How Cleo Reached $400M ARR: Barney Hussey-Yeo on AI, Growth, and Building a Consumer Fintech Unicorn

0:00Welcome back to Riding Unicorns. Today, we're incredibly excited to have Barney, founder and CEO of FinTech Unicorn Clio on the show. Barney started building Clio as an AI product long before the current LLM hype cycle. So we're really interested to find out where that inspiration came from. And we're going to hear more about the journey of going to the US and scaling from zero to now$400 million ARR, which is amazing. So Barney, welcome to the show. I work at Redbus Ventures with Simon, who are obviously very happy investors in Clio. You were super ahead of the curve when it came to building with AI, particularly for consumers and on the application layer.

0:42So what was it that kind of gave you that foresight that this was going to be a massive opportunity? Yeah, well, thanks for having me. But I think the thing that I was really lucky to do is go to a really good CS department, do my master's in machine learning. And I think being in a computer science department, like a good one, is probably like the most interesting place to get ideas from. Because all of your professors are right at the edge of their fields. And they're all kind of like 20 years ahead because you've got to have this fundamental research that is nailed and done way before commercialization.

1:16So, you know, back then they were talking about bioinformatics. machine learning was my core so everything was machine learning it was robotics swarm robotics there's a project on swarm robotics which is now like a bit scary because I know what is happening in the world of drones but it was this fantastic place to learn what was coming and if you looked at the research outplay and computer science at the time when I started in the early 2010s it was all vision so we just had neural nets we'd beaten I think it's the Alexa net benchmark and that was the exciting thing but just as i was kind of doing my masters and after natural language processing became dominant research output and if you looked at all of the h index accumulation it was coming from natural language processing so i was obsessed with how machine learning could be applied to ai assistance and to language and then you know everyone you guys the world kind of woke up when 3.5 was launched and you had chat gbt but anyone kind of paying attention knew about the transformer architecture two three years before that everyone knew in machine learning this was coming it was just that was a catalyst moment for the media and kind of the lay people and it's now obviously the biggest thing in in the world and it's going to transform our society our economy where we live for good and for bad and it's an amazing time to be building i want to get onto your like insane revenue growth but just before we get onto that i think people need context could you just explain like what you guys actually do so clio is an ai assistant for your money Very simply, we're trying to build the financial companion, the assistant, the coach for a billion people.

2:50We're building an AI that feels like a friend, feels like a human. It becomes radically personalized to you as you interact with it and you speak to it. And it learns from your data and from the context that you give it. It basically becomes a always on, always available, 24-7 proactive assistant that is kind of pushing you the exact right thing to do all about your finances every single day. So it's helping you plan for really long term horizon events, whether it's getting a mortgage, retiring, whatever it is, it's working back from whatever your goal is to give you daily actionable insights and advice to help make you a little bit richer every single day.

3:27Love that. Hopefully all of our listeners are going to be users and that much richer as a result. But yeah, so on to your like wild revenue growth, especially in the US. Can you talk a bit about that growth and the operational challenges that it comes with? And maybe start with those. I want to get on to like the psychological sort of shifts you must have experienced. But just talk about the growth and the sort of operational tensions. The central tension at the start was there was no revenue. The first four or five years, we had made no revenue. We literally just focused on building the AI system, just getting we connective users.

4:04It was like a pretty out there strategy. I'm not sure I'd do it again. I was pretty brave. I was pretty young, but I was kind of adamant that we're just going to build like a world class product, make people love it. And then we'd do revenue later. I was very good at raising capital in the early days. It was the Zirp era, right? So capital was kind of like freely available. It was easy to raise. I never had to do a proper fundraising round where I like went out and pitched people. it was always people wanted to preempt the round and just give me money so i thought i was hot shit i wasn't it was like the macro and the zirp era but it makes you a little bit overly confident so we had the reckoning with the covid which is when i raised the series b and that was a tough round because it was just before covid we work had crashed uber just crashed like the entire landscape was changing from Zirp to COVID.

4:56And I raised 25 million pounds at that point. And I was like, oh my God, we need to build a real business model. I'm burning 2 million a month. I've got no revenue. I've got no business model. It's time to go. So that was like a 180 shift. Just as lockdown changed our lives, it definitely changed the business as well. So it was a pretty intense kind of couple of years, but yeah, we successfully made that shift just from a feature to a kind of global products with lots of product lines that are kind of tens of millions in revenue each and so much more diversified and real enduring business today yeah okay so you switched on charging for certain products what were those phases of growth but you're now 400 million ARR so like what were there distinct phases do you think it took seven years to get to 100 million so it's not like an overnight success like seven years to get to 100 million ARR that's actually kind of standard if you look at the data there's some ai companies these days that do it like two days but that wasn't what was happening back then but seven years a long time you're grinding out to get to your first hundred not profitable in any point during that journey really grinding to get to the first hundred once we got to 100 though the next hundred was in like 19 months the next hundred was in like 12 months the next hundred was in like no do you mean it's just it's an exponential then and it's a machine and it just keeps growing.

6:14So the first hundred million is absolutely savage. It's the hardest thing you're ever going to do in your life. It's brutal in every single way. They're kind of subsequent hundreds exponentially easier to be honest. And Barney, the product's now available in the UK, which is very exciting. The UK launch is off to a good start. If things are sort of easier now than they were when you only had a month's runway, how are you preparing for the shift from being slightly under the radar because your customer base and revenue was very US, solely US really, to now you will very quickly be seen as one of the UK fintech icons and that shift in awareness around Clio in your local market.

6:59How are you preparing for that personally? We've got this great talent brand. We're backed by the right VCs. Like Clio is always in the press and stuff. Normally for good reasons. and yeah people know we're like a top tier company and i think it largely comes down to like if you look at linkedin you just look at who actually joins clio everyone's really been successful in their careers it's a very high quality group of people and a very smart group of people that's highly research focused so it's just in the uk it's like has a great track record for hiring and is actually pretty easy for us the harder thing is going to be kind of you know we're going to do Australia and Canada and France and they're going to be harder markets for us and that's where languages culture regulation all comes into play and is a little bit different the UK and the US are fairly similar in some regards it's going to be more challenging doing Japan or Latam than it is here so no I'm excited for all those challenges we want to be global we don't want to think about just two markets we want to think about a billion people and being something's pervasive around the world.

8:05Awesome. And with consumers becoming more and more used to working with LLMs or chat AI products, how has that helped the Clio story as well as people become very, you know, accustomed to using products like this? And also, what are the sort of data motes and defensibility that you're baking in to ensure that Clio remains as the leader in the sort of finance advisory space? yeah it helps on just helps on acquisition as soon as chat gpt kind of came online our cost of acquisition came down because people were willing to use these products and kind of got more accustomed to them so if you look at our growth since 2022 it's just been like a rocket ship proper rocket ship and it's become a lot easier for us to do so you know i've got to thank them for that and obviously want to compete with me through the journey but you know not to get too technical and nerdy on like the data we've been doing this for 10 years right and we've had billions and billions of conversations with users we spent millions and millions annotating and getting eval sets for what works and Clio is not like ChatGPT in terms of all of our interaction really comes from push so we're a proactive service so we've had recommender systems and behavioral scientists and people working to decide what do I say to you at what point in your journey to help you take the next best action so this massive data moment we've got this massive kind of product advantage and it's compounded over time and that just really helps us build a world-class product so you've got that and then you combine it with all the financial products we've built and successfully scaled so we don't just give advice but we take action we can help you get cards debit credit cards buy now pay later savings wealth management products like the suite is there now so we can monetize success on anyone that's come in which if you are starting from scratch you're a little yc startup it's a much harder thing to do and get to real economics pretty quickly There's a contradiction I want to explore because you come across as pretty laid back.

10:04And yeah, I imagine you're not to build such a successful business. And you sort of talk about how it's kind of easy now. But then, you know, pace of execution, I'm sure is still super important to you. I know you've talked about sort of clawed code and how AI is helping you and probably your organization. But like, how are you thinking about speed of execution as a CEO now? My kind of default pace is pretty fast. I talk fast. I move fast. I get everything done pretty fast. I like being intense and moving fast. It's kind of all of my leadership team, a shipping code. And it's not just shipping code to like our production app.

10:42It's shipping code to make the organization work really effectively. When you have 550 people globally, you have information, just all these different places, Granola notes, Notion, email, Slack, mode dashboards everywhere. work and being able to pull that all together to visualize that to automate to make everything run really smoothly i find the like building the os of the company today is like so grassifying and so interesting so i don't have to have all these like individual meetings where i gain context and have pre-reads and it's slow we can now have agent-to-agent conversations we're exposing all the data in really interesting and unique ways and then we're building agents and tools to be able to interact and to do stuff with them running a business right from the fpna are you hitting management cases down to the very individual engineer shipping you can go all the way down the metric stack to the execution stack you can have it all instrumented and you know what's on track where it's going off track you create visibility on your business these days so i think the companies that go exponential are going to be the ones that take full advantage of this and get full on it so if you're not 24 7 in Claude Code you don't spend 30k a month like I do on Claude Code you're probably going to get left behind it's great for me because I'm like native to it but I think it's gonna be a real challenge for these legacy businesses you know imagine you're running BT or something how hard it would be to change that organization and make it AI first but yeah gonna be a big divergence I think in output in these companies yeah that insane that you're spending 30k a month on claw code but i love it what do you think your business would look like today if you had not been using ai as power users internally you know yourself you talked about your senior management over the last 12 18 months have you got any grasp of that delta it's only got really good since opus 4.6 so opus 4.6 was like november december time and the clawed CLI it genuinely maybe it's 4.5 but it was like genuinely there was this kind of like aha moment in coding where it's like oh this actually works now and this really works so it went from being this kind of pair programmer thing which you'd sit and you'd kind of work with it and you'd still have to be a software engineer essentially to this thing where it's like oh it can actually do tasks end-to-end and if I chain and I do recursion it can do really meaningful like long-term tasks so it's probably only the six months we've seen this acceleration i've definitely seen the acceleration of my token spend and all the companies token spend but it just means we are shipping a ton these days like way more than we ever have yeah we've had the kind of the cultural adaptation to it as well because you know we've got 170 software engineers not all 170 of those people jumped on ai and people wanted to handwrite code for you know months longer than they should have so it's taken us time to be able to get all those 170 to be fully ai native like all the tooling that we have uh clio everything is you know mcp'd and got all the right kind of platforms for it but that was a bit of a cultural shock and the people that aren't and haven't been using it they're the people that we've had to be exiting from the business now so like there's a real productivity gap between the people that have gone full into ai and the people that are still hand reviewing code handwriting code and i think you're gonna have you know in like a couple of years there'll be like a marketing tagline we still write our code by hand there'll be like the bespoke software agency still hand coded because it's just changed so much and if you think about the output of these companies is software it's the thing that really does matter and it's the thing that really does drive gdp growth and i've got so many follow-up questions but one of them was around like token spending.

14:32You obviously mentioned some of your own token spending. How do you encourage adoption and use of AI whilst also keeping a control on sort of excessive use or maybe even personal use and things like that? We have a budget of two grand per engineer and then it's like a grand per everyone else in the company and leadership can do whatever they want. I can't certainly. but the the business that's really interesting though bonnie even just having that policy is ahead of where most people are because what i think i've seen from speaking to founders is that they have employees that are desperate to try and use ai tools they hit the free tier or the token limit or they need to upgrade the package but they haven't quite yet validated that this thing that they're playing with is going to deliver the outcome they want they've got a choice to make they either have to expense it without knowing if it's going to deliver results or they pay for it themselves and then if it works they then go and expense it but there's kind of these like structural barriers to adoption but it sounds like you've solved that by kind of giving everyone a play allowance and then from there they validate and then if it works then you can scale it up yeah i definitely think there's a company to be dealt here like token economics which is like the middle layer where you know it takes all of your problems and then it kind of looks through what were you doing was it useful we're using the right model parameters we're using like too much of an expensive model could you use other things how could you optimize all these generally as you optimize a sequel query probably don't actually but as you optimize your code there's ways of profiling it and i think there's a similar thing to be built now with tokens we're trying to build internally i think it's a company to be built we look at people i also think particularly for non-engineering teams you know for the for the sales and growth teams that are experimenting with 100 higgs field for ai influencer creator and stuff like that and people are learning how to use these tools it's not as simple as just typing something in i don't know if you've ever played with higgs field but it's really complex and you like an hour's youtube tutorial and you're still not using 90 % of the features.

16:44So people kind of play and then hit the barrier and then it's not really like proven that it's going to deliver the value yet. But yeah, it is a whole business problem in its own right. Understanding where the usage is being spent, the productivity of that usage and the translation from that tool through the rest of the business and things like that. Yeah, there's a big bit of FOMO in startups and the best companies are spending a lot on tokens and here are other people doing 10k budgets like it's kind of becomes this arm race and you're like shit i don't want to get left behind why is my budget 2k why is it not 10k do you know what i mean so like the best startups are pretty well capitalized and they're being pretty just all in on this which means that some of it is probably excessive and not that useful and not optimized i think there's a rationalization over time with the business we talked about but the next year or to token spend is just gonna i would love to be an early i know a seed investor in anthropic i'm very jealous of his million dollar seed investment that's 100x already but it's gonna be a pretty wild couple years any favorite tools other than claude we use metabue the clio i'm an angel investor but it allows you to look at all of your talent all your interviews across the business so it records it like granola notes and then it kind of lets you compare to the actual performance in three six months time of those people and correlates what is actually happening in your interview process versus reality so it allows you to pinpoint oh these people are like way too lean and it just makes everything like way more efficient having these notes and pre-reads all generated for itself i'm very bullish on that another one is stacks.ai which is helping us like close on a book within a day versus 10 days you've done management accounts before and then you've got to have all these like people analyzing all the transactions and categorizing it stacks just helps you get to management account close and just automate like your entire financial stack and it's like you need two less people get the data in a day versus 10 days there's loads of these companies being built at the moment which i'm super super bullish on and you don't have to build everything yourself you should still be buying sas software it's still a good thing to do but these ai native ones are hyper useful for companies that are well capitalized and that are doing really well i think founders and management feel it's fine to give big budgets and to spend on lots of sass i think it's the sort of middle of the road companies or the ones who are earlier on in their journey and still being super frugal where they're perhaps making a false economy of kind of restricting token spend and saying let's build this ourselves let's not buy which perhaps people have to just psychologically get over that ramp yeah it sounds so british it's like a civil search civil service kind of view of the world i know we'll go home we should be optimizing for success right not optimizing to avoid failure the people are really taking risk and lent into the technological waves they've been the ones that win so yeah what would you advise younger founders things that you've perhaps learned on your journey people often get caught up on improving the story and the pitch deck and they're like oh if i just tweak the way that i'm saying it if i just make the pitch a little bit more concise a little bit punchy and i'll change the narrative in this way and that way and then the vcs are going to give me money and then they're all going to come clamoring at my door i'm really sorry to say sometimes it can work like that to be fair but like the reality is you've got to build and if you have not built a great product just goddamn build just don't talk to investors don't talk to vcs play hard to get if anything tell them you're shipping tell them you don't have the headspace for someone of such low iq honestly that is what gets vcs going do the guy that just raised like a four billion valuation the deep mind founder that just came out raised a billion he was pitching tier one fund and he said to one of the partners there after like five minutes i just don't i want to give any headspace to venture capitalists sorry i need it for more important things can you talk to my chief of staff he walks out the room puts in as chief of staff uh shocker that tier one fund offered a term sheet within like 10 minutes got rejected uh anyway just fucking build just build a great product don't care about investors play hard to get if anything and get numbers build something great and honestly if you put numbers on the board you build a great product it ends up working out for you sometimes there's macro cycles yeah but eventually if the numbers are on the board you're going to get paid so just put numbers on the board so the first final question is our future unicorn prediction so yeah if there was an early stage company that you thought had a good chance of going all the way who would they be i've got four is that right can i do four eloquent.ai we're using it clear so there's lots of these kind of agents for cs that automating thing the difference here is that they use computer use so they can watch your cs agents do a task it learns from that and automates it it is automated like 30 of our most gnarly cs tasks where you had to like click around move a load of stuff around which working in production it's working at scale amazing founder i think that's going to be that's that's already going huge jack and jill eloquent ai eloquent.ai jack and jill it is an ai agent for kind of recruiting.

22:11So you have an AI agent that helps you with your job search. And then you've got one for finding talent as well. And it matches the marketplace. One more reasonable, they just raised 8 million for kind of pre-seed. The founders are truly exceptional. One of them was a professor of machine learning at Cambridge, and they're building super intelligence for coding. So I think those three are all going to be multi-billion, yeah, hopefully trillion dollar companies in the future and you said you might have a fourth clove clove is back to my excel they are crushing but it's in my space so i've got you know i know a lot about it and thought a lot about space but it's going after the ultra high net worth so clio's have kind of mass market mass market affluent they're building like the personal wealth advisor for people with a million 10 million 100 million in capital and the difference is they're using humans but and a combination of ai So the thesis is, if you've got 40 millions in the bank, you're probably going to want to talk to a human, but you're going to probably want the intelligence of AI.

23:12So it's combined with the two best things. And I think they're going to crash. OK, and then our final question, Barney, is our dinner party guest game. So if you could have dinner with any three people, who would they be? I would love to go back to a credible leader like Obama. I think you could learn a huge amount from him. Again, on the politics one, it'd be great to just bring back Churchill, just talk about what was going on there. I think that'd be an epic one. and then maybe you bring Alan Turing you bring him back and you would talk about AI and what's happening today and get his take on it because I bet he would have the most kind of interesting and insightful things to say if you told him about the future he'd probably like build upon it and actually come up with a new revelation even being 100 plus years gone so maybe my three bit of a weird eclectic mix of people but I think we'd get on I think it'd be a good conversation awesome thanks so much for sharing this they are all people that have been mentioned previously as you can imagine because they're pretty like go-to names awesome barney thank you so much for coming on it's obviously great to have you on with what you've achieved cleo is just a rocket ship now you you went to the long-term plan and it's great to see and obviously it's now available in the uk so anyone listening can go and download it and and give it a go i've got it it's really amazing how easy it is to connect all your bank accounts and get such interesting insights so yeah it's been great to hear how you actually have gone about building it and some of the insights so thanks so much yeah well thanks for having me guys it's been a pleasure and i'll speak to you soon that's it for this week thanks very much for listening to stay up to date with the latest episodes please follow or subscribe on your favorite podcast platform we also have a newsletter called reading unicorns which is another great way to get every episode direct to your inbox and we'll see you on the next episode