 I'm from a company called Cebo Labs. We're basically a data science and remote sensing company. So we established ourselves in the marketplace two years ago, but really that was about sort of 10 years in the making. So the usual story of basically where you have a lot of these companies. We might be young, but we've been in it for a while. And I suppose something that's actually quite differentiated us as well as we really, there was a lot of groundwork done basically before we hit the market. And basically pretty much the first day we turned the lights on, we basically had clients that were actually paying for work. So actually we haven't been taking any venture capital money. We've been basically growing the business organically through real customers with real revenue, which is a nice way to be doing it. I suppose when we first started the business, we were really focusing on things specifically to do with pasture biomass and land condition assessments. And our primary clients are really the corporate agricultural, the corporate pastoral companies. So we really got to start with some confidence and some trust from some very large corporate cattle companies in the north. But over the last couple of years, we basically started to, that we've been doing multiple pivots as we're going, but still the core is really our core pastoral monitoring business. So those issues around climate variability, we found ourselves monitoring floods for pastoralists in the north. We're now working with retail companies. We're working with processes. So this whole issue is basically about how we actually get a better understanding of the value chain. So a few years ago, basically our primary client was basically with the individual producers. And now we're actually working with processes and retailers actually who are supporting their producer network. So how do they actually manage their supply chain? How do they manage their supply chain risk? We're actually starting to work with retailers and processes basically about that. It's just transitioning with that. I'll just change that, but I'll try it one more time. So I suppose we've seen some shifts basically in terms of the awareness of the supply chain. And we're also starting to be doing a lot of work basically at the industry level. So I suppose as a small company, we've found ourselves now working with individual producers. And we're delivering about 20 million hectares of individual pasture by, individual paddock pasture biomass data every week now. So that's a lot of data being delivered directly to producers across the country on a weekly basis. But we're also basically working at the other end of the spectrum with the industry and contributing to things like the beef sustainability report. And there's actually a sheep sustainability report coming along as well. And I want to touch on that as well. So I suppose we're working from the individual paddock and then actually right to the other end of the spectrum at the industry level and everywhere in between in terms of how we actually get the producer connected basically back through that supply chain and the processes and the retailers. So I suppose in terms of the core things that we're doing in terms of the value proposition. OK, I'll go back to where I was. OK. So things around basically kilos per hectare. So there's been many, many years basically working around estimating pasture by mass. And remote sensing hasn't done a terribly good job of that in the past. Working at things like how many grazing days we have in the paddock, issues of land conditions. So estimating ground cover within a paddock and across the property. And how is my ground condition, ground cover changing over time? So looking at both the production perspective as well as the land condition perspective. I'm going to touch on that as well as I go. Now I suppose in terms of the, this is a bit of a messy slide but I suppose in terms of how individual companies and producers interact. I think there's been some comments here earlier on about basically about we've got lots of people sort of trying to throw apps at producers. And I suppose we find ourselves in that place as well. But when you've got a producer that basically has to do things like do biosecurity plans and other things. They've got to be working with their processes. They've got to be collecting data in the paddock. And there's now other efforts basically at play around sustainability reporting, particularly in the beef industry. We've now got a number of mechanisms that are basically trying to develop accreditation systems for the beef industry. So how do we actually have information flowing basically for an individual paddock level at that biosecurity level right through to how do we report across the whole industry. Basically from a paddock effectively to the nation and even things in the middle there basically around individual animal recording. So that market is actually developing quite rapidly. So what we're doing is things like using ENVD technologies to develop basically a blockchain systems for registering and authenticating onboarding properties to allow them to flow effectively information through that information chain. So things around pasture biomass, looking at changes in land condition over time. Tree cover, it's not an issue here but basically we're doing a lot of work in Northern Australia around tree cover, monitoring and demonstrating to the marketplace that producers actually are looking after their landscape and we're getting into carbon accounting as well. So we actually want to make sure that we've got systems in place that allow a producer to walk down that value chain and to be able to talk to other systems along the way. And so it's not just CBay Labs actually doing that. Just wanted to quickly touch on some of the technology perspectives when I'll dive back into how we're using it. So I suppose there's been quite a few slides on that but I suppose in terms of the last five years, particularly the last three years we've actually obviously had a big shift in technology capability. I was a post-grad student in 1987. I thought we were gonna solve the world's problems with airborne video and within a few years I thought we're gonna have basically everyone basically having satellite imagery so it took us, it's taken about 30 years for that reality to really come to the fore. But we really have reached a point in time here where the data is not the problem anymore. It's actually how we actually get people using that information and how we actually get that information synthesized is the issue. Now we can access, and we've got Tim Neal here. Tim's delivering high resolution imagery to individual producers. The fellow of the service guy earlier on was doing the same thing. And we've got the ability to monitor the whole of Australia every five days at 10 meter resolution using 13 band data now. So data is not our problem anymore. It's how we use it and how we integrate it. And just to give you an idea here, I mean this is sort of where past us from space was only a few years ago, 250 and 500 meter resolution pixels and we're now basically able to image an individual property at 10 meters and see individual tree canopies basically on a weekly basis. So some of the sort of things that we're working on I'm gonna dive into just a little bit of technology here for a minute. Onboarding properties, processing data. There's an enormous amount of data available here now. We've developed an on-demand, on-the-fly processing system which basically allows us to process images in the browser and actually throw thousands of CPUs at an individual computing problem. So just for example, here we've actually got the whole of Australia worked to produce a biomass index map in about less than about a minute. So we've actually accessed 3,000 satellite scenes sitting basically in a data catalog and in about a minute or so we've actually been able to access those, apply a biomass model to them and produce a map of Australia. And we can dive in here, I was doing this last night. This is a million, basically 100,000 square kilometers. That's about 10 million hectares. You can see the individual parcel, sorry, the individual property boundaries here. This is a pasture biomass model running across the Northern Australia. In about a minute, that 10 million hectares there, I was able to process that whole area and then you can see down here at the individual property level, the level of variability here. So that's happening basically in a minute over about 10 million hectares. So just actually just mentioned there as well, in terms of the accuracy, we've got thousands of sites, so this does not happen by accident. We've actually got producers all around the country and we've got Tim Prance here, one of them helping collectors collect data. We're basically trying to develop an army of producers basically across the country, they're collecting field data for us. I'm gonna show you that a little bit more of that in a moment. But to get across 10 million hectares and basically produce about, you're able to produce a product on the fly within a minute or two. And here's an example, basically here's the whole of South Australia. So this was about 11 o'clock last night. Very happy to grab a laptop and show you here, basically live. So there's an image there, the whole of South Australia that basically was produced, a multi-spectral image there. It was a two week image, so taking 15 day image, looking at the median spectral response over a 15 day period for the whole of Australia and that took about a minute to generate basically for the whole of the state. And I'll just dive down here, sort of just zoomed into this area here. Happy to show you that working on the fly later on. So that's all sexy stuff, or sexy to me anyway. It's really about how we actually then start to integrate that. And at the core of it, so all of those things I was showing you a minute ago, it's all on the left hand side here. It's really about how we collect the data. So we've got mobile apps that we're using, we're using lots of plate meters data and I don't know why plate meters haven't been used more in Australia, we're using plate meters to estimate pasture biomass and calibrate data. We've got mobile apps that we basically are giving to people to do visual estimates and collect data basically in the field. Yes, we've got some fancy machine learning in the middle here and it's getting faster and faster all the time. It's quite typical for a given week for us to find a 10 fold increase in the speed and accuracy of a model in a week. Basically where some new techniques of the machine learning sort of capabilities are just effectively going through the roof. And I suppose one of the challenges for us is to ensure that we actually have a full understanding of the technology as it moves forward. But we typically, very often, I'll basically, we'll be sitting there in a week we've actually increased the throughput of processing by 10 fold, just by doing things a little bit smarter. Now at the other end, Pops basically intelligence for producers. So basically working with other service providers to deliver online and in the paddock solutions. I'm gonna show you that in a second. So here's just a quick example here. Who's doing pasture biomass assessments here on a regular basis? Penny? Two people, okay. But what this allows us to do, just imagine, you know, if I wanna get out in the paddock and I spend, I do about 50,000 kilometers a year basically driving from basically central Queensland to basically South Australia on a regular basis, doing pasture cuts. I've got gear in the back of the truck, plate meters, clippers, pasture cuts, going into hotel rooms and sticking grass, in the microwave and drying it during the night. They must wonder what's going on in a hotel room for the next day. But just imagine here, if we basically, anyone that's going in the paddock, we can give you an open source mobile app. We can give you something, you can take your five minutes to load it onto your phone. It basically, you can take a picture, GPS reading, walk across the paddock doing pasture estimates. Every time you press the button, if you're in mobile phone reception or as soon as you get home, it actually hooks up to the cloud and basically dumps that data, the pictures, everything into a database. And if we actually had every one of you in the room here that was in the paddock doing that, we could be generating thousands and thousands of basically of sites. Basically, I don't have to leave Toomba as long as often as I do at the moment. And this is sort of the work that we're doing with Tim and others just to try and get that sort of that, the data that we need to drive these models. But I've got producers that can be 1,000 kilometers away and I'm sitting there basically analyzing data and as they're in the paddock and pressing the button, I'm actually seeing records coming into our database. And typically if they need it, we can actually have a model actually built for the property basically the next day. Calibration of plate meters here as well. So every pasture type is different and so you can't just presume when you're using a plate meter that basically it's going to be the same all the time. Different pasture types, different seasonal growth stages. So we're spending a lot of time building libraries of data for plate meters, lots of cuts. So I suppose this is sort of what the front end looks like. We're a data science company, we're not trying to produce some front end where it's been millions of dollars building front ends because it's a very costly exercise and also for every front end you build, it often reduces your capacity to integrate and collaborate with others. So we're really focusing on, yes we've got to have a front end, but we really are focusing on how we integrate with other systems such as AgaWeb, MyaGrazing and others. So basically on a five daily basis, so I might just, I'm not sure I'm not going to basically click here and it's buggered up a little while ago, but I'm going to give it a go anyway, why not see if I can get some web. Okay, so there's a little web interface there. So it's the 19th, it's a few days ago. There's an estimate of basically, there's basically the multi-spectral imagery. This actually works on my wallet to just sit in here when you've got people in front of you. A fractional cover image, you can actually also see here that we're stripping out clouds and doing cloud detection and cloud shadow detection as well to make sure that we're actually the imagery that's coming through as clean. NDVI at this time of the year is absolutely useless. So there's a lot of people who've been using NDVI and pasture systems. It's actually, it's completely valid in cropping systems where the crop is obviously green. In this case here, we've got basically, we've got brown pastures and NDVI just does not work in effectively outside of peak growing periods. And then we've got our machine learning model which is actually predicting pasture biomass basically on a five day basis. And then we can get estimates of kilograms per hectare there and the total tons in the paddock. In the paddock name, you can see that I'm just clicking around. This property here is highly drought affected. You can see here the numbers down in 300 kilos per hectare. So it's obviously in pretty poor condition at the moment. And then we can also produce a traffic light map. So every five days they get a traffic light map of basically where their pastures are at, plus the reds, the lowest and greens the highest. This starter here, any individual paddock in here, it's a real time feed straight into AgriWeb there as well. So that number in there goes straight into the AgriWeb app. Get back to here. Oh, very good. Okay, I just wanted to quickly, just as an example here at the other end of the scale here, this is half a million hectare property. We've basically got grazing circles there. So that's a three kilometer and a five kilometer grazing circle. We've got the paddock boundaries and the land types. We can zoom in. That's changes in ground cover. So the red areas are bare ground. The green areas are photosynthetically active. The cover and the blue areas are dry cover. So we can separate the green fraction from the brown fraction and the bare fraction. And we're actually then able to predict estimates of biomass basically within each grazing distance away from the water. So you can see here, we've got basically lower biomass basically in the areas that are more watered and being heavily utilised. And as you move away from the water points here, so you're getting more biomass, you're getting less utilisation. And yes, we've got integrations. We've got a lot of work going on with AgriWeb at the moment. Mya Grazing, we're working with the integrations with Mya Grazing. Saving technologies is the same thing we've actually integrated into their system. So the idea here is for us to be in the back end rather than the front end as much as we possibly can. I just wanted to quickly touch base at the other end of the spectrum at sort of the industry level. We've been doing work with the beef sustainability framework. And while individual producers right now might not see direct benefits to this, we're actually, we're starting to link them up. So we've got a property database or a land parcel database for the whole of Australia. We've actually processed 30 years of satellite data for every single land parcel in Australia, about five million land parcels greater than a hectare. There's about 550,000 individual properties. And we've actually got a, basically, a longitudinal database of tree cover changes, basically, per land parcel and also a longitudinal view of ground cover for every property in Australia. So this is a South Australian example here. So this is basically, this is the arid zones there. So the red area is the lowest, the lowest ground cover. And then we've actually got a graph here over the last 30 years of ground cover changes basically in the, this is the arid lands region there. So this blue line here is the median ground cover levels basically for the arid lands region. And so 50% of the arid lands basically is that blue line. Can you see the trend, the long-term trend there in terms of ground cover? So actually we're seeing a decline in ground cover levels basically across the arid lands region over the period. There's obviously a wet period in here. And then we're going, we've actually been on the slide. But the more concerning thing here, and this is what we're really trying to highlight here, is that's the 50% of the region. Look at the lower 10% and 20% oil. So what that's saying there is that we've actually got 50% of the land cap that's following a particular trend. And actually it is a declining trend. But the bottom end, so in terms of those land managers that are struggling with their ground cover levels, they're on a very different trajectory. So their decline in ground cover levels actually is a lot steeper than effectively than the average. So in terms of a land condition perspective, we've actually got the ability to produce a graph like this for every single land parcel in Australia now over the last 30 years. So what we're doing is there is looking at how we can connect individual producers to that long-term trend data so they can look at the paddock. They can look at the paddock today this week. And then we can also get them to look at the last 30 years and put everything in context in terms of what they're doing now. And we're just building a dashboard so the middle of the year we'll actually have a dashboard that actually allows, basically that exposes this information to basically to the general public. Now, it's a lot of sensitive information. So clearly basically producing individual property level data is very, very sensitive. And we have no intention whatsoever to basically in terms of exposing the individual property data to anyone other than the property owner. So there'll be zoom controls on here and we won't be providing property boundaries and those are the things into the data. There'll be zoom controls on it, but it's all publicly available. And what people will be able to do is to be able to select a region and select basically sort of a, it might be a catchment boundary or it could be a local government area or whatever and then look at effectively the trends across that region in terms of their ground cover condition over time. And we're then building some tools to then give them secure access so they can actually then benchmark their property to everyone else without people seeing their property. They'll be able to go in and select their property and then benchmark themselves to the rest of the population, if you like, without dealing with those major privacy issues. Now, I just wanted to just finish up quickly. So I've got a minute. How many consultants have we got here in the room? Okay, now in terms of producers, when you're actually, when you're onboarding someone at the moment, every single software provider that's actually here at the moment, when a new client rings up and basically you ask them, who are you? Where are you? Basically, what are your credentials? Where's your property boundary? And quite often that can actually can take hours potentially to actually identify where a property is. They might say I've got a KML file or they've got, there's ways of getting out but generally onboarding of a client is actually quite difficult. We've built a system here which has been commercialized basically over the next few months. We call it the MyFarm Property Key. What we've actually done here is taken, basically we've got land parcel data for the whole of Australia. So the lot plan numbers, everything that sits in your rates notice with a lot plan numbers, we basically got access to every land parcel. We've got an authentication system we've built with Meet and Livestock Australia. So with LPA, so if you're a livestock producer, you've got a PIC code. This has really been built around the livestock sector here but there's parallels in the grazing in the copying industry. If you're trading in cattle, you're basically sheep, you've got a property identification code. So we've actually got a system here which goes and authenticates a producer. You put in your LPA credentials and your password and your PIC number. It goes off to Meet and Livestock Australia, authenticates you as a valid producer. So we know who you are, we know that you're valid and you've given us your passwords so basically, presumably, basically that it is the right person. We go to MLA, we get the information on your, on the producer's behalf. We then get the address from that and we actually find that half of the PIC addresses, actually, are not in, not the front gate. So God help us, if there's ever a major biosecurity in Australia. So what we then do is get the producer, we present the parcel boundaries to the producer. They can go click, click, click, identify the parcel boundaries for their property. There's the lot plan details coming here and they hit the button and that's them producers basically a property key. So it's actually an encrypted data package with all of the authentication information, their property boundary, their lot plan details and what that allows us to do is then start to build services around that. So we've got APIs now that we're developing that can give them a satellite image, we can do a change image. What the producer can then do is then take that key and hand that key to any other provider that they actually wanna work with. So rather than every third party software provider having to onboard that same client over and over and over again, what we've actually got here now is a single point of truth where that key, as that producer hands it to other organizations, that gives them permission to basically access their details and where their property is. It's also gonna allow us to build APIs as an industry and allow me as a company to be able to work with Tim or work with Tim Neal or other companies that basically are building applications. We've got an authentication key that the producer has provided which we can then build services around integrate services basically without having to duplicate effort across individual companies. So that'll be coming onto the market in the next few months. So we can do things like here, we're doing a trial with about 100 properties in the next couple of months, doing forest cover change analysis across those properties as part of an accreditation system, ground cover analysis and other things. And then we've got this, this is just a little blob here, we've got this encrypted data package in here that basically gets produced when you hit the button, hit submit. And when you hit the download button, it doesn't go to anyone else, it goes to you basically. So you produce it as the producer, it comes onto your download, actually download area and then you decide who you wanna pass it to. So it's really, that's really about sort of how we then integrate those services and start building dashboards. Everyone wants a dashboard, but at the moment, it's really, really difficult for these dashboards while individual companies actually are struggling to integrate at that sort of machine to machine level. And that property key is gonna help with that. I'll leave it there. Thank you. Thank you. Thank you. Thank you.