 Before I forget, if you want to know more about our solutions, because in 15 minutes, it's impossible to show everything, please scan this QR code. This gives you a possibility to book a demonstration, a trial, basically to have a way to test our software with your real data, so ensure that you have this scanned. So who knows about Topodot? Some hands. OK, two, three, four. OK, not bad. But well, for the ones that don't know about Topodot, we are a software company developing our tools since 2011. So basically, we are a company based in Orlando, Florida. And we have offices in Portugal, in Romania, in Dubai, in China, in France, due to a very specific reason. So we support our customers 24-7. So this is what this community of more than 6,000 users across 700 companies stay with us and, of course, believe that they can enhance their workflow with our solutions. So what Topodot offers? Like I said, we offer a software that provides you a way to produce the foundations of a digital twin at the lowest possible cost. So what does this mean? It means that everyone is working with LiDAR data, with mobile mapping systems, static scanners, drones. Well, everyone is using point clouds. But either you or your engineers well, at the end of the workflow, you need to have a workable data for your road, rail, for your engineering project. So no one likes to deal with thousands of gigabytes of data with millions of points. Everyone wants to have the right insights, the right CAD drawings, or GIS database for their projects. So what we are offering is basically a way to simplify a point cloud to something workable, well, in this case, related to the topic of today, into GIS data. So let me give you some very brief explanation of the workflow. So you guys are capturing the data with systems, like I said, mobile, terrestrial, aerial. And you have point clouds. So this is the first part of your workflow. The second part is when top of that starts. So it's when you start a productive process to extract information from point cloud to get something workable. So related to GIS, to get some polylines, to get some points, and to get some polylines into the R3D. So this is the main objective. So having a productive way to extract insightful data from your point cloud. So top of that offers solutions for managing effectively the data to assessing the quality of your point cloud data before even the extraction. And then, of course, you start the extraction in a productive way. And this is part of a productive process that leads you to be competitive in the market and basically to provide any kind of GIS CAD 3D model deliverable for your customers. So at the end of the workflow, well, you can say to your customer, yes, we deliver digital twins. Yes, we deliver 3D models. Yes, we can deliver any geospatial data from LiDAR point clouds. So the focus of our software is mainly in transportation corridors. So if you are here for indoors, sorry, I have bad news for you. You can leave. Just joking. But we mainly focus in outdoors. So this means streets, roadways, railways. So basically, all of these applications you can run for GIS asset inventory, asset management. Basically, as I said, to extract the relevant information for your maintenance and operations. A quick example, you need to maintain a railway. You need to know where are all those traffic signs. So basically, you can extract them from LiDAR data and have them in your asset management system, basically for maintenance and a good operation. The same related to roads. You can basically have all your paint marks if you want to, for example, run a maintenance project to check what needs to be repainted or not. And basically, it's endless the ideas that you can have here to use LiDAR point clouds to get GIS information. And not only that, but also if I would like to. OK, great. So not only that, but from the point cloud and the extractive data, you can also do analysis and report insights to your customers. So this means that, imagine, you are running a project for a municipality and they need to understand in the road network what needs to be maintained in terms of pavement. So they need to discover where are all those issues and the stresses on the pavement. So this is a tough process to handle with point clouds. But it's a very simple one if you use, for example, the pavement stress analysis, where you will automatically detect all these distresses and report in a simple GIS format data telling your customers where are those distresses, what is the size of them, and where should they focus on their road maintenance operations. So this is just a quick example of the advanced analysis and reporting documentation that you can also perform to your customers using point clouds and top of that software. So well, rather than speaking a lot, let's see some examples. And like I said, well, today is to show you a way to optimize the extraction of GIS data with point clouds. So let's see how you can, from point clouds, extract lines to your 3D, how to extract points to your 3D, and how to extract a polygon. Because if you learn this data set in a shapefile or geodatabase, for example, in an ASRI platform, well, you need this basically for planning, for example. So let's see how to extract the painter's stripes. So you have the point clouds. Like I said, if you are running a mobile mapping system, you also have the images. So with this tool, you can basically select using the intensity of the data and ask the tool to vectorize for you a 3D polyline related to your paint stripes. So either the continuous ones or the dashed ones, basically you get a line from the point cloud with all the information about width, length, et cetera. And from here, you can tell to your customers, look, you have this amount of paint stripes. If you want to repaint them, well, here's some insights that you can use for maintenance and operations. So a very simple process. Like I said, start point, a direction, and that's it. The software vectorized for you automatically. Let's see another line feature example, a guardrail. So you have your guardrail. Everyone knows the shape of one. So you have the curve with region. You can create your own templates. And from here, you can inform the software, look. I want to extract from here up to the end of the guardrail. And you see what's the dimension. So 2,000 meters of an automatic extraction in less than five seconds. And you have the top and the bottom of the guardrail. And this is, well, you are working with the LiDAR data. So this is a very accurate process where you can see those lines automatically placed in there. And while you are surveyors, you are engineers, you are cartographers, so you need to be precise. So quality control is very important in this process. And it's available in every tool. Let's see now a polygon feature example, especially within urban environments. You don't want to vectorize this manually. You want to have your driveways, your ADA ramps, automatically available and ready to be placed in the ground using the point cloud data. Of course, none all of them are similar, but you can adjust them. Again, you have a quality control process where all these assets can be basically transformed from a point cloud to a 3D shape ready to be used in a GIS environment. Let's see another really interesting case. For example, how to get the vegetation for many reasons, security for maintenance, et cetera. So, well, you have, again, millions of points, but you just need the outline of this area. So how to get it? Well, it was even faster. So I could even not explain. So from all this cluster of a vegetation area, you get this line. But look, if you want it in the ground, that's not a problem. The software can do that for you. So you don't need to struggle to vectorize this area, like not seeing it well, et cetera. So the software can outline this for you in an easy way. So this is a really cool tool. And now let's go, well, speaking about GIS, everyone wants to extract traffic signs, light poles, trees, et cetera. So in an automatic way, this tool is identifying in the point cloud any vertical element, in this case, a sign, a pole, a tree. So it's automatically predicting and giving you as the least categorized and sorted by type, where you can just, as a user, click in Accept or skip. Well, you skip the ones you don't want to extract, and you accept the ones that you want to have in your GIS deliverable. So, well, you can understand how tedious is this process. So having a tool that can give all these insights for you in an automated way, well, it's invaluable, right? So, well, what's the purpose of Topodot? And why should you have or use Topodot for this type of applications and not any other software? So simple recap of the workflow. Like I said, you have point clouds acquired by static scanners, by mobile mappers, by drones or aircrafts, et cetera. And you need to have a way of simplifying the point cloud to get something workable. I can bet with any one of you that if you ask 10 engineers to get a measurement, for example, for a traffic sign, like give me the height of this traffic sign, you ask for 10 different engineers and you'll get 10 different answers. Because each one of them will measure from bottom to top in different ways. And even if someone choose 10 centimeters left or right, this will provide different measurements. So you want to work with accurate data, with accurate results. And you don't want engineers to spend time because time is money, you know? And you don't want them to work with heavy data. So you, as experts, as LiDAR experts and GIS ones, you want to simplify their life. So the second part is when you take the point clouds, the images, and you extract what an engineer is asking you. Oh, you want the traffic signs? OK, I can extract for you. You want the paint lines or the edge of the road? OK, I can extract for you. Don't worry, from a point cloud, you'll get a polyline, you'll get a point, you'll get a polygon. So I will simplify your life. And basically, you provide the deliverable. Well, since the topic today is GIS, so you provide the deliverable as an export option from topodot in Shapefile, in Geodatabase, in KML. But not only. Well, today I had the opportunity to make a different presentation. It was more cut-related. So you can also provide DGN, DWG, or just a single Excel file for any engineer to work with this information. So just before end the presentation, oops, I just wanted to give a last insight. Why? Well, I invite you to walk around to see different options, and then to stop by topodot booth and see why topodot and, well, not any other software. Well, mainly because of this. And I can see some faces here, some well-known faces from topodot community. And I think it's the reason why they chose topodot and not any other software. It's due to our break-even point. It's due to the productivity. Well, you don't want to walk around and look for software prices. You want to look around and see where you can find the most productive process. Forget about the software prices. Even us, we are not the most expensive. We are not the cheapest one. But you need to think about how long a technician will work with point clouds to get a deliverable. Because, well, if you have a very cheap software, but the engineer will take two months to get a deliverable, well, just go for another option that makes an engineer work just two days to get a deliverable. So this is why you should think about investing in productivity. Because, well, as any company or as any governmental agency, we need to save time because time is money. It's our public money or it's our private money. And we need to be efficient. So it's why investing in productivity. You can leave any project to high profits. You can leave any company to high returns. So I can say that this is why you should look for top of that. And for that reason, again, I invited to scan this QR code, get your demo, with your existing data, with your real data. Videos are great, but for you to really assess the software, put your hands on it, work with your past projects, and just assess the quality of the work.