RedChip Investor Group Call with Rail Vision (NASDAQ: RVSN)

Hello, good to see you.

Thank you.

Yeah, thank you very much. Great being here. My name is Shahar Hania, CEO and co-founder of Rail Vision. Let me start with a short clip, and then you feel free to ask and stop me whatever you want. And then if no question, we'll move directly to the presentation.

Every year there are thousands... Can everybody here, everybody see? Yes? Yes, the audio is coming through clear and we can see the video as well. Great. Into railway accidents. In 2019, there were 1,552 accidents in Europe alone. These accidents cost the lives of 824 people, 618 more were injured, and the total damage is estimated to have cost about 3.5 billion euros.

The moment a train driver in Poland ran down the aisle warning passengers seconds before the train crashed into a lorry. Rail Vision presents the artificial intelligence revolution for preventing railway accidents.

The systems operate day and night under all weather conditions. They are able to sense beyond the required braking distance through a combination of sensors specially developed in the company's laboratories and artificial intelligence. With these systems, a previously unavoidable accident is transformed into a controlled braking sequence, enabling the driver to safely bring the train to a complete stop.

Detection of humans and vehicles in an urban environment. Detection of vehicles at long distances. Detection in a railway operational environment. Detection of the train travel route. Detection of locomotives and rail cars. The system relies on artificial intelligence to detect, identify, and classify objects. Detection of braking shoes in a railway operational environment. Detection during limited visibility. Detection of large animals. Rail Vision. Trains just got smarter.

Okay, so we'll go directly to the presentation. Can everybody see the presentation? Yes, yes we can. Thank you. Great. Okay, so a bit about Rail Vision. We founded in 2016 with four founders, and I'm honored to be one of them. We have more than 60 employees, where the majority of them are R&D personnel, scientists, researchers, engineers, and so on. And we have a strategic investor, Knorr-Bremse, a world leader in the train industry. A bit about Knorr-Bremse: they are in this industry for more than 110 years. So they know the market, they know the customers, they're already located all over the world, and they're traded at a valuation of about 10 billion euros. But I think that the most important thing for us as a small company from Israel is being connected with somebody that already has a global presence. Imagine that we have to take that from scratch and build this ecosystem of selling; it will be, let's say, a very challenging task to do. But now we have it in place. We have the global entities, global rooms that already have boots on the ground. They already have the contact to the customers, they're all the close customers. So this is why this is a great benefit for us as a company.

So what's the problem? You know, a train needs about half a mile to stop, give or take. Okay, depends on the train, depends on the weather conditions, and so on. And a train operator, conductor, driver, whatever you call it, sees and classifies in a day up to 300 meters, 400 meters, nothing more than that. And at night, it sees nothing. So in a matter of fact, the train driver is about irrelevant in terms of avoiding accidents. Our system can classify up to two kilometers, day, night, 24/7, rain, snow. So by that, providing an alert to the driver, and that he has enough time to respond accordingly: stop the train, slow the train, sound horn, or whatever is needed to avoid this terrible accident. Because you know, this accident with side casualties, God forbid, as also the damage to the platform itself, because the platforms, it might take even up to one year to fix it and get it back to business. And you know that it is said when wheels are not turning, you are not earning. So this is exactly what we can prevent, what we are preventing by avoiding those terrible accidents. And you know, just lately, the last accident that happened in Palestine, Amtrak was delayed because of Norfolk Southern, the NS freight company, has a derailment, and Amtrak has an impact, has delayed because of that. So beside the damage, the direct damage to the train itself, it damages indirectly to all of the network of the trains using the same tracks. So this is a terrible impact and huge damages to all of the operators. So this is exactly what we can prevent by using our technology.

So when the train operators understood that they have a problem, they looked to the right and left and saw that the most advanced industry in that sense is the automotive. But unfortunately, from their point of view, the available technologies from that industry are good for 50 meters, 100 meters, nothing more than that. You are talking about LiDARs, radars that usually are good for vehicles, for cars, but not good enough for trains. Because trains need 200 meters for marshalling yard and up to two kilometers at main line. So this is exactly what Rail Vision is addressing, and is not looking for the automotive industry because it is not relevant.

What is our solution? We have an external sensor unit that is combined from a very sensitive visual sensor and also a thermal imager that can look day, night, 24/7 out there and classify up to two kilometers. And quite a lot of know-how, and it is all built inside Rail Vision about the optics, the electro-optics, the sensors, the way of transmitting the information to the computing unit that is inside. And the computing unit that is inside is running artificial intelligence, deep learning technologies in real time, which is very unique, I would say, in this industry to Rail Vision. As far as we know, so this is a great benefit. And I can say that for now, as far as we know, we are the only ones all over the world that are able to put a system on the locomotive and you can start working. On the left, you can see the mainline system, our flagship system that can classify two kilometers. You can see behind, I think in the background, the installation that we did on the long-term pilot with Israeli Railways. As you may notice through the PRs, we managed to sign a contract for the very first 10 units of this kind of system to be installed on their locomotives. And this is the first time all over the world that somebody is deploying this kind of systems. And on the right, you can see the marshalling yard system that we've developed with SBB Cargo. A marshalling yard is a place, imagine three trains coming from the port carrying 100 wagons each. The first one carries wheat, the second one carries sand, and the third one carries gold. Now you have to arrange, disassemble, and assemble the train that goes to Berlin, for example, that carries three wagons each. So all of this operational activity is taking place in the marshalling yard. So you can understand the very low efficiency that this operational thing is happening because you have one person and the other person has to be on the other side. And if there's only one person, he has to go from one side of the train to the other side. This is only, you know, you can imagine the people that is going one mile, which is give or take the length of a train. So you understand how non-efficient this process is. And with our technology, we can increase efficiency from three persons to two persons to one person, depends on the use case and the infrastructure, but can easily be much safer and, in a matter of fact, decrease dramatically the damages and be more efficient. But the most dramatic problem that they have is the human resources shortage. You know, we were discussing with a US-based company that shared with us that they are recruiting people, training them for two months, and after one month they just retire. They cannot stand the conditions going out there, standing out there, cold, snow, night, 24/7. These are very hard, difficult environmental conditions to work in. So the solution, the only solution, is technology, and this is exactly where we fit in.

So a bit about the size of the industry. So you know, you just understand that whatever infrastructure and transportation are involved, it means a huge amount of money. So whenever we can contribute to the efficiency of this activity, it means that we are in business. Also going from maintenance to predictive maintenance. You know, imagine a train that goes from Canada to Mexico. So through this route, you might encounter some vegetation that penetrates the gauge of the train. And instead of waiting till it takes the train and causes damage or derailment, you can define in our system that is already installed on top of the locomotive. You can look outside and provide an alert when it penetrates to the predefined area, and then the maintenance guys just go out there and take care of this problem. But imagine that you're collecting data through all of the year. So the maintenance guys, with all this information, can predict and spread out the teams according to the predicted maintenance a year ahead. So it's going to be much more efficient, much more cheaper to the operator, and this is exactly what we can provide to the operators.

A bit about the business model. Beside of selling the system to the operator, the locomotive serves about 20, 30 years, give or take. So we have to support this system through all of these years. So the service and also the obsolescence management, because you know, electronic components last for about five years. So whenever there's a failure, it is not just replacing the component because it might be obsolete already. So with our service, we can take care of this problem and have this service paid according to the SLA through all of the life cycle of the locomotive. And beside all that, additional feature, software licensing, updates, and so on, all of this will generate recurring revenues through all of these service period.

Here you can see our system, our first system that we sold to SBB Cargo on the locomotive. And on the right, you can see it was a dense fog. I personally was inside this locomotive, you couldn't see a thing. And without technology, we managed to classify the tracks, classify the wagon that is in front of us, and also the person which is very close and you couldn't see with your bare eyes. So, and I don't know any other technology, radar, LiDAR, that will be able to classify to this resolution the person that is out there.

Rio Tinto, a mining company that runs its operation in Pilbara desert in Australia. Their train is already autonomous, but they have one problem: they don't have any mean or any measure to detect and classify obstacles before colliding into them. So this is why they made all the way to Israel to witness our technology. And after doing that, we signed the contract with Hitachi, which is their integrator, and we delivered the system on time. We ran the system for about four or five months, long-term pilot, and it was outperformed, very successful. And we are negotiating the next step into that operator. And I can say that the potential there is 220 locomotives. So you understand, even with not a big operator, the huge deal that can be conducted and the great potential beside all the additional services related to the signaling and related to other systems that can be integrated together with our system.

Israeli Railways, you know, from about seven years ago, we signed the contract with Israeli Railways, collaborating with them, collecting data, free access to whatever information is needed, free access to locomotives, drivers, operators, switch yards, tracks, whatever is needed in order to develop this kind of system. So beside of the technology that is involved here, we have also a great barrier for other competitors to come just by having the relevant data for our system. And this is because of this strategic collaboration with Israeli Railways. But beside of that, after conducting more than a year long-term pilot with them, they signed a contract with us because our system was outperformed for the very first 10 mainline systems to be delivered to them and to be installed on actual or operational passenger trains and also freight trains as well, which is a great breakthrough that we made this year.

Let's talk about the future. You know, the world is going autonomous, and no doubt that the first industry that will go autonomous is the rail industry. We see it already going autonomous: metros, we see Rio Tinto, and all the others will follow them. Because you know, when you have a driver or engineer, you have to take care of him, you have to make sure that he's coming on time, is not tired, is not playing with his iPad, and is not eating, and so on. When you are going autonomous, it cannot go autonomous without eyes. And as for now, we are the only ones all over the world, as far as we know, that can put a system on the locomotive which is battle-proven and already been purchased. So you can move on towards autonomous.

A bit about the people. So the chairman of the board is a senior vice president from Knorr-Bremse, Mr. Mark Liberty. He has a vast experience in sales in the rail sector, and we benefit out of him quite a lot on daily basis. Myself, I'm from a technological background, and I served in the military as a technological expert, electro-optics expert since '94. And through that, I was involved in the communication industries, military industry, Elbit Global Companies, Rafael Systems. I was dealing with sensors, algorithms, missile warning systems, jamming missiles for a living. And then we established Rail Vision. Oren Fux, there, which is the CFO, vast experience with public companies in Israel and also in the US.

A bit about the financial data that you can also look through the last PR regarding that. These are the numbers that you can see. So if I'll summarize this deck: we have a strategic investor that is supporting the company in all terms. The market is just huge. The market is here. We are not talking about a dream company, we are not talking about an app in your iPhone. We are talking about a sustainable industry. So whatever happens, trains will still run. And this is a huge market, and everybody there understands that they have to go towards digitalization and automation. The system is already under contract, you saw it. And the long-term revenue with the operators is, I can say, promised. And of course, the strong management with the vast experience will lead the company forward. Well, thank you, that's it. I think if you have further questions, please feel free to ask.

Well, very good question. For that collision, I can say that with our current system, we will probably not be able to prevent this collision, this derailment, just because it was not an obstacle. It was a failure inside the train, in which we are not looking at the moment. But of course, our technology is good for many things. Also, we've been approached by some operators for many use cases, including that, and some of them even offered that they will look on passing trains and whether we can provide an alert for that. And from a technological point of view, it is quite obvious that it is possible.

Well, I can disclose only the ones that we're reporting on the PRs. There are quite a few, some of the main lines, some of them switch yards. And the ones that are disclosed are Rio Tinto, Israeli Railways. We were quoting about... no, we're not reporting that, sorry. And also in Japan, SBB Cargo. These are the ongoing pilots or let's say deals. We expect that, you know, Israeli Railways is already a contract. So we expect that a few months or so, some of them will materialize. But this is a belief. I cannot say exactly when it's gonna happen.

Yeah, no doubt about it. We saw it for the last year. It was, you know, especially in the US, we saw a great change with approaching us. I think if you go to the public media, you can see some RFIs, not some, quite a lot of RFIs for very big companies, in which I cannot relate at the moment because it was not disclosed publicly. But yes, yes, we see the impact, we see the need. Quite a lot of accidents take place in the US alone, okay, give or take twice a day or something like that, where the minority, as far as I know, are from a technical failure.

Sure. Once we're going to install a few systems and they will understand the benefit, it will be mandatory. Exactly the same thing that happens with Mobileye. They worked for quite a lot of time trying to push into the market, and just after understanding the value, the insurance companies stepped in. So now we understand that no vehicle, no car, is without these measures, with this system. So it's exactly the same thing. We understand that's going to happen with our technology as well. I can tell you that the accident that took place, I think it was in Minnesota, three months ago, it was a derailment due to a collision of a freight train with a dump truck. That, for sure, could be avoided, and all of the casualties and the huge damage that took place there could be avoided by just installing our system. That's it.

It will be on the coming 20th.

Yeah. I can tell you that it is quite clear that we're gonna need another round, and we are planning accordingly. We expect that just like the other rounds, it will be backed up, will be supported by Knorr-Bremse. So we cannot say more than that at the moment. It is quite obvious. Please let me know if that answers your question.

Yeah, that's correct. I wouldn't say that it would happen the coming year, but later on. Again, it depends on the customers and the use cases, because we see that every customer would like his own flavor or its own, let's say, adaptation to the overall safety perception. So if it is paid, I don't care, you know, it is what we have to do to support those customers also from the technical point of view. So I don't see significant reduction in the human resources. But again, we understand that this is a great cost for us as a company. But you know, engineers, especially AI engineers, cost a lot, especially in Israel, cost quite a lot.

220.

Yeah, yeah, yeah. You know, at the end of the day, they came to us and asked for this pilot and understood that there's a use case. There's some other use cases not necessarily related to safety. But let's go back to safety: they do have cows, kangaroos, people out there. We just detected in the Rio Tinto desert that somebody crossed the tracks. And this is a great deal for them because, you know, everybody knows that they have money and everybody will sue them. So for them, it is a great thing to have this kind of system.

Exactly. But beside of that, if they hit some cows and they have a lawsuit, and they're publicly traded, it will impact probably, I don't know, of course, but probably will impact their share price. So why wouldn't they just invest in this kind of system and avoid accidents as much as they can?

We can even go more extreme. Okay, let me take your comment and just show you how far can we go just with having this technology. Rail Vision UK is an infrastructure monitoring company. They monitor the tracks, and they, in a matter of fact, occupy the tracks while they are testing it. So this is not necessarily the same use cases that we are talking about. But of course, collaboration in the future is considerable, and not only with them. But as for talking about... just sorry one second. Sorry, I have a call and I was just postponing that. Just a second, please. Okay. Okay, sorry for that. But now I'm free to talk as much as you want. So talking about, I'll tell you one use case that we filed. We filed a patent on that. When you are getting into a station, you can, in a matter of fact, by using our technology, you can do clustering to the people that are about to entrain, for example. You can see that children are about to go to entrain to wagon or car number four. You can target the commercials inside this wagon and do a Sony PlayStation or Nike, whatever. And if it is males, for example, you can do baseball or whatever you think will be appropriate. And by that, also generate revenues just because of commercials. Endless possibilities of generating revenues by using this technology of artificial intelligence. But now, at the moment, we have to do the penetration. We have to prove to the world that we are the best, in which we already proved to quite a lot of the customers. And now we are on this phase of having our customers happy, and only after that we're gonna deal with the additional features that we can provide to our customers.

We are not talking about radar or LiDAR. We're talking about the visual, a very sensitive one, and also a thermal imager. Okay, both wavelengths are being used. So we're talking about visual, which is 0.4 to 0.7 micrometers, and the long-wave IR is on the long-wave, which is around 10 microns. So it has an imager. The detector itself transforms the radiation to an electrical signal. So this is what's going on. And also, the great deal is doing that to this market, to this industry. So this is why we developed the optics and the sensors, not the imager, of course, but everything around that.

The cost of what, I'm sorry?

Yeah, we're talking about, if we're talking about one to ten, or let's say quantities on the low end, we're talking about more than $200,000 per system. And the installation will cost somewhere around $10,000, $12,000, $16,000. We're talking about figures that are, let's say, reasonable at the market.

Even more than that.

Give or take 50 percent.

Yeah.

It is about 16 million overall, and the float is around 6 million, something like that. The exact numbers are available.

Maybe. Yeah, on the warrants, the IPO was a unit, means one share and one warrant.

No, no. Around 6 million.

No, out of the 16, 6 of them...

100 percent.

Welcome.

Well, we expect and we believe that we're going to have a few customers this year. But since it was not disclosed anywhere, I cannot say anything about that. But you understand that even one customer is a few millions. Okay, so this may give you the sense of how our industry looks like.

Now, we are targeting... I cannot say that we are not talking with the OEMs, but this is not our main target at the moment. We are targeting the operators, because they are the ones that pay the price. And if there will not be a demand from their side, the OEMs will not do it, because the OEM responds to a tender, and if the tender will not require our system, we can just talk. So at the moment, the main activity is talking to operators rather than talking with OEMs. But yes, it is quite obvious that we are doing that as well.

We are not considering the LRV as our main activity at the moment because there are quite a lot of, let's say, competition there and prices are very low. Why should we be active there? This is why we took all of our effort and put that on mainline and switch yard, which is a much better place to work in. So at the moment, we are talking with some customers, but we don't see the great deal doing with a few thousand dollar system when we can do much better in other places.

Well, great question. I think that we did some steps. We participated in quite a lot of rail conferences, rail news, Rail Gazette, many newspapers that are related to this industry. And I think that some of you might have saw us in the CNBC channel. We did a campaign there, and results were great. And we are considering to continue that. It is just how to do, what the cost, and the planning ahead of the purpose of this campaign.

I didn't hear the last sentence, sorry.

Okay, so for the first one, yes, I do consider our system the most advanced all over the world. And I can tell you that the competitors, as far as I know, are not even close. Okay, that claims that they can compete with us, I didn't see even one system that can go up to half a mile. Okay, I'm not talking about more than a mile, in which we are positioning. I didn't see any system like that. Maybe there is that I don't know, but we don't know, other companies don't know about this wonderful competitor that probably does not exist. Okay, so again, to our knowledge, nobody is even close to us. And about being a standard, I'll just repeat what I said regarding Mobileye. Once you have enough systems there and you can prove statistically the benefit regarding safety, then for sure, I believe that it's gonna be mandatory to put that by the FRA or wherever it can be. Same thing that happens in the automotive industry.

Thank you.

Stay tuned.

Yeah, as I mentioned before, our technology can do a lot of things. Okay, and once we develop the core technology, in which we did, quite a lot of use cases, and I can tell you, no, I cannot tell you, quite a lot of things can be done there. Of course, I'm not sure that with trucks and buses they need two kilometers. They probably will need less than that, but there's some other applications that might be considered as relevant for our capabilities.

Oh, this is a great question. PTC is all about, you know, positioned static sensors. Some of you might have saw my article that was released in one of the majors, and I was talking about the PTC, which is a great step for safety, but it is not enough. Okay, because when you have an obstacle, nothing can see that, okay, beside our system. So as a full suit, getting integrated into the PTC with our system, and we can report whatever we see, whatever interruption we might have, this is a great benefit. The PTC is the first step for safety, but it is only one part of the puzzle. Okay, so some of you are asking about the inference of our artificial intelligence. No, we are not using any cloud or any infrastructure outside the edge computing in order to run it. So this is our significance. So we are running artificial intelligence in real time on edge computing.

Great question. The first answer for the first question is no. I just mentioned through the presentation that our system is about to be installed with Israeli Railways also on passenger trains. Okay, the reason that we approach the freight guys are faster is because they suffer quite a lot and they're usually privately held companies. In the US, also passenger trains are the same, but those guys were the first ones. So first come, first served. That's it. But passenger trains are definitely in our strategy. Okay, and as for integrating into other systems, first of all, we don't need to be integrated. We are a self-sufficient system which provides, which is an ADAS system. We are assisting the train driver by avoiding and alerting on obstacles. In the future, I believe that we will be integrated into the signaling system towards a fully autonomous operation. And this is relatively an easy task to do.

Well, I don't think that these systems are related to obstacle detection. Okay, as far as you know, no other technology or no other system is doing that. So therefore, again, the integration is maybe part of the requirements, but it has nothing to do together. Okay, for the first being as an ADAS.

Yes. Same thing that happens with Mobileye. No reason it will not happen with us.

Yeah, usually if you're talking about 40 meters per second, so your question gets a lot of meaning. The answer to that, yes, this is of course a very straightforward strategy. And if you'll notice, Knorr-Bremse has established two years ago or three years ago a division of digitalization that takes into account also our system. So you can see that on their website as well.

Well, as I mentioned before, we are the only one that managed to break the glass ceiling of penetrating into that market, doing all the homologation and proving that our system can help avoid terrible accidents, and each accident costs so much. So it is quite clear that having our system is a great benefit for the operator. And another thing, as I mentioned a few times before, a half a year ago, one year ago, it will probably be the last time that you'll be able to invest in Rail Vision at this valuation. So make sure that you don't miss the train. Jump on the train. Just make sure that Rail Vision system is installed on this train.

Thank you very much. It was a great pleasure. Looking forward to hear from you. Thank you.