Cordel Group (LSE:CRDL) — Results for 12 months ended 30 June 2021

0:00 Good morning, everyone. Good morning, ladies and gentlemen, and welcome to the Mastrana Group PLC Investor Presentation for the twelve months ended 06/30/2020 time by the q and a tab situated on the right hand corner of your screen. Simply type in your question and press send. The company may not be in a position to answer every question received during the meeting itself. However, company review all questions submitted today and publish responses where it's appropriate to do so. These will be available via our investor meet company dashboard, and you'll be notified once they're ready for your review. I'd also like to remind you this presentation is being recorded. Before we begin, we'd like to submit the following poll. I'd now like to hand you over to Ian Budry, chairman and the CEO of Strana Group PLC. Good morning. Good morning, everyone. Welcome to our first Investor Meet company presentation.

0:50 Our fiscal year ending in June 2021 marked an important transition from the original Maestrano banking focused business to the new rail industry business. The board is delighted with the results being achieved by Nick and his team. I'll now hand to Nick to run through the results from last year. Thank you. Thanks, Ian. Before I do just dive into the presentation, I wanted to give it a recap. And to do that, I thought we'd just start with a quick video that we've got prepared, which is a customer video, but should just go a little bit, to explain what it is that the platform does.

1:38 Uses LIDAR AI to automate rail inspections. This is the CORDEL WAVE. It's a rugged LIDAR scanner specifically designed for railroads. It's a set and forget device, so train crews don't even need to touch it. It can be mounted on rail inspection vehicles, high rails, and revenue trains. CORDEL's cloud based AI engine has been trained on hundreds of thousands of rail miles to accurately categorize and interpret scan data. CORDEL uses LIDAR point clouds because they allow three d calculations that video just can't do. This means you can visually travel down a track and rotate and check measurements automatically on screen with high accuracy. But the real benefit comes from identifying items of interest and CORDEL's AI helps with that too, so engineers can easily generate work tickets for specific responsibility types like for ballast crews or high wide teams or vegetation teams. With CORDEL automated inspections, track closures for inspection periods can be significantly reduced sometimes by as much as 90%.

2:33 Visit cordel.ai for more. Told you it was short. So firstly, what I wanted to do is just recap what the Maestrino CORDEL platform actually does. Firstly, we design and assemble low cost LIDAR camera and positioning systems. We install these on in service trains. So these are the vehicles that are already passing through the network on a daily basis.

3:09 We then take that data and we unify all of that remote inspection data into a scalable cloud based data lake. We then build and deploy fully automated AI powered analysis applications that enable railways to inspect their networks from a computer screen. This process is almost fully automated, which is a major safety benefit and cost savings to customers. It allows inspections to happen more often with higher accuracy and lower costs compared to manual inspection methods. And automation also means that our margins increase as we increase our revenues.

3:54 Our focus is on deploying our LiDAR and AI as a service to the world's railway market. It's key to understand that rail is the same in every market around the world, whether it's freight, transit, light rail, or metro, or whether it's in Japan, The US, or Brazil. Meaning, we can deploy the same hardware and software systems with only minor configuration changes for each customer and each market. And with over 850,000 miles of available railways around the world, there's vast growth potential. Over the past twelve months, we've processed over 65,000 data miles across four continents, including Australia, The US, Japan, and The UK. In Australia, we completed four captures of the entire freight network. Traditionally, networks would be lucky if they completed even just one scan every five years.

4:50 But by drastically reducing the cost per mile, we're enabling railway markets to increase the frequency of their scans. And this is the major innovation benefit to the rail market.

5:05 The CORDEL platform offers a compelling business model with increasing revenue potential from each customer as we release new AI driven applications. And once we've captured data, which has the highest cost, the scope for AI driven applications to provide value is virtually limitless. With a very low direct cost to deliver each new application, we increased gross margins per customer per mile. With this increasing value, customers realize the benefits, especially in reducing their labor costs, increasing safety, and reducing their own carbon footprint. This leads to a very sticky customer base with long term upsell and cross sell potentials.

5:53 Over the past five years, we've continued to invest in the scalability of the platform to achieve high gross margins at scale. And by leveraging our research and development and manufacturing capability, we deliver quality hardware systems that tightly integrate with our automated software pipelines.

6:14 We are an unusual, company in the global AI software industry in that we've actually built and own the entire artificial intelligence platform. We have no external software and hardware dependencies. Our continuing focus on AI applications as a service and the increasing rollout of our sensors on trains around the world is succeeding against traditional service models and providers. We're not just winning contracts. We're creating a new way of working for our customers and our partners. In January this year, we released the CORDEL Cloud web based software platform, which you could think of just like Google Street View for rail, except it's updated every week with fresh data.

7:04 Now with over 365 paying users, we're growing the user base by 15% per month. Only last week, we had over a 170 active users at one time and multiple hardware systems live on trains capturing data in Denver, Miami, London, and Melbourne. Customers and partner wins in The US were with Union Pacific and Holland, and in The UK with Network Rail and HS1. These opportunities are really just the beginning. With an accelerating pipeline of contracts and partners, we're very pleased with our progress.

7:45 As we continue to work on the engineering and safety approval processes in our relevant market, it's worth noting the approvals that we've received from Network Rail and Network Rail High Speed. These have global standing in the rail industry and validate the integrity of the hardware software combination.

8:06 And it's not just the CORDELL platform that's been growing. NEXCORE makes the sensors carried by both drones and trains, meaning that our research and development investment is amortized to both both operations. And NEXCORE has a growing list of global distribution partners and is continuously evolving its products and technology. AirSight, which is our original services business, also continues to grow with recent high profile contract wins in Australia and an accelerating sales pipeline. AirSight provides the business with the human skills and customer projects to test and validate new projects, products, and services as with it as we develop them. The FY '21 results demonstrates the core logic of our business plan, 94% revenue growth with 50% cost growth.

9:03 The increasing costs were primarily people as we expanded our software engineering teams and added rail industry experts in The USA and The UK. Increasing margins is a focus across the business. Business. Our sales model is based on reseller partners and our product margin model on increasing automation. Increasing Our f y twenty two strategy is built around partners, evident with the recent Holland announcement in The US and an exciting pipeline of new partners around the world.

9:41 In f y twenty two, we will deliver additional AI services, we'll onboard new partners and open up new markets, while we whilst we accelerate revenue growth in our existing markets. We will continue to invest in our products and teams to ensure customer success and support the growing international sales pipeline. Feedback from customers and partners validates our platform as a compelling global offering. This gives us the confidence in continuing our growth well into the future. I'm now going to hand it back to Ian just to conclude our presentation.

10:25 Thanks, Nick. FY 2021 laid the foundation for the group's new direction. It's now an appropriate time to align our name with our technology and target industries. Therefore, at our Annual General Meeting on November 18, we are seeking shareholder approval to change our name to CORDEL GROUP PLC. The new ticker will be CRDL. CORDEL is a compaction of corridor delta, an engineering expression in the rail and road industries, meaning the precise measurement of changes in road and rail corridors. Thank you for your attention and we now invite questions from the participants. Thank you. Ian, Nick, thank you very much indeed for your presentation. Ladies and gentlemen, please continue to submit your questions using the Q and A tab situated on the right hand corner of your screen.

11:27 But just while the team take a few moments to review those questions coming already, I'd like to remind you that a recording of the presentation along with a copy of the slides and the Q and A can be accessed via investor dashboard on Me Company platform. I'd also like to remind you that your feedback is important to the company. Immediately after the presentation has concluded, you'll have the opportunity to provide that. And Nick, before we go into any live q and a, we had a number of pre submitted questions, if I may. The first line. Follow-up Brilliant. So I'll kick the ball off with that one. Firstly, there's actually a very big difference between freight miles and transit miles.

12:13 So freight being freight networks makes up, you know, about 95% of The US railway market. And the remaining, you know, five to 10% is made up of transit. Now the big difference there is what we refer to, in the business model part of our presentation, which is our frequency multiplier, which is higher value networks, carry out more have higher requirements to carry out more scans of their network due to the higher frequency of passenger trains and and freight trains. But from a mileage perspective, it's possible, I guess, to have contracts with most of the class ones, which make up that, you know, 95%, of the 140,000 miles.

12:59 I guess knowing full well, though, regardless of how beneficial the services are, not everyone is going to buy it. So we've been engaging with all of the class ones directly. And there's certainly a a number of standouts, I suppose, that we're confident in contracting with in the future. That's great. Thanks, Nick. The next question we have here is the investment in the machine learning platform, a large upfront cost and then normalizes or will it grow alongside revenue growth into the future?

13:28 Brilliant. Okay. So the AI services that we provide have, you know, quite interesting unit economics. It's fundamentally what we've built the entire revenue model on. So as we, as we get new models and applications, it does take investment from us to build those new models. Most of that investment is actually charged to the customer. So for example, you know, we've just launched Ballast as a new AI service for ARTC in Australia. ARTC requested that model six months ago as a service, you know, wanting to look at the overall how we can do ballast formation automation. So we built the model. We charged them to build that model. We've now deployed it in Australia for for the customer.

14:20 The nice thing about the AI models, though, although there is an investment to build them, the a, the cost to actually run these applications or these models is really small, especially compared to the cost that the customer would usually take to make something. But also, once we've built that ballast model, for example, we're now deploying that in The US. Because ballast is ballast, you know, rail is rail. Virtually every market is fundamentally the same from an engineering perspective. So once we build new models or or new applications, the applicability in its where in the market that it was developed is obviously high, but also means we can drag and drop those same machine learning models into different markets. And every time we do that, the models get stronger, or or perform to a higher level because fundamentally, they learn a little bit more about what Ballast looks like.

15:13 Now Ballast is just an example, I suppose, and there really is no limit to the number of different AI applications that can be run. But as we add on each brand new model, fundamentally, that, you know, radically increases our gross margin for that customer. Thanks very much indeed. The final one we've got here, Nick, is what is the difference in onboarding speed of a new operator via Holland versus a direct contract between CORDEL and an operator?

15:45 Very good. So, fundamentally, over the past, you know, few months, our partnership strategy has been validated, right, through Holland specifically. But, you know and the reason for that, right, is that the onboarding time with, you know, partnership like Holland, for example, is days and weeks. Right? Whereas compared to, if we're doing it or contracting with the networks, we're talking months and years. Different, you know, different scalability options, and there's obviously trade offs for that. But that is, you know, why as we've progressed over the past few months especially, that, you know, we're taking an even stronger approach to our partnership strategy,

16:30 as it really does just enable us to go to market in new markets, far quicker than we could possibly ever try to achieve ourselves. That's fantastic, Nick. Thank you. That concludes the pre submitted questions. If I may now, Nick, just ask you to click on that Q and A tab and just where appropriate to do so, read out the question and give you a response. That would be fantastic, please. Ian, do you want to just take one? So we have the question here from, Andy. What visibility do we have on revenues?

17:05 I think it's fair to say that, more than half of our annual revenue is is contracted ahead of time. And then the the each year, the the the growth part of the business is contracts that are in our sales pipeline that have yet to to be secured before before the year starts. We're trying to move the business to very much a recurring revenue basis where our customers pay per mile of data captured and analyzed. So as we go along, as we have more contracts with more different railroad companies, each year we will have a much larger proportion of the revenue locked in before the year begins.

18:03 We have another question here from John. In other expenses, we have a line for other expenses. I think he's looking at the consolidated statement of profit and loss in the report. So those other expenses in that particular table are the expenses associated with producing our revenue. So the cost of input goods to our manufacturing, the the cost of the the people who directly service customer revenue.

18:50 I'm happy to provide a more detailed answer if that would be helpful, but I'd need some input from our CFO to do that, but we'd be more than happy to do that, you know, after the presentation today.

19:05 Okay. Good. Nick, I think there's a question here from Richard, which would be good for you to take. Okay. Which is okay. So looking for so it'd be useful if you're able to give some examples of problems discovered by our system that have prevented serious accidents on rail lines, which would not have been discovered using traditional methods. Now this is a fairly sticky question in that as a service provider in the railway industry, we try to avoid correlation specifically to our customers around the three d's, which is deaths, derailments, and delays. It's not a helpful, conversation to have, in a sales context. However, the fundamentals that we can really talk to if we inspect a network more frequently, more often, and with higher accuracy and higher levels of performance, which we can do due to the automation.

20:10 One can, I guess, deduce that we should therefore be able to detect more faults and be able to prevent, you know, more of those types of events?

20:21 I can't speak to a specific example of, you know, avoiding something like that fundamentally because the fact is that if you avoid it, there's nothing to you know, it never existed. But what we can say is that the process, especially with ARTC as an example, by using our automated system, they've been able to complete inspections that were on a three year backlog. You know, effectively meant that they hadn't carried out those inspections. You know, the last time they did was, you know, three years ago. So and over the past twelve months, we've effectively carried out, you know, three or four times the network scan, which means we've seen that thing four times inside of that. So,

21:10 it's not one example. I guess there's more of a overall performance increase and improvement into the way railways inspect their networks. So I'll take the next question. What loss are we forecasting for FY 2022? But that actually flows into the following question, when is our target for cash flow breakeven? I think that's the more important point. We are targeting cash flow breakeven, within the next six months, remembering that right at the moment, we are investing in increasing the scale of the business.

21:55 We're hiring additional people, so that we can process, more customer data and and deliver more revenue in the future. However however, we do plan to be cash flow breakeven at the end of the year, but certainly by the end of the financial year. And and the loss for FY '22 will be smaller than the loss in FY '21. The only thing that could possibly change all of that is if, for example,

22:37 we won a particularly large contract and there are some of these in the wind at the moment which would involve us increasing overheads in order to prepare for the contract. But right now our plan is to

22:58 wind back the cash burn and be cash flow positive by the end of the year. Do you wanna take the question from Paul? Yes. So the question is, what scope is there for moving the technology into roads?

23:15 Which is a a very good question. Fundamentally, the platform was built and developed for roads first. And the reason for that is actually a technical limitation. It's much easier to put sensors on a car and drive them around our offices, than it was to put our sensors on trains. So some of the first, know, preliminary machine learning models that we ever built, and sensor systems that we ever built, were designed for roads to start with. So I guess, fundamentally, there only limitation to our system and the the the software architecture or hardware and software architecture is fundamentally that it works in linear infrastructure, which could be anything from power lines and pipelines to to and, you know, roads and rail.

24:05 And really that's kind of the way that we've positioned the technology is that, there are only minor modifications if we had to roll this out in roads, for example. Now there is different use cases and applications, so each one of those would require different machine learning models. But in reality, that's, you know, a a fairly insignificant component of, the expense of the platform. We've specifically, I guess, isolated the, the marketing model, right, to focus on developing that industry leadership inside of the railway network. But that also gives us credibility. It also builds, I guess, machine learning models specifically and, you know, the automated applications that are really bespoke bespoke to the rail industry.

24:55 And I guess lucky for us that, you know, as I said early in the presentation, rail is rail doesn't matter where you are in the world, but engineering with railways is fundamentally the same in every market. So which is why we're focusing on that. But if you recall, we actually had a project in the Northern Territory Northern Territory government with our airside business.

25:18 So we still use AirSight to, you know, to our advantage to be able to test and deploy concepts, different service offerings before we, you know, proceed to fundamentally automating the platform on a much larger scale. So the opportunity is certainly there, specifically for roads. It's not our number one priority at the moment. Our number one priority is onboarding new customers and scaling out our solutions for, for CORDEL and RAIL. But over the coming years, I dare say it would most likely be an area of the business that we decide to launch and grow. Because, you know, 850,000 miles of railway is a big market. I think there's something like, you know, you know, six and a half million, miles of of roads around the world. So,

26:13 you know, quite a a different scale market again, with also different, you know, competitive, markets and, and areas, which is why we're not diluting our effort at the moment and focusing on railways. Thanks, Dick. I'll move on to the next question from Mark. Cash burn remains high as per the FY 2021 results. North America did not contribute any revenue. Yes. We had a very expensive year in The United States. We have four people there. We always expected that we would be spending a year to eighteen months to secure our first customer in North America.

27:01 It is a extremely careful and conservative market. And like any engineering situation where there is millions, if not billions of dollars of of risk, they're very careful in and do very detailed evaluations of product. However, we turned the corner, the first contract with Union Pacific was a really important step to be able to announce publicly that we've won what's called a class one railroad in America. There are seven class one railroads. As Nick mentioned earlier, they control or own most of the freight miles in America.

27:51 So winning the first one was really key. And now that we have revenue flowing from them, we have revenue flowing from our partnership with Holland, we expect The US business to very quickly be profitable. Next question from Glenn, do if we need a further round of funding, will shareholders be given the opportunity to take up any offer?

28:17 If that were the case, I'd very much like shareholders to have that opportunity. It's not our plan at the moment. We are however, we keep an open mind to this, and I think it's fair to say we are very aware of wanting to bring our shareholders with us on the journey. Next one, Eunice. Yeah. So this one's for Paul. What is the target gross margins and what is the quantum of central costs? National Rail. Go back up one. Oh, sorry. How much does sorry. How much does National Rail or Network Rail spend on this sort of thing annually and what could we do with it for in broad terms? So network rail in The UK is a very interesting market, for us.

29:13 One, because, because of the age of network rail, fundamentally, every other railway around the world is built to UK standards fundamentally. And that's because most, railways, you know, were modeled off the the the British rail system. So it's an interesting market for us in that term. It also is a very congested busy network, which means that passenger numbers and train movements are very high across, which which is only you know, it's a 20,000 mile network. But does mean that the demands on the infrastructure are probably much higher, than they are in larger railway, areas in terms of size and geography similar to, you know, for example, The US, which has, you know, a 140,000.

30:06 But it does mean that frequency is very high, or where the requirement for inspections is is very high. In terms of what they spend, there's probably there's no one number on this. What we can talk to is some of the projects, you know, that our that we and our the incumbents or competitors are currently working on. Some of those are for, you know, projects to scan the network, for example, which range from anywhere sort of from a 100 to 1,500 pounds per mile. You those projects are, you know, in that three to 4,000 mile groupings for the different regions. And that's just kinda one example of, the types of projects and the types of of work that we're, you know, able to do. But, I mean, network rails spend something like $40,000,000 a year sorry. £40,000,000 a year, sorry, on, inspecting, their assets.

31:09 And so we wouldn't obviously replace that cost, but I think if we went some way and and gained a percentage of that, you know, a decent percentage of that, that would go a long way to explain and answer that question. It's a it's it doesn't give us an exact science. It's, you know, it's quite a a, you know, a big and complicated area. So next question from Paul. What is our target gross margin? The short answer to that is 90%. We are currently on our way there. And, again, I come back to the earlier comments about our strategy, which is to get more sensors on more trains automatically capturing data, which is then processed automatically.

32:02 And our customers access the results of that processing via a an Internet portal and and they provision the the calibrations and the analysis that they want via a a user interface. So there's no human involvement on our part in any part of that cycle. It's fully automated. So as we get more sensors on more trains, more people using the the what we call the Google Maps for rail, then our margin will increase and we believe we can get it to 90%.

32:53 And so there's one one last question here, which is what's the competitive situation? Which is a great question because it doesn't have a straight answer, but we've done a huge amount of work on understanding our competitive landscape and where we're positioned relative to that. Now it's a little bit different in each market, of course, but, the best way to think about it, specifically in The UK, I suppose, is, our platform be being completely end to end and inclusive of hardware and software means that we offer a complete end to end service. At the moment, there are no other service providers delivering a similar end to end service, especially with the levels of automation that we provide.

33:41 Now but that doesn't mean there's you know, we don't have competitors. Contrary to that, we have, you know, lots and lots and lots of different competitors. Some of them provide, for example, specific solutions for balanced profiling, and that's all they do. Some of them might provide, you know, track inspection services at a very large scale. And what we found is there are a number you know, in The UK, we've got two primary, competitors and, I guess, incumbents. And we look to I guess, and the key difference to what we do is the ultra high levels of automation that we can apply fundamentally to the exactly the same services that they provide.

34:28 We can do it close to a 100% automated, which means that the cost of doing it is drastically lower. And therefore which also then changes the the, you know, economics of how we deliver this service to increase the frequency of scans to help the customers increase the quality of their inspections. So, hopefully Now just to provide an anecdote, we had one pilot customer in America who had been charged $3,000,000 to for the lidar capture on a relatively short stretch of track, 50 miles or thereabouts. And when we mounted out since we did it in an afternoon. So there's there's a couple of orders of magnitude difference in the cost and the speed with which we can capture data.

35:22 And that leads me into the final question, I'll have a I'll take the technical one here, Nick, if you don't mind. Yeah. Please. Is it necessary to have our own NextScore LiDAR units mounted? No. We can process data from captured from any LiDAR units. And we already have customers in Japan, for example, who have a a backlog of recorded LiDAR data which we we are analyzing for them. So, you know, an interesting thing, there are there are companies, partial competitors to ourselves, who just do the LiDAR data and then hand over what's called the digital twin of the network. But once the railway gets that digital twin, they can't do anything with it. Until you've processed the data, until you've positioned it in terms of latitude, longitude, elevation, and so on, until you've corrected for the various errors in recording, you know, the data has no value. So we process the data from anyone's lighthouse.

36:31 The key advantage of our next call units is that they are they can record faster, so the train can be traveling at higher speed as it's recording the data. They record with higher resolutions, so more more points per inch, and they extract and prepro we extract and preprocess the raw data from the LiDAR unit before it gets uploaded to the cloud and into our computer units. So in effect, we are condensing the data in real time when it's being while it's being captured where our competitors have to store this enormous volume of data before they can, you know, do anything with it. Yep. So we really do have some amazing technology in NextScore, and and it's a a key part of our competitive advantage, but not essential for customers who have existing LiDAR units or existing data recorded.

37:45 Ian, Nick, look, thank you so much. You've answered every single question that we've had come through from investors today, and thank you so much for the investors for submitting all those questions indeed. Of course, you'll have a opportunity to review any further questions that come in from the attendees. But just before we redirect the attendees to give you some feedback, Nick, may just ask you for a closing snapshot, please? Yes. Certainly. So, overall, we're incredibly pleased with our business performance over the last financial year, and we're really excited with the growth potential that we've got coming into f y twenty two and beyond. Major focus this year will be on continuing to expand our pipeline, and relationships with, with our partners. That's a really exciting space for us to be expanding into as we start to conquer The US, The UK, Europe, Australia, and whatever else other markets we move into.

38:43 That's fantastic. And, Nick, thanks again for updating investors today. Could I please ask investors not to close the session? It should be automatically redirected for the opportunity to provide your feedback in order that the management team can better understand your views and expectations. This will only take a few moments to complete and is greatly valued by the company. On behalf of the management team of Mastrana Group PLC, we'd like to thank you for attending today's presentation. That concludes today's session. Thank you very much, and good morning. Thank you.