#95 - Leveraging AI to build an intelligent operating system for retirement and wealth providers

Speaker A: Welcome back to the Building and Growing podcast. We're delighted to have Michael Watkins from Aurum with us. Michael, welcome.

Speaker B: Thanks, Lucas. Good to be back and yeah, good to be in New York as well.

Speaker A: That's right, yeah. First podcast, uh, filmed, uh, uh, in the U.S. um, and you know, New York's a fantastic place to, uh, film it. We've got a great studio here.

Speaker B: Yeah, it's fantastic. Very, very good.

Speaker A: That's it. Look, Michael, um, the first time we did a podcast on Orem, I think it was back end of 2023, um, you know, just before you sort of moved out or, you know, right after you'd moved out to, um, Abu Dhabi. Um, you know, so fast forward, we're nearly two years down the line. Uh, and you know, I imagine you guys have made a lot of progress, which we'll dig into. But before we do that, do you want to introduce yourself and you know, sort of give us an overview of RM itself?

Speaker B: Yeah, sure. So it's uh, 2022. So it's been three years now.

Speaker A: Oh, wow.

Speaker B: Even, even longer than we thought. But, um, yeah, so Mike Wat, uh, CEO, co founder of Aurum. Aurum is an operating system for retirement and wealth providers. So basically think, you know, we take your data, we take your products and your processes and bring that into a single platform. Um, so yeah, that's, that's who I am. That's what we do.

Speaker A: Fantastic, mate. And um, look, uh, you know, can you talk to us? I guess how sort of the proposition of Aurum has, you know, maybe evolved since that first, uh, podcast in 2022 to now.

Speaker B: Yeah, so we, um, I think initially we were under the impression that we would have to, um, prove our technology before we could sell into enterprise clients. Uh, so we kind of took the approach that we would do a B2B. Sorry, a D2D2C. Um, B2B2C proposition, um, for ourselves to kind of prove that it would work, sell into enterprise corporations and then flip to the pure kind of SaaS, uh, model. Um, and as it kind of played out, we didn't have to do that piece. Very technology kind of speaks for itself. We could go direct to selling technology. Um, and that's what we're doing now. So we just license our technology to large financial services institutions. Uh, we're working with the largest in uh, the UAE and getting a ton of traction outside of that as well in other, other markets.

Speaker A: Fantastic. That's great. And so, you know, I mean, you mentioned that I guess you're focusing on that Sort of that technology piece there. Are you able to maybe talk us high level through, um, some of the different problems, um, that you know, your buyers might face in various markets?

Speaker B: Yeah, so I think there are probably a few different things that we solve for, but I kind of bucket in into three. So first is that data typically exists in different systems because they're running maybe three, four or five different platforms or all of their data. Um, second is that their products, again, if they're running three or four or five different, uh, platforms, their products are split across uh, different platforms and therefore the experience is really disjointed. And then it's really hard to get kind of an overall view of how processes and workflows work across those products and services. Uh, so they're kind of like the three main problems that we see and that then expands into if you're a multinational corporation, you've got, you're providing retirement products in one market, maybe even several markets. And how do you have a consistent joined up experience across those? Um, so they, they're kind of like the big problems that we solve for. Uh, we wanted to be a global platform from day one. So we built, that's part of the reason why we built in the uae. Um, and yeah, and that's, that's kind of where we're getting lots of interest and traction because we're solving those big costly problems for our, for our, uh, our customers.

Speaker A: Fantastic. That's great. And can you talk to us, I guess about that journey of, you know, setting up in the UAE and you know, the initial traction that you got there?

Speaker B: Yeah. So, um, obviously, obviously it was a new market or relatively new market. I had some exposure to it before, but um, it was again like part of the reason why I moved out of there. The regulation there is very dynamic. Things happen quickly, uh, change happens quickly. Uh, so there was kind of an initial period of finding feats, making sure that we had the right talent around us. Um, that was kind of probably more challenging because you just don't have the same networks. Um, but once we kind of created the foundations, it's kind of, it's been pretty smooth from there out. We have like fantastic people that work there, half of our team in the uae, half of the team outside. Um, and yeah, it's been a happy journey so far, I would say.

Speaker A: Fantastic. That's great. And look, you know, we find ourselves here in New York today. You know what's brought you over here?

Speaker B: Yes, I mean for us, uh, like I said, our platform is Global from day one, uh, the retirement market globally is absolutely huge. What $65 trillion uh, of assets, um, and billions being spent every year on maintaining kind of legacy technology. The US is a huge market, um, and I think probably will be the most important market for us. So we are over here for a couple of different reasons. So we're speaking to prospective customers, partners and we also have a conference here as well next week. Um, like I said, we see this as a very, very important market for us. So we want to be here, we want to be present and uh, really solve some of the big problems that are facing the US retirement market.

Speaker A: That's great. And I guess um, you and I met in the British um, sort of retirement market space. Um, for those in the audience who might be more familiar with say the British market or UAE market, do you think you could talk us through sort of some of the differences of what happens in the US Market?

Speaker B: Yeah, sure. So I mean for those who are familiar with the UK Auto enrollment is now very like prevalent. So basically what that means is that people are automatically signed up to some form of like retirement or pension saving. Uh, the U.S. u.S. Is very different in the sense that um, it's kind of employer led. So there's no kind of mandating or hasn't been any mandating until recently. Um, so you kind of have this uh, kind of multiple different product type where uh, some uh, individuals have no coverage whatsoever. Some have some coverage. Um, they've recently now obviously been kind of the Unsecure 2.0 act, which is brought in kind of an auto enrollment style system, um with uh, board employer plans. Uh, so we're kind of seeing like same problems and different problems faced in the market, uh which is why it works quite well for us.

Speaker A: What is your typical client?

Speaker B: Yeah, so um, our typical clients are, are ah, banks, asset managers, pension providers and how we typically work with them. Um, like the nature of our products means that we can prove value like within the first day to week. Um, so essentially what we do is we kind of understand what their problem is. We have kind of host a workshop, uh, or series of workshops to kind of get to the root of like what they're trying to solve for. We configure our platform for that problem and then essentially what we do from there is kind of um, take them from that day through to release and that can be anywhere from you know, two, three, four weeks up to a few months depending on the level of complexity. Uh and obviously the regulatory risk, compliance risk that they need to get signed

Speaker A: off you know, I mean you've mentioned I guess the speed that you're able to help them launch solutions and products. How does that compare to say a typical um, typical route to market currently?

Speaker B: Yeah. So I mean globally our competitors typically are anywhere from like 10 to 30 year old technology platforms. Um and I don't think there are many examples of 10 to 30 year old technology platforms that are able to move quickly. Uh so you know if you're going from zero to implementation it will take anywhere from nine to 18 months, sometimes more for our uh, competitors to get something off the ground. Where whereas like I said for us we can do an implementation in as little as a day. Like obviously in reality there's like I said all of compliance, legal and all of those things. But for our part of the deliverable it could be as soon as a day. Um, uh, but more pragmatically it's probably in the four to eight weeks because uh, there are various pieces that need to be tested, refined and everything from the business side.

Speaker A: Indeed. Yeah. And look, I mean that's a significant amount of time saving and I imagine budget saving as well. Um, delivering something in four to eight weeks as opposed to nine to 18 months. So can we I guess dive a level deeper into that as to how you're able to help those clients achieve you know, such, such a huge um, uh reduction in their time to market?

Speaker B: Yeah, so we, we built around this problem that uh, there's a heavy involvement from like engineers to like write the code, build the technology. Typically for any like implementation, implementation um, the platforms are rigid so typically they're built for like one thing and they're being asked to do multiple things. They need to be like heavily customized. So we basically build a platform that um, is highly configurable. So we have these basic concepts around. Money comes in, something needs to happen to that money and then money goes out. But outside of that um, we built for multi, uh, language, multi currency, uh all of the comms to be configurable, all of the copy and content to be configured configurable. And then of late we built something really cool which is um, an AI workflow product builder, um, which essentially allows us to take any product rules, input them into an LLM and then outspits the kind of the code that needs to run in the background to kind of calculate um, how that product should work. Um, so all of these factors mean that we kind of, we're prepared for the use cases that we know our customers want to see. Yeah, and just massively increases the uh, rates of execution. Yeah, the other, the other important thing I think to mention is it also means that they aren't relying on engineering resource and they can also extend their own proposition themselves. You know, once they feel comfortable with the platform, they can continue to build IP like within the platform without having to build on the side or on top of.

Speaker A: Yes. Fantastic. And look, I mean uh, I guess just time back to kind of the first podcast we did in 2022 to now. Um, you know, you're talking about the fact that you know, you're going to be able to offer the sort of AI workflows in order to reduce that time to market. How has technology changed over those past three years? Um, to facilitate this product? A new proposition.

Speaker B: Yeah. So we launched Aurum in September 2022 and I think it was November 2022 when uh, ChatGPT 3.5 was, was launched. So we've kind of like run in parallel to all of the AI developments that have been happening, which is like from a timing perspective for us is perfect. Yeah, we have been very deliberate in not jumping straight into a solution and thinking like thoughtfully about what problems do we need to solve and how do we apply this in a way that manages risk, in a way that manages kind of um, a changing environment in the AI landscape. Because you've seen uh, a number of startups come and go because you know, OpenAI have kind of eaten them uh, through, through development.

Speaker A: Yeah.

Speaker B: Um, and we've really kind of hyper focused on the specialism that we operate within, um, and solving a couple of use cases. So I mean technology has changed hugely. Um, we were talking the other night, I don't think it's uh, it's transformational today, but it's not transformational. It's as it will be in the coming years as it evolves.

Speaker A: Indeed, indeed. And you know, what sort of level of co creation have you had with um, you know, I guess the sort of banks and pension providers that you know, you're working with, um, providing this solution to.

Speaker B: Yeah. So um, by way of background, I mean I've been in this industry for over 20 years now, have a firm understanding from like working in kind of almost every, feels like every role within the industry. Um, so collectively as a group of people who have also shared some of my experiences, we're very opinionated about what the problems are and how to solve them because the tendency is to people get uh, quite complacent about this is how things are and this is how they will always be. So we obviously, excuse me, um, obviously we have uh, collaborated and co built with partners that we're working with in terms of like what, what the solutions need to look like for them. But we are, I would say 90 to 95% are just opinionated in how we believe these things should be executed so that they're future proof for the future.

Speaker A: That's great. And you know, I guess when it comes to the adoption of AI, I think you know initially it was quite consumer driven as you know. You mentioned ChatGPT kind of took off at the end of um, uh 2022. Um, how are you seeing financial service providers uh, adopt um, AI into I guess you know, some of their key infrastructure.

Speaker B: I think there's probably two parties in financial services. So there are those who have uh, formed partnerships with the general purpose model providers um, and are active, actively working with them to kind of um, utilize it in their back office functions and some of their front office pieces as well. Like a few examples I can think of like I saw Citibank uh, in the last week announcing they built like AI advisor tools. Um, so I think they're going a bit deeper. They've spent a lot of time and money on their data infrastructure. Um, and then you have others who are kind of more I would say passive consumers. So they want to be involved in the hype but they don't either have the infrastructure or knowledge in terms of like how to implement it successfully and meaningfully. Um, and they kind of have just bolted on you know like chat interfaces or whatever. Yeah, um, something that's not particularly scalable. So I think there's a general interest. But the problem that you have with financial services generally is like there's a ton of risk involved. Right. Like you need to make, you need to get it right. You can't afford to not get it right.

Speaker A: Yeah.

Speaker B: Because if you do, like that's going to be a big fuck up for you know, um, for that company.

Speaker A: Indeed, indeed. And you know, how do you see CTOs kind of approaching that, you know, risk versus reward?

Speaker B: Yeah, I think um, I mean naturally, and I wouldn't put everybody in this bucket but CTOs typically are quite experimental, again depending on the person and the organization. Um, so I think there is a desire, but like I said, I think the rate limiting factor for most financial services organizations is just they don't have the infrastructure to be able to achieve the things that they want to achieve and it comes in amongst like you know, a bunch of other burning problems they have. Right. So I think Today for most companies, AI is still seen as a novelty because people can't think of like, you know, uh, solid applications that they can apply it to that isn't just a novel, um, a novel thing. But that's probably just ah, call it confirmation bias or you know, um, experience lock in where they've just had one dimensional thinking for the past 20 years and therefore like it's really hard to be like innovative with how you apply new technologies.

Speaker A: Indeed, indeed. And you know, when I guess say the infrastructure piece starts, um, to be solved. Do you think there are any other key challenges that they're facing, uh, when it comes to adopting AI?

Speaker B: I think two things probably. So one would be uh, like data privacy protection. Data is always obviously a, ah, subject that gets a lot of attention. Um, so that is definitely one. And then I've completely forgotten what the other thing was. I was going to say come, um, back to me. I'll remember in a minute.

Speaker A: Yeah, yeah, that sounds good, that sounds good. Um, and uh, you know, I guess we've spoken a fair bit about the US market here and the opportunities that there are here. Are there any other markets that you know, you've been looking at recently for expansion?

Speaker B: Um, like honestly like we're here to win. Like we want, we want to be the number one technology provider in the retirement and wealth space globally. Uh, so I mean we're actively in conversations in 13 countries, um, and I think it's only a matter of time before we kind of have impact in those companies. Like we, we're a small but growing team, um, and we're definitely not trying to bite off more than we can choose. So we're trying to be like hyper focused in which markets we go into, uh, first until we're at kind of sufficient scale to be able to run multiple markets at once. But I do think that one of the efficiencies that we have as an organization is our technology actually stands up. So there's not a heavy reliance on having tons of people for implementation. There's not a heavy reliance on tons of people, people for sales delivery, um, because the technology is designed to be implemented quickly and realize value. So we're very fortunate in that regard. But um, yeah, our focus at the moment is continue to do an excellent job for our customers in the uae, um, and the US is the next market for us.

Speaker A: Fantastic. That's great. And you mentioned, I guess, um, uh, team size, um, when we did the first podcast, you'd closed an investment round back then. Um, do you have any sort of funding plans, uh, for the near future.

Speaker B: Yeah, so we raised one round um, since then. Uh, so we closed that in last December. Um, so that was awesome. To bring on another institutional investor. Um, we raised $3 million. Another advantage of our business model is that we're incredibly capital efficient. We don't need to raise huge sums of money, uh, to be able to kind of capture value. Uh, we will be raising another one. So we'll actually be kicking that off in a couple of weeks when I'm back from the U.S. um, we have an incredible uh, list of investors interested, uh, and our uh, current investors also looking to double down. So you know that puts us in a really good position. Um, and really now it's about kind of like three areas for us which are we always want to go faster because we're like very clear on what it is that we're, we're delivering, what our, what our future looks like. We want to continue delivering excellent service for our customers because we built that reputation today. And we want to make sure that maintains into new customers but also making sure that we can maintain it for our current customers. And then the final um, area of focus for us is like actually having boots on the ground, like being present in the markets that we want to go into because building relationships is incredibly important. And whilst, yes, we can do that remotely and all of those things, you need to live through, feel and breathe your customers pain to like fully understand it.

Speaker A: Indeed, indeed. And look, I mean um, you know, the fundraising environment back in 2022 was you know, not great. I guess it's improved slightly over time. But um, you know, AI has been a really key sort of factor in terms of unlocking investment recently. Um, you know, I guess the type of institutional investors that you're raising for from um, may not have had as much say AI exposure compared to some of the, the other sort of vc, um, style investors. How are you seeing, I guess their thoughts and appetite for it change?

Speaker B: Yeah, I think. I um, mean it's kind of well documented that there's a ton of money going into AI at the moment and you know, lots of people comparing it to kind of the uh, the dot com bubble. Um, personally I believe that, I mean there undoubtedly is a bubble because I think you can't, there isn't enough focus on long term value. I think that's probably the thing that you're seeing but naturally you have to take bets. As I said, we were very conscious about how we embed AI into our solution, um, to make sure that it was embedded first and foremost and not just a novel feature future. Um, but we are a technology company and I think one of the things that people should understand is that just like the Internet is and was a technology, AI is exactly the same thing. So you should focus less on the tool and you should focus on the problem and the outcome. Um, so we see it being critical to our uh, technology stack for the foreseeable future. Um, but we're not just waving an AI flag because, because we're like okay, if we say AI then we get another 10 million in funding. There's no value really in that. Uh, yeah, um, so yeah, summary, lots of money going into AI, but only a few of those bets will actually uh, bear any fruit.

Speaker A: Indeed. And I think it's a really good sort of opportunity to dive a level deeper in terms of the impact that AI has had in terms of what type of products you're able to offer. So you know, I guess do you think that it's led to you guys being able to offer a much sort of broader and more thorough say solution? Uh, I don't want to ask a yes or no question. So I think it's better for me to say how has that impacted your product offering?

Speaker B: Yeah. So uh, our plan has never changed but like I said, and this is why I think about AI as just being another tool in the, in the toolbox. Um, but our ability to execute on that faster has definitely been enabled by AI. So um, we always like our plan was always to build a global platform, our plan was always to build a multi product platform. Um, and we built the infrastructure to enable that. And now the part that we can kind of create the most value with is by leveraging LLMs to handle the product rule engine. So you don't need an engineer to write the code for every single product. And if you think like, you know there are many, many products just in the vertical that we operate in. There are many different like product rules, regulations, uh, depending on country to country. Um, so handling that via um, uh, large language models is like, it's fundamentally game changing. It's a huge value. It means that we as a technology provider can go faster. It means our customers can go faster. It means that they, there are, uh, it's more robust, more visible and there's less dependency on you know, like I said, uh, engineers, technology, uh, so the cost to serve comes down significantly and both from our perspective in terms of, you know, the headcount that we need to build these solutions out, um, and then that being passed on to not only kind of our customers, but their customers as well.

Speaker A: Yeah.

Speaker B: Um, so it's huge value, huge unlock.

Speaker A: Indeed. And you know, I mean you've mentioned sort of retirement as a value vertical a few times. Are there any other verticals that you'd like to apply? I guess that same methodology to the.

Speaker B: The short answer is yes, I would like to eat the whole world. The longer answer is we're very focused on what we're doing now. So um, retirement is our kind of primary focus. A secondary focus, because it directly relates to retirement is like the broader wealth proposition.

Speaker A: Yeah.

Speaker B: Um, and we're all already kind of building out products in that space. Uh, but as a supplement to kind of retirement pensions, uh, workplace savings. Um, but by definition like what we've built can be taken in many different directions. It is elastic. It can be because the concepts are uh, similar across financial services. Typically money needs to come in, something needs to happen to it and then the money needs to go somewhere else. So if you take that basic premise, uh, and you have enough elasticity in your products then, then there's kind of no limit in terms of what you can do.

Speaker A: Yeah, fantastic. That's great. And I guess, you know, a question in terms of um, go to market, um, because you know, I guess a lot of people are, you know, seeing these things on LinkedIn which are all about, you know, high volume, sort of cold calls, cold emails, death of um, you know, cold marketing. You, I guess as a business are not looking to sort of reach out to tens of thousands of SMEs, um, like a lot of tech companies are. Ah, there's a very, I guess, well established pool of companies, um, that you're establishing relationships with. What does that go to market process look like for you?

Speaker B: Yeah, so I mean I had this conversation earlier today, interestingly. So, um, up until now everything that we've been doing is kind of product led growth. Uh, so we have a product, it solves a clear problem and then because it solves a clear problem in a kind of an excellent way, we then get referrals to other clients. And that's how we've acquired our first six clients through word of mouth and reputation. Uh, but taking that internationally is a very different sales motion. So for us now it's about complementing product led growth with sales, their growth. Yeah. And I don't think they're mutually exclusive, just to be clear. So we're not, we're not just uh, going to hire a bunch of salespeople who take, you know, ah, an Order from, from the customer and then bring it back and say, can you build this? Because our product solves the, the problems that they, that they, um, that they have. So we, um, we've, I mean, we borrowed methodology, uh, from Palantir. I mean everybody in the world now knows who Palantir are, but we've kind of been banging this drum for a long time. Um, we believe in kind of working hand in glove with our customers. So we have kind of a full deployed engineer model. Uh, we have deployment strategies. So people again, who work clearly to not, not just understand the problems, but to articulate the solution to the problem to maximize the value. And I think that again, like, this is something that a lot of people misunderstand around. Like how that role works is. It's not about, um, like I said, order taking, it's about actually affirming the value that's being created by the solution, um, and doing that in a meaningful way. So we won't just, you know, if somebody wants something that's like 50% different from what we have, we'll say no. We're comfortable with saying no because we believe that the way that we built things is the right way.

Speaker A: That's great. I haven't heard that term of kind of uh, deployment strategist before, but, um, certainly it makes sense in terms of really affirming the value. And there's, I guess there's that saying that you shouldn't win work just for the sake of kind of delivering it or doing it in a way which you don't think is the right way because, uh, ultimately it comes back to your reputation afterwards.

Speaker B: Uh, yeah, I mean we, to use a weird analogy, but if you think about your iPhone, for example, you buy an iPhone because it does like a few shiny things that you like. But mainly it's I pick up the phone, I'll call, I'll message, whatever, and scroll social media. Um, but there's a ton of rich value that exists within that product which you may never find.

Speaker A: Yeah.

Speaker B: So like their job is to basically make sure all of that rich value is unlocked and that the experience is cohesive. And that's like we, we call our platform an operating system for that reason.

Speaker A: Yes.

Speaker B: Because it isn't just about, um, doing some very like, um, you know, low value parts, uh, of the value chain and workflows. It's about how do you connect, you know, the whole experience and allow them to build products, services, you know, on top of that.

Speaker A: Yeah.

Speaker B: And do it in a joined up way, you know, access if you think about like iOS, right. Like your whole life lives inside of your Apple id, you know, all of your data is there, you have your applications that sit on top and the fact that you can join all of those pieces together with like you know, login with Apple or um, you know, simple features like being able to copy from your iPhone and paste it onto your, onto your laptop.

Speaker A: So useful.

Speaker B: Yeah, yeah, I use it like 20 times a day. But the fact that you, you have like this um, connected ecosystem that you can build on top of builds you know, your use cases on top of like that's what we are, we're replicating in kind of retirement and wealth spaces. Like it isn't just about single point solution, it's about an ecosystem or an operating system. Yeah. That can be used for multiple things.

Speaker A: Fantastic. And look, I guess you know like when we met the sort of the fintech ecosystem in London was growing. You know, I joined Revolut. I know that, you know we've just walked past Monzo's office over here. Um, you know Wise has kind of, you know I think is going to delist uh, in the London Stock Exchange and list over here in New York. So we've seen you know, a consolidation I guess of the fintech ecosystem. But where do you see that going next?

Speaker B: I think it's really interesting right, because you've got the, this kind of uh. I don't think the US is thinking about Europe but Europe is always thinking about the US and um, I think what you have seen is uh, kind of a manifestation of like decades worth of like embedded social um, conventions and norms. The US is just more like risk on. They're more uh, able uh as a society to say we think we can do this and therefore we are going to do this. Whereas in Europe like I think that's probably not so much the case. Um, there's kind of, I don't know whether it's like shaming ah of like you know, too afraid to fail because like somebody will say something bad. Um, but yeah, I mean you kind of AI has almost like given some kind of level of resurgence to the European, um, European ecosystem from a startup perspective. But I think ultimately the reason why the goal is always to the gold standard is kind of cracking. The US is because a, it's obviously the largest market in the world. Um, but you're really running with the big boys if you can be successful in the US So I think it'll be an interesting time for the European ecosystem. Um, there's tons of Capital there, there's tons of opportunity but it's quite disaggregated in the terms of a market. Um, I mean again I'm going down a rabbit hole now but like the UK leaving the eu, um, the EU not really operating as like a single, single economy. Um, that's kind of a limiting factor. I think if you, if you had a few of these things where like there was the EU is more of like a, a single economy then you end up in a situation where it kind of rivals the US from a market size perspective. Yeah, um, but the, Yeah, I think Europe is just a few, very, very difficult place to build. Um, lots of, you've got all of the right components but just a few key elements missing.

Speaker A: Yeah, yeah, gotcha. And you know, I guess Orem aside, what, what would you say excites you the most when it comes to AI in fintech?

Speaker B: I think it's everything that we don't know today. Like um, I think like again like we were kind of talking about this the other night. I think um, the broader, you know, we exist on kind of an adoption curve. This is like a, you know, well known fact. Um, we're still very early on in that adoption curve and it's really about how you like fully integrate through that adoption curve like AI. Um, and I think when that kind of, when we get to kind of the last third or fourth or the last quarter, um, that's where it will start to become really interesting because once you have like main stage adoption, um, jobs will get replaced and uh, there will be probably seismic shifts in like how the technology evolves from that point. Yeah, um, I think I'm just really interested to see kind of the specific use cases that drive the most amount of value specifically in the financial services because that's my world. But more broadly in sciences, uh, health for example, um, and physics because yeah, like that's where kind of the global societal shift will happen. Like financial services is obviously fantastic. But um, saving people's lives and discovering new science, new physics or whatever is like that's. Yeah, that's fundamental.

Speaker A: Indeed. Indeed. Yeah. I mean, you know, you think about, I guess um, you know, certainly I wear a wearable, you know, and it tracks all my health. Well, I guess some health data in real time. You know, what will happen when there's you know, chips for example, um, that are going into people and you've got you know, real time data being fed into LLMs. How much are we going to learn about people and you know, preventing like the prevention of diseases, um, because I think AI helps with diagnosis. Um, you know, hopefully it's going to help with treatment and prevention as well.

Speaker B: Yeah, so I had an interview today and a really interesting guy that I was speaking to, we were talking about. So we both have this thing where um, you know, like, if we want to keep notes, there's no like format or that kind of works for either of us. Like my, the way that my brain works is um, don't really know how to. It's kind of like an ugly puzzle, uh, where you know, like the shape and size of things needs to be in a specific order. But it's like very specific to me. Um, and he was talking about broadly, uh, how to solve that problem. Um, and my belief is the mediums in which this information is kind of recorded, the interface is more important to solve before you solve the platform. And by that I mean today we're heavily dependent on phones, um, but we have another number of other devices. Like you said, wearables, you have headphones, you know, you have got meta glasses. I, um, think there is no single solution as in there's no silver bullet where it's just like one device that solves all these things. I think it's like all of those devices seamlessly being connected. Which is I guess why I'm probably most disappointed in Apple's AI strategy to or like execution today. Yeah, um, but I think this will, this will apply like across all sectors. Once you have like a really joined up ecosystem across the AI space, uh, then you can kind of unlock a ton of value in terms of um, sentiment analysis, memory, like you said, health data, all of these things that are kind of interdependent. But you maybe don't realize that today just having a global view of how you navigate the world and what you need, that's where the real value will be unlocked.

Speaker A: Yes, indeed, indeed. That's fantastic. Michael, we've covered a great deal today. Um, uh, so I actually have kind of a bonus question for you before I ask my closing one. But um, we talked about employee count and building efficient teams. Um, now in the past, during um, the previous sort of startup, um, funding years, let's say employee headcount and you know, funds raised were like two big um, metrics. Whereas now it's becoming increasingly clear that you can have a very small number of employees and a very, very high revenue business thanks to AI, what do you think the next metric is going to be?

Speaker B: Yeah, it's a good question because it's kind of like inversely Correlated, um, what kind of has but hasn't? Because I think it's more of like a badge of honor. Right. Like if you can hit, uh, a billion dollars with one person, which is kind of like the. Now the kind of the. Who is going to do that? Um, I think from a metrics perspective, it always has to come down to value. Right. And I think the trick that's being missed in this kind of AI frenzy today is will that value be there in 5 years? Will it be there in 10 years? So these companies are hitting like 100 million ARR in 8 months. Is it still 100 million in 10 years or is it actually now 5? Or they no longer exist? Um, like I said, you have these innovators, you know, if you go through the adoption curve, then naturally, you know, there's always going to be like, people who like, give me this new product.

Speaker A: Yeah.

Speaker B: Um, and the AI landscape, like, it's an echo chamber. Right? Like in this space. Sorry, in the startup, um, startup, uh, space, it's an echo chamber because we are innovators by definition. You have to be if you want to, you know, create a new company.

Speaker A: Yes.

Speaker B: Um, but so, um, this is a really long way of me saying that I think the value, the metrics are the same. I think they just maybe get tapered down slightly.

Speaker A: Yeah. Fantastic. And I guess going back to my original question then, you know, um, is there any, anything else that you want to sort of, uh, add?

Speaker B: Um, no. Look, I think, uh, like my ambition, our ambition as a company is very clear. The problem that we're solving is a very big and important one. One that gets like, massively overlooked. I think it's probably worth, you know, noting. You know, there aren't a ton of, uh, startups in the retirement space. This is kind of like once every five years, ten years, uh, do you get a new one versus like payments, where it's like every ten minutes? For the length of this interview, there's probably ten new payment startups.

Speaker A: Yeah.

Speaker B: Um, so, yeah, I think, um, we're very committed to what we're doing. Um, we're solving a very big problem. Uh, and we will solve that problem, uh, and continue to solve that problem.

Speaker A: That's awesome. And you know, one final question. Um, just because of, I guess, you know, the success that you've had, you know, in your career and I guess, you know, as I know you as a person as well, are there any final takeaways you'd want to share with the audience?

Speaker B: That's a good question. Um, family makes you focus. There you go. That's my, uh, sound bite family. Makes you focus. Perfect.

Speaker A: Michael, thanks so much. And, uh, we're looking forward to watching Aurum continue to grow.

Speaker B: Thanks for having me, Lucas.

Speaker A: You're most welcome.