#095 icetanaAI | We Write AI That Keeps People Safe

Speaker A: The cameras is nice because it gives us an idea about how many people were keeping safe. Look, we've got stories of actually saving people's lives. So these are the stories, um, that we like to hear and share.

Speaker B: Welcome to the Mid Stage Startup Momentum podcast. Each week we interview up and coming founders of some of the fastest growing mid stage startups across the world. Your host is Roland Siebelink, who, who will share some of his own experience helping startups scale from 10 to 1,000 people in a few years. Here is Roland.

Speaker C: Hello and welcome to the Midstage Startup Momentum podcast. This is Roland Siebelink and I am a coach and ally to many of the fastest growing startup companies around the world. And around the world we take quite literally today because with us is Kevin Brown. He's the uh, founder and CEO of Istana, dialing in all the way from Perth, Australia. Hello Kevin. How are you?

Speaker A: Good, Roland, good. Happy to be here.

Speaker C: I'm very happy to have you on our podcast as well. Often I have founders that I just have a first conversation with. But Kevin, you and I go way back, right?

Speaker A: Yes we do.

Speaker C: To tell the audience's story, if you will.

Speaker A: Ah, uh, okay. We were, we had a, uh, growing startup that was moving into scale up. We had a lot of growth challenges and Roland came in and helped to stabilize it, put structure in place and um, using the scale up methodology and some pretty deep industry experience and uh, uh, a cheery personality like um, helped us take a business, helped us take a business from you know, like probably about, I want to say we were probably making about half a million dollars.

Speaker C: Mhm.

Speaker A: A week to about $1.4 million a day. And I think the team grew from. I think probably when you started we had, we were probably about 200.

Speaker C: Oh no, no, no. You were, you were 80 or something when I started. Yeah, yeah, yeah.

Speaker A: Ah, was it okay? Okay. It's funny like, because when I started there was 70 and then I had to make it 30 and then it went up to 80 and then I think by the time you left it was probably closer to 500. So. So you were instrumental.

Speaker C: I think they were over a thousand when. And that was just three years later, right?

Speaker A: Oh yeah. Because I think. Did I leave before you? No, I think it's probably the same time. Um, uh, yeah, we, we, I still, I use the, the scale up methodology still. You know, like we, we use the strategic framework Isatana and we use rocks. We use the, you know, like the new leadership team members. Read the scale up book. Um, and yeah. So

Speaker C: uh, as we're talking about it, Kevin, what would be like your 1 minute summary for founders, like why they should look into something like a scale up methodology?

Speaker A: Uh, because I think that the skills that you need to create the embers or the flame of a business are very different to the skills that you need to take it to the next level. Like there's, there's a, uh, there's a kind of entrepreneurial lack of structure that, that just works or doesn't. And, and then you know, once you start dealing with scale, I think often those creative entrepreneurs struggle with the structure and um, need a bit of help around um, how to plan to scale, how to pro and also how to think about the business. Like, like a machine. I like the um, you know, like figuring out the flywheel, understanding the unit economics.

Speaker C: Well, let's move on and talk about your, talk to you about your current company. So you left to ultimately found Ice Tana, right? Is that right?

Speaker A: No, I didn't, I didn't find that. Roland. This is, this is maybe the, the, the interest and part of it.

Speaker C: Okay.

Speaker A: Like before, like I don't know if you know this, but before vgw, I was involved in another business that um, became a uh, like sold for a billion dollars. Um, and VGW was the last. You know, this is like probably about $7 billion at the moment. And then when I came, when I came out of vgw, um, I met the CEO and the CEO was uh, a caretaker CEO for, for Isatana and Isotana is actually. Yeah, so it's actually been around for like 15 years.

Speaker C: Wow, so you refounded it in a way.

Speaker A: Yeah, yeah, yeah, yeah, totally. That's. And um, I'm, and I, I consider myself to be the founder at the moment. And uh, I think this is another. This was one of the reasons why the business didn't take off 15 years ago because it didn't really have a founder. You know, like it had a, it came from a, it came from a general purpose anomaly detection algorithm that they applied to video. And so it came through out at the local university, got commercialized, raised some money and then they brought in a career CEO. Uh, the career CEO was more sales, less tech. 15 years ago is like 150 years ago in AI. It was absolutely remarkable what they achieved. Um, but by the time I came the business was close to dying and it was one of these ideas where you kind of like, I don't know, that seems like a good idea. Why, why is it not working? And just the application. So just maybe this is a good segue. We, we write AI software that keeps people safe across thousands of CCTV cameras. We, we, we, we specialize in self learning AI. So um, the problem that we fix is that security teams are often drinking from the fire hose of, of this, of video. And our largest customer at the moment has 8,000 cameras. And this is across 17 high end shopping malls in the Middle East. Oh wow. Um, every five hours those cameras produce more video footage than the entire Netflix catalog. So have a, they have a real time, they have a legislative requirement to monitor all the cameras in real time. And this was our first application 15 years ago of this emergent technology. So when I joined um, there was some cultural issues, let's say the last, the kind of dying moments of a business. There's either the fanatics or the people who can't get another job. And I'm sorry if I sound sheer but you know, I had to sift out the fanatics and you know, and keep them on and change the culture. So I changed the culture. Patented technology, you know, like a rebuilt. So our mission was to retain this 8000 camera customer. And this was for me. I was like, if I can do this, this is a big business. If I can, you know, I'll go and do something else.

Speaker C: Was it primarily a product and people challenge when you joined?

Speaker A: Would you say it was a cultural and product challenge? Like the, the culture was terrible because it wasn't succeeded and everyone just was like beckoning and yeah, one of the first things I had to do was put values in place. Like there was no mission, there was no values. I put truth in. There's a value that still stands strong here because there was a real culture of just not telling the truth.

Speaker B: Yeah, yeah, yeah.

Speaker A: It was like he did it, he did it. And then anyway, so, so it took me about, I suppose about six months to a year to figure out what was happening with the people and the technology. And I'm reasonably geeky. Had the keen interest in AI since I was a youngster. And so I was like, I feel like we can do a better job with us with new tech. And sometimes actually we had to wait for new tech to appear. Like for the last five years we've been building the tech. We've got uh, a strong growth story in the Middle East. They um, like they, they, they've got lots of cameras, they've got a legislative requirement to monitor them. They, they've got no problem replacing people with AI. Um, whereas in Australia the security businesses Here the business model is based on head count. So giving, um, them the tools to replace the head count just. It doesn't compute.

Speaker C: Right?

Speaker A: It didn't compute. And now, but now these guys are coming like sort of local place, local council, and we don't even have a go to market for Australia, Roland. So, uh, go to markets in the Middle east, it's in Japan and M. And we're just stepping our toe into the US at the moment. But the markets came alive, you know, like the people are coming and saying, hey, you know, does anyone have any AI around here?

Speaker C: Yeah. Now people can imagine it, right? And they start identifying all those like, routine jobs that AI could the most easily replace, I guess. Right?

Speaker A: This is it, this is the thing. And we've got a head start because we've been doing this for 15 years. And so basically we've built a handful of generalized machine learning algorithms, um, that we've basically used 700 million hours of CCTV footage to generalize. So we switch it on, it learns what normal looks like. It builds behavioral models across multiple dimensions for all the cameras and then it reports on the unusual or interesting things. And after a week it's got a full, like it understands the flow, the um, weekly cycles.

Speaker C: Yeah, threat detection. Right. Like it can basically detect threats and things that are unusual that need to be looked into.

Speaker A: Yeah, absolutely. Yeah. We've got machine learning algorithms that basically take a full day's worth of footage and reduce it to uh, maybe a percent of a percent. And then we double check with the GPT and as a consequence we can have like one person monitor two 3,000 cameras in real time. Oh, wow.

Speaker C: Oh wow. Uh, that's huge. That's huge savings. Right. Let's maybe talk a bit about your go to market a little bit. Right, so you were lucky to already have the customer with the 8000 cameras when you came in. Right. You've been thinking about your go to market since. Have you grown the business? Have you specialized in some niches versus doing multiple verticals? How do you think about all that?

Speaker A: Okay, so first of all, enterprise software is much more difficult than B2B and B2C. Well, the B2C, like the, you know, the, the time on a VGW was often four weeks or six weeks until you made your money back. Um, and you're, you know, you could test messages and the funnel within, you know, within seven weeks.

Speaker C: That was also an exceptional business model, of course. Right. It's not, not general for B2C, I would say.

Speaker A: Yeah, yeah, yeah, that's true, that's true. But enterprise software is more difficult, longer, longer lead cycles. And when you're kind of looking for product market fit, it's expensive to spread. So we found niche in the Middle east. Like we uh, rebuilt the sales team as well, so bringing in an experienced sales team. So recently we got a uh, purchase order in for $1.8 million. Our revenue is pretty low, it's like $2.2 million. So we've doubled the revenue with one purchase order for a smart city in the Middle East. And when we do a good job of that, there's another few deals in the pipeline that are like three or four times larger. And there's a lot of cameras there. So that's one go to market. We've got partnerships in Japan, we're chatting at the moment with another distributor who has global reach in robotics. They see Isatana as a key part of their consolidated security bundle. Okay, so, so, so we've got, we've got that ah, we've got emerging interest in the U.S. people are bypassing the, the incumbents in the U.S. have come into us because we, we have the expertise. But so the moment we're actually, we're putting the fine in the fine touches I would say on the go to market in the US And Australia has woken up like Australia's like hey, you know, I've got, I've got and 10,000 camera deals in the pipeline from large organizations here who uh, realize not only the AI ah can augment their existing security team, but increase their security coverage often. Like with these places, you can have some casinos here have got 4,000 cameras and the security team can only look at 200 cameras. And even then humans, like, humans get distracted after something like 2030.

Speaker C: Yeah.

Speaker A: Mhm. So it's great. So now, now that the business has come to us, you know, I'm actually in the middle of building a, we're on a hiring spree just now. Um, I've got some, I'm hiring more engineers, more sales people, more operations guys.

Speaker C: Um, how big is your team now, Kevin?

Speaker A: At the Moment there's only 21 of us.

Speaker C: Oh, wow. Okay.

Speaker A: But yeah, like, so we're a pretty small team. You know the machine learning and product team is eight deep. Uh, but we've got some pretty smart guys here. And also the IP that we've got is in the generalized algorithms like the we've got. And also because enterprise software has such long sales cycles, it was important for me to keep a small team um, because you know, like We. Yeah. And often when you're dealing with these large customers, you need to be ready to walk away and negotiate. Like the, the Middle East. I suppose everywhere is interesting for negotiating, but uh, I'm sure.

Speaker C: Yes.

Speaker A: Yeah. Yeah.

Speaker C: Okay. Okay. Very cool. And then, but your sales strategy is uh, primarily based on distributors, it sounds like.

Speaker A: Yeah, but, but sometimes the distributors need a bit of uh, like the, you, sometimes you need to take a lead, give it to the distributor, uh, you know, like make the money for them and then you know, get things, get things going. Ah.

Speaker C: And then you mentioned in, in America especially like you said, people are going around the incumbents. Right. So who do you see as the incumbents and are they your competitors or are you basically disrupting them?

Speaker A: Yeah, the competitors over there we've got ambient AI, uh and those guys raised about $54 million through Andreessen Horowitz. These like three guys that, that were in stealth from Stanford for three years. They, they kind of, they've got a bottom up approach, they've got a great product but they've got a bottom up approach where they, they're more precise. We are more accurate and that we come top down. We, you know, we don't specifically find like fights, you know, like, but we find people that have fallen over, people that are running. So, so we're more likely to find things that you, you hadn't thought about or planned. Whereas the ambient AI guys have like uh, uh, they've got uh, like uh, maybe A list of 35 specific use cases that they'll find. But we compete with them. Like we are, we are more efficient on compute. Like we can fit 400 cameras on a server. Their tech requires a lot more grunt so we scale better and we're self learning and there's no need to act. All the guys like the, the guys spot AI. They are, they're small to medium. Like, so they started that like we started at the top end, which is probably what you shouldn't do. But they started, they started at the bottom end and they're m making their way up. But yeah, it's good. Like they're educating a lot of the market over there. Like this is, this is wonderful for us to have these guys um, educated and also it's wonderful for me as a CEO. We're getting movement now so the investors are being educated on autonomous security and AI. So yeah, it's all good.

Speaker C: How ambitious are you for Istana? How big do you want it to be in like five to 10 years time?

Speaker A: So five to 10 years so okay, this is maybe egotistical but I'm going to say this anyway. I've been involved now uh, into unicorn billion plus businesses out of Perth and the market for this is massive. We've only got 20,000 cameras on the license. Right. And our aspirations, our near term aspirations, our near hag, I said you can, you can write that down is 100,000 cameras. So we've been plugging away but now the go to market like reaching 100,000 cameras seems so plausible that we've, we're looking at a million and when we look at the million cameras and again this is not crazy. Uh, there are people in our, like there are people, there are competitors who have 4 million cameras on the license.

Speaker C: Right, right, right. Yeah.

Speaker A: So the numbers are not wild. So for me that's where I'm heading. I'm heading to a million through a hundred thousand and all the numbers between there and so so when we do that then this becomes a significant business that again you know, comes out of little old Perth. And you know it's a software business. You know like we need to, to be clever, we need to scale and you know, so that's where I expect it to be. I expect Amazing. Yeah. Pretty big.

Speaker C: And uh, actually a great example to other founders of like deciding on one, what I call widget. Right. How do you measure the impact of the business in non financial terms? And in your case it's I just count the cameras. Right.

Speaker A: Ah.

Speaker C: And uh, you don't have to be confused about is it customers, is it accounts, is it sites, is it you know like just pick one and go with it. Right.

Speaker A: It's funny like because I was chatting to some remote video monitoring services in the US and um, and they um, they, they don't count cameras, they count revenue. And and my leadership team were like hey, why don't we count revenue? And I was like because the abstraction makes things much easier to share. All your numbers and your you know, and your growth and your planning. You know like if we yeah it's, it's ah a, it's a strong scale up move to find the unit economics.

Speaker C: It's that and also uh, yeah the unit economics is really the real reason. But I would also say uh, from our joint experience it's also so much more uh, inspiring for many people on the team, especially lower ranks because nobody's going to get inspired by more dollars. Right.

Speaker A: And the cameras is nice because it gives us an idea about how many people were keeping safe. Look, we've got stories of actually Saving people's lives. So these are the stories, um, that we like to hear and share

Speaker C: built there. Right. Like about people keeping people safe. And more and more stories there will really inspire people to know they're doing something good in the world.

Speaker A: Yeah, exactly. You go to sleep asleep like a baby, knowing that my AI is keeping people safe. So.

Speaker C: Yeah, that's amazing. Yeah, very good. Well, uh, Kevin, this has been a pleasure. Now that you've gotten yet one more company under your belt and you've got so much experience, I'm sure you talk to younger founders, people who come behind you every now and then, what's the typical advice you share with them?

Speaker A: I think, okay, just do things you enjoy. Don't do things that you don't. Also. Okay, uh, from a founding perspective, because I've got one of the young guys here is leaving the start to become an entrepreneur. Um, find a group of people that you want to help. Don't go looking for an idea. Go looking for a group of people that have a problem that you can fix. And keep doing that, uh, and everything will figure itself out.

Speaker C: Yeah, I think that's really good advice, like, because it immediately helps you understand, like, what would the customer think about this? Right.

Speaker A: Yeah.

Speaker C: And you start thinking in terms of pains to solve also what is good enough. I love that approach. Really good.

Speaker A: Yeah. Awesome.

Speaker C: Very cool. Well, thank you so much. Kevin Brown, ah, uh, founder or re. Founder and CEO of Ice Tana, dialing in all the way from Perth, Australia. Thank you. It's been a pleasure. Any last words for the audience?

Speaker A: Um, no. If you find yourself with a startup and you find yourself struggling with scale more than business, then give Roland a shout. He's helped us build, uh, a few a billion dollar business and there's a few more in there for him, for him to help you out with.

Speaker C: And nobody's going to believe this, but this was completely unprompted. So I really appreciate this, Kevin. Uh, thank you so much. Um, and for the audience, we will have another episode for you ready next week. Thank, uh, you everyone.

Speaker B: Like what you heard? Subscribe to this podcast and leave a review. Tune in next time for more hot startups and interviews with some of the highest momentum startup founders in tech today.