter, we'll start providing the KPIs that Eyal had up on the slide and then add additional KPIs as we go through the next 12 months. And that's a normal way to measure a company like this. So if you have the KPIs and you have the TAM and you see the company's penetration, you should be able to model it out and figure out whether the company is succeeding or not, right? And there are a number of companies out there that were built this way and have been very successful, and I'm sure you can find them. And they all see this land-and-expand strategy and how to build platforms and geography and other things, but somewhat of a similar, maybe even a SaaS model. So are we -- we're done. Okay. Well, look, thanks, everybody. This is a lot of time, and really appreciate your patience and all those of you that are virtual again as well. So I hope you learned something about what we've been learning for the last couple or 2, 3 years. And I hope this clears up for those of you that are shareholders and loyal shareholders and supporters why we've been doing what we've been doing and now maybe it's a little more light to what Rekor has been up to, and you'll be able to follow as much better as we go forward in the future. So we're excited, and we thank you again for coming.