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icetana (ASX:ICE) secures Sydney Opera House contract

icetana Limited (ASX:ICE) Non-Executive Chair Matt Macfarlane discusses his transition from the CEO role, the company's artificial intelligence solution, annual recurring revenue growth, and the recent contract secured with the Sydney Opera House.

 

icetana Limited (ASX:ICE) Non-Executive Chair Matt Macfarlane discusses his transition from the CEO role, the company's artificial intelligence solution, annual recurring revenue growth, and the recent contract secured with the Sydney Opera House.

Paul Sanger: Today, we're talking to icetana (ASX:ICE). They have a market cap of around $10m. icetana is a global SaaS software company providing video analytics technology designed to identify abnormal events and unexpected behaviour in real-time for large-scale surveillance networks. The technology is used everywhere from shopping centres to casinos to universities. We're speaking today with Non-Executive Chair Matt Macfarlane. Matt, welcome back to the network.

Matt Macfarlane: Thanks. Great to be here, Paul.

Paul Sanger: Now, Matt, let's just start, you've just recently transitioned from the CEO role, so tell us a bit more about the change in roles, what brought that about?

Matt Macfarlane: Sure. So, it was at the start of this month and I've handed over to the person who was my Chief Operating Officer, so from within the organisation, Kevin Brown. Kevin was formerly at Virtual Gaming Worlds and drove that business revenue dramatically upwards as the Chief Operating Officer there. We've been working on the transition for a long time, and I've decided to stick around in the Chair role to do investor relations things and because icetana is still very close to my heart and I see a great potential for the business. So, I'm very keen to continue to be involved, just not quite as involved as I was in the past.

Paul Sanger: Got you. So, Matt, let's start. There continues to still be a lot of buzz around AI, artificial intelligence, including machine-generated images and programs like ChatGPT. I'm just wondering if you could talk through your own self-learning AI solution and how it's developed and how it works.

Matt Macfarlane: Sure. So we've, just in the last three or four months actually, completed the development of our product to a commercial level where it is being re-released as a completely new platform dealing with exactly the challenges you talked about in the introduction, picking up things in real-time for large scale surveillance networks. But we're doing it on a thoroughly new platform. And that new platform utilises the latest in AI technology. We use a system called YOLO, which stands for You Only Look Once. It's a licensable but open-source product that helps us identify people and vehicles and other interesting events that take place. And then we combine that with our own AI solutions to map out scenarios, understand events, and compare them in real time to what we're expecting to see in front of each individual camera.

So, our systems are AI-generated. We're training them with neural networks. We're learning to find things like fire and smoke or people falling over in front of cameras, which is particularly useful for surveillance networks. At the same time, we're utilising all the AI developments that are happening out there in the world. So, ChatGPT has transformed many people's jobs, yours in particular, I'm sure. But also in our own operations, I reckon that our development team has probably lifted their productivity by about 30 per cent just from the types of tools that are now available in the AI world. Things like DALL E, which allows you to create images, helps us to train neural networks. We can create a thousand images of fires in a shopping mall if we want to in a matter of minutes. In the old days, it would take you days and days to trawl through YouTube videos and other images on the internet to try and get your neural network trained. And so, for icetana, it's been really transformative, the last six or nine months of AI development. And it's also been the same for our customers, who are showing a lot more interest in our product.

Paul Sanger: Fantastic. So, let's go onto the business now. Your recurring revenue has been increasing. What sort of growth to ARR can we expect to see going forward?

Matt Macfarlane: Yeah, look, we've been increasing, but only very gradually, because we've been stuck in the old world of our previous product, which was literally 10 years old. The new product is explainable. It's accessible through a browser. It's integrated with ChatGPT. It's really transformed the engagement levels that we have with our prospects and with our existing customers. So, a lot of our existing customers, we're currently negotiating and working with them to migrate across to the new product, and we're seeing expansion opportunities on the back of that. So, our revenue growth has been quite muted the last couple of years, but a big focus for the next 6 to 12 months is absolutely on revenue growth. So, we're now in a position where the product is so attractive and interesting that we can bring in really good sales people.

Honestly, six months ago, I had a hard time attracting a salesperson because I had a tired old product, but now I've got a super exciting new product and they can see the potential of that. And we're now able to hire sales guys who are literally going to take a sales cut because they know that the commission they're going to earn on selling this is going to be much higher. So, the business is going to go through some incredible revenue growth, I think, in the next couple of years. In terms of numbers, we haven't released anything, but certainly, in terms of budget, I'm certainly aiming towards… You know, a good SaaS company should be growing 40 per cent every year. And so that's the threshold that we're aiming for. And we did achieve that in the past few years, but it slowed down a bit in the last 12 months.

Paul Sanger: What sort of ARR retention levels is the business seeing?

Matt Macfarlane: So, last year, we were just slightly under 100 per cent in terms of revenue ARR because we lost a couple of larger customers early in the year when our new product wasn't ready and we were at the tail end of our old product, which was a bit disappointing. However, historically, we have pretty consistently knocked above 100 per cent in terms of revenue retention. So that's, you know, you make up more from growth of a customer than you do from losing customers, and that's where we're aiming for going forward, and we certainly expect that in the next 12 months.

Paul Sanger: And what area's driving the most growth in the business?

Matt Macfarlane: Look, I think the most interesting sector for us is in guarding services. The reason why guarding services is interesting for us is a single guarding services company might have 20 or 30 different clients that it can actively monitor remotely. So, you might have one guarding services business that looks after 20 schools, and each school has 50 to 100 cameras, and they can monitor all of those schools at night without having to send a guard out to them through the course of the evening. They can save a fortune on monitoring those operations, and we get a beautiful multiplier in terms of the number of cameras we can support. So, that's a really interesting growth area for us. But we've recently pivoted into lots of other sectors, and anyone who's got a control room where there's lots of cameras coming into that control room is an interesting target for us.

Paul Sanger: And the company recently announced a new contract with the Sydney Opera House. Just behind you, by the way. How important a win was this and how will it impact revenues?

Matt Macfarlane: Look, there were two things that were really satisfying about the Sydney Opera House win. One was that it was a very competitive tender process, so we were up against some of our main global competitors in this space. So, it was very pleasing to get through that and end up with a commercial relationship with the Sydney Opera House.

The second is that it's an industry segment we haven't dealt with in the past. So, a cultural and event centre has traditionally not been a place that we've been able to sell into particularly well. And in the enterprise software game, it's very important to have reference sites. So, you can't get more iconic than the Sydney Opera House. We are, of course, extremely pleased to get them. Commercially, it's quite a small contract to start with, and we certainly hope to grow it by proving ourselves on the site.

Paul Sanger: And, look, clearly you're focusing on clients in Australia, but geographically, outside of Australia, where do you see the real target markets that you want to get into and can see good revenue growth from?

Matt Macfarlane: Yeah. So, look, I think we have a strong focus in Australia to start with for revenue growth. We want to create a strong franchise model for how we get into the market with this new product, prove how it can step up the revenues of the parties that we sell through. But we see Singapore, Japan, and the Middle East as core markets in the next 12 months. Beyond that, the US and North American markets are going to be really interesting because we want to go there with our franchise model in hand and go to the security integrator resellers and help them to sell a product that should fly off the shelves.

Paul Sanger: Fantastic. And what additional opportunities can you see for the technology going forward?

Matt Macfarlane: Look, a lot of our sales to date have been to shopping mall customers. And shopping mall customers are really interested in getting some marketing and related information to help their lease negotiations, to understand when there are spikes in traffic, and that sort of thing. And out of the box, we get people counting and we also get heat maps that we can pretty easily create for these customers. So, adding features like that to our product is a core focus.

However, there's a lot more opportunities to also enhance the security offering. So, looking at things like fight detection and picking up specific events in a targeted manner, as we do with our current fire detection system where we've trained a neural network to find a fire in front of any camera. That's interesting for us. And we are very much a customer-driven development organisation. So, as we sell to customers, we listen closely to their needs, and we develop accordingly. With the new product, we are releasing a new release every six weeks. With the old product, you'd be lucky to see a new release every year. So, the accelerated development has made a dramatic difference to our customers and their engagement with us.

Paul Sanger: And is there an opportunity or are you speaking to people like the police force, the fire service, the armed forces? Are they conversations that you're having? Is there potential?

Matt Macfarlane: There is potential. It depends on the willingness of the party to go into a real-time-response environment. So, the police spend most of their time trawling through other people's footage, historically, after an event's happened. So, they have a strong use case for forensic analysis of historical footage because they don't have a lot of actively monitored sites. But there are some opportunities, and with the advent of AI and people realising what can be done with it, there's a lot more companies that are open-minded to real-time response. And we think that we are starting with the commercial sector, but the government and the public services sector is certainly an area we want to move into.

Paul Sanger: Matt Macfarlane, really appreciate the update. Clearly a very interesting six months for icetana. We will be watching very closely. Thanks for your time today.

Matt Macfarlane: Thanks for having me along.

Paul Sanger: Thank you.

Ends

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