Global tax compliance with an AI-native solution by Sphere with its CEO and CFO, Nicholas Rudder (USA)

Speaker A: Foreign. Voice of fintech.

Speaker B: Welcome to Voice of Fintech, a podcast mapping out the Swiss and global fintech scene. Connecting fintech enthusiasts with startups, incubators, accelerators, business angels and VCs and incumbents interested in partnerships. Voice of Fintech will help you navigate the fintech ecosystem. Here you can listen to the startup founder stories, what investors and incumbents are looking for when dealing with startups, and find out more about resources provided by incubators and accelerators. My name is Rudy Falad and I'll be hosting this podcast. Hello and welcome to voice of InTech. Today we're going to talk to Nick and we're going to talk about ainative tax compliance solutions. So that's a mouthful. So we're going to break it down into pieces, make it clear for everyone. Nick is from Australia, but he's based in California. As you should be if you are in the startup world. Right. Um, I'm very curious to find out what that really means. He's also funded by Andreessen Horowitz. So this is one of the top class investments that you can think about in this space. Right. But let's find out more and judge for yourselves. Nick, how are you today?

Speaker A: Great. Sunny day in California, can't complain.

Speaker B: Wonderful. But I always say to this, it sounds like you want to complain, but you cannot. Somebody is preventing you from that. Anyway, that's all good. That's all good. So I get it, we envy you, uh, if we are based in rainy towns like I am. But in any case, welcome Nick. So let's talk about your solution soon enough. But before we even get to this, can you tell us, how did you get to do what you do today? How did you become a founder in a startup? In a fintech?

Speaker A: Yeah, So I think my journey started in startups at university. So I was in Sydney, uh, I went to the University of Sydney. I did my own startup at university. It was a platform that helped link local businesses to charities. It did okay. We won some incubator competitions. Didn't really go anywhere, but it gave me that first itch to build something. I then went into finance. I was at PwC and Macquarie bank, which is a big Australian investment bank. And I know your background's in, in IBD as well, but yeah, I found that part of the world like advisory is you scratch the surface with businesses and you don't quite feel the heat of competition building features that lots of people use. And so I wanted to go back to starting my own business. When I did an MBA in London. And during that mba, I started my first company, which was Scholarsight. It was an edtech platform of all things, if you would believe it. Terrible industry, EdTech. I wouldn't, not sure if I would recommend it, but that idea spawned actually out of, uh, somewhat of a lackluster experience I had with the mba. And it was a platform that helped people upskill in technical subjects. That's what got into Y Combinator. That's what brought me to San Francisco. And that business did okay for a bit, but frankly it just wasn't going to scale, scale into a massive business. And we can go into the reasons why, but it did have a lot of tax issues. And so that is what prompted me eventually to go into sphere and what we are today. I combine this prior pain that I had in the last business with my finance experience at PwC Macquarie and yeah, that's what sort of brought us full circle to where we are now.

Speaker B: I see. So that's great. So it sounds like you've seen a lot of exciting stuff, but you felt like you want to go deeper, right? You want to have a more tangible experience, you want to build things, grow things. Right. In mature businesses. You, you, I don't want to say a cog in a machine or something like this, but yeah, you're one of many. Right. Great that you were able to do this. And you are serial entrepreneur by now. So you alluded to it a little bit. As you've seen in one of your businesses, many tax issues. I know your business is global, right. So that must be extra challenging. So let's talk about it in a minute. But how did you actually get going? You said, okay, you've seen these issues and then what happened?

Speaker A: Yeah, so I'd seen these issues in the marketplace business that we had this edtech marketplace. And the thing is that marketplaces have these issues with tax quite acutely because you have to cover tax on transactions, on all the transactions in your marketplace, not just your revenue take rate. So the stakes are very high for a marketplace. If you get tax wrong, it can have a huge impact, uh, on your bottom line. And so that's what sort of gave me that first idea. And I guess when the first business failed that edtech marketplace, I wanted to go back to those finance roots, work on this problem I'd faced in the last business. And so I focused very much on selling to CFOs and people in the finance realm. And sure enough, as I talked to more and more folks, these finance leads at tech companies here in sf like it was the same thing, kept cropping up, which was tax. And it was a lot of pattern matching. And then eventually like that's what really got me to pull the trigger, uh, on this idea. I, I will say that when I did this business at the beginning I had no technical co founder, uh, so I was, I basically had to sell this product before building it to be sure that this was the right direction. And we did, we, I sold five contracts off a Figma prototype before, before we built anything on what Sphere is today. And that's what gave me conviction to go forward.

Speaker B: So you call your latest venture Sphere. It has to do with tax compliance solutions for marketplaces. Can you give us a bit of an example and paint a picture, say that people know about ebay, people know about Apple Books or something like this, right? And they're selling their products there, it's being shipped to different places. Maybe it's a physical product, maybe it's a digital one. So you need to collect as I guess VAT or sales tax, uh, because of your jurisdiction, is that it or is there anything else?

Speaker A: Let me give you the overview. So I guess Sphere, what we are and what we call ourselves is an AI powered cross border compliance platform. And we focus right now on one particular type of compliance which is indirect tax, which is the tax on top of a transaction. So sales tax, vat, gst. So just to make this real, like when you're a company like Lovable or Replit or 11 labs, uh, you sell around the world and you as the company, 11 labs or lovable, have to collect tax on your transactions based on where that customer is. And so the way to m flip it and give you the idea on the customer side of the equation. If I'm going to buy a subscription on Lovable and I go to checkout, there's a line item underneath the subtotal which is tax. And what's happening is that tax is being calculated by pinging Sphere's tax engine, AI native tax engine. To figure out, okay, based on the product that's being sold at this checkout session and based on where that customer is right now, what is the right tax? And firstly, is it taxable or not? And what is the right rate if it's taxable? I will also say, like we don't just do this for marketplaces. This sort of tax is applicable to every company, uh, under the sun selling anything, whether it's software, whether it's services, whether it's physical goods. And so it's a, it's an absolutely massive market. I did allude at the beginning to of that response that would you say we do indirect tax? Now the way we see it is there's actually lots of different types of compliance that a business needs to abide by when they sell internationally. Indirect tax is a big one, but there are also other things like tariffs if you're a physical goods provider, uh, withholding tax, input tax. And we're really looking to be the revenue based compliance platform. So similar to what deal and Rippling have done for global payroll compliance, we're doing for the compliance of selling that revenue based compliance element.

Speaker B: I see, I see. All right, so let me dive into something that is on um, the on minds of people every day these days. You cannot sell anything if you don't say it's AI, uh, powered. Right. So you say you are AI native. So what does that mean? What kind of AI are we talking about? Is it really AI or is it gen AI or traditional AI or it's just rules?

Speaker A: Yeah. So this sort of feeds into one of the key differentiators of our uh, platform, the AI native tax engine, basically. So tax engines have been around for a long time. There are big incumbents in this space, companies like Avalara, Vertex, and basically those tax engines, uh, yeah, they're nothing new, but they're built on very manual processes. Because really what a tax engine is a bunch of if else statements to say for this product in this jurisdiction, this is whether it should be taxed or not, and this is what the rate should be. Right. And to get all that matrix of if else rules, they have these teams of thousands of tax researchers that go and review the tax law in every jurisdiction. And remember, in countries like the US this changes down to the locality level, not just at the state level. So incredibly complex, a huge surface area of law you've got to review. And so you've got to basically review that law just to generate the determinations. And then you've got to continuously monitor that law to keep it up to date. Right. And we're the only vendor in the market that was born post the AI boom. And for the first time in history we have this technology that can, that can automate 95% of that manual tax research process. And so what our system does tram, it's called the tax review and assessment model. It ingests, codifies and monitors trade law from around the world. Right now it does indirect tax law, but it's very quickly expanding into other areas so that we can provide the right tax treatment to Any product, regardless of whether you sell it with a much, much smaller tax team and do it at a far quicker rate.

Speaker B: So it's not just the rules engine, but you actually automate the research behind the scenes. Right?

Speaker A: So basically the research that dictates the rules, that's what we're automating. You still have to have a rules engine because when you do the tax determination on a transaction in real time, you don't want any AI in that bit because that would be a disaster. You don't want any risk of hallucination. You still need the deterministic rules. But how you figure out what the rules are, that's where tram comes in and that's what is a step change function in being able to scale globally and monitor those rules globally.

Speaker B: So the rules are, uh, not probabilistic. Right. So on top of that you have basically generated AI agents kind of thing.

Speaker A: Right? So we have AI that will basically do the work of figuring out like for a certain product category, let's say SaaS, and all the different characteristics of SaaS products, it will figure out what the tax treatment would be in every jurisdiction globally, and that it does that as a first pass. And our, uh, accuracy on the first pass is very high. We still have tax experts in the loop that review the outputs of the model. We do that for two reasons. Firstly, because you need to have guardrails to understand, figure out is it 100% correct and validate that. But secondly, you want the feedback that those experts provide because we use it to fine tune the model further to get that first pass accuracy higher and higher. So over time, maybe that expert in the loop starts to become less and less of an important step as the first shot accuracy climbs closer to 100%.

Speaker B: So it's basically AI augmented compliance professional and it's about text. So it is a large language model, I assume, right?

Speaker A: Yes, it is. Like at the end of the day, trade law is available. All the trade law for every region is available online. It's in hard to find places, it's in unstructured formats, it's sometimes in different languages. And finding the rules and the patterns in that is exactly what AI is extremely good at. So yeah, I would say it's a core piece of our, uh, infrastructure. It is the thing that dictates how all of our products work, because all of our products are compliance products and the rules are an essential part of that. That's what it means to be AI native in this space. It does not. What AI native? What would not Be AI native in what most of our vendors, our uh, competitors do is you might have these workflows that you can sprinkle AI on to make incremental efficiency improvements. But you're not getting a step change in efficiency and a step change in output if it's not at the core of the business.

Speaker B: I see. All right, so coming back to your clients marketplaces, right, you say at the checkout, you choose the rate and depending on the customer, et cetera, et cetera. So how do you deal with integration? So somebody else does it for you? Or is there an API? Is there a role for AI agents? Or this is just coding and that's it.

Speaker A: So there's two sort of main sets of integrations that happen in our business. Firstly is like we need to plug into our uh, clients billing systems. So they might be using Stripe, they might be using NetSuite, they might be using a custom billing system. And we need to integrate with those systems one, to ingest transaction data because we need that to be able to monitor their exposure as well as file returns for them. And two is so that we can push tax live at uh, checkout or at the point of transaction. And so those uh, integrations are simple pre built connectors. There's no AI, there's no need for AI in that. Maybe you could use AI to increase the speed at which you build them. And there's a lot of internal AI use. I would say at Sphere we're a pretty lean team and I would say some of our engineers are doing the work of what maybe 10, 15 engineers would do at a traditional company. So that's one thing. Then uh, the other part, main integration that we have at ah, Sphere is, and this is the second big differentiator that we have aside from the AI tax engine is we spent the last two years building direct integrations into over 100 tax authorities around the world so that we can properly automate all of the compliance workflows in that region so that we can send data straight to the tax authority for registrations, for filings. And then in that type of integration sometimes the tax authority has an API. So that's great. And you can build out, you can build out that API, you can maintain it and that's straight through processing. That's awesome. But lots of tax authorities aren't that advanced and they might not have an API. So there you have to build smart agents to go into the tax authority portals and fill out forms. And that is where you do use agentic AI and where we use it and there's a lot of investment on our end going into that.

Speaker B: Oh, uh, wonderful. But you talk about obviously you're present in many countries and within the US there are different states and communities have different tax rates and things like this. But does it work also cross border? Because if you are exporting then ideally you don't even charge the vat. The customer is responsible. Right. Otherwise it's very difficult for the customer to reclaim the original VAT than to pay the one at home. So the, and in some countries there are deals like between Amazon and that country that they charge automatically the correctly for the destination. Right. So does it work cross border? Because that's another level of complexity. Right?

Speaker A: Yeah. What you're referring to is. Yeah, the reverse charge where basically you push the tax obligation onto the customer and they self assess the VAT. But that's only true for B2B transactions. So B2C transactions, a uh, US company needs to charge VAT on all B2C transactions. And the threshold in many of those EU countries is zero. So on the first EU transaction they'll need to start charging VAT. So if you look at a lot of our customers, the lovables, the replets, the 11 labs, they have millions of B2C transactions. That's honestly where the larger tax complexities lie is when there's high transaction volume. So marketplaces, B2C vendors, and that is where we shine. So the two differentiators I mentioned, the AI native tax engine, the local rails in the tax authorities around the world, what that allows us to do is to provide a very strong global cross border product. Because a lovable, a replit, they are going to need to collect, register, collect, remit and file taxes in not just these US states but, but in many international countries that charge VAT and gst.

Speaker B: All right, okay, understood. So we talked about AI ah native but then you alluded to that makes you different from other solutions. Uh, what else? What makes you special versus your competitors.

Speaker A: Yeah, so uh, I think we've talked about the AI native aspect on the, on the product side which is the tax engine. We've talked about the rails. That's it. Those two things are what allows us to win with global companies. And there's a lot of uh, competitors who claim to be global but they're very US centric. They do well on the US side but they fall short a bit on the international. In terms of what else makes us AI native though, uh, we, it's all well and good. Like I think the most important thing is being AI native on that product facing side. But you also need to be AI native on the internal side to create maximum operating leverage for yourself. So you're seeing a lot of these businesses at the moment who are teams of 10, 20 people reaching 100 million ARR very quickly. And the reason they're doing that is because they're effectively leveraging AI internally to get maximum efficiency out of their engineers, maximum efficiency out of their growth team. We are a very lean team. A lot of people think that we are much bigger than we actually are. We're very lean and we're able to do that because we have built the appropriate systems and harnesses to get agents to do a lot of the work for us. Now I'm not saying we fully, this has taken a lot of time to build. Also we operate in a space where there's zero margin for error. So you do need to be careful on what you're using the AI for and that you're guarding against what they call AI slot. But yeah, we've managed to get a lot of operating leverage out of the internal AI systems we've built.

Speaker B: Okay, all right, great stuff. Now let's get real. How do you make money?

Speaker A: Yeah, so we uh, have very much a, uh, multi product strategy. So as I said right now we do indirect tax and there's three ways we make money. So we charge by the region. So a region is anywhere they register and file for taxes. So a US state is a region, a country is a region outside of the US Basically. There's some nuances there, but yeah, and we charge 100 bucks per region per month. That's the list price. So if you're in all the US states, that would be 60 grand. We then charge by the transaction. So we give 50,000 transactions for free and then we charge 5 cents per transaction. Again that's the list price though if there's high volume, we do negotiate on that, then we charge remit. We also have embedded payments on our platform for tax remittance. Like when people file returns, they got to pay the tax authorities and we have embedded payments for that. And we do take a FX margin on those tax payments. So those three revenue streams, I guess you got the regional rate, which is a very SAS classic stream recurring. Then transaction and remittance is very usage based. And so the usage based streams obviously scale with the success of our clients, which is a good business model to have. And that's why we partner with some of these very fast growing companies. But we sort of offer our product At a reasonable price, I would say, compared to the competition. So that's what we currently charge for. But we are launching these adjacent compliance products at the moment. I mentioned input tax, which is the tax on expenses that a customer, so a lovable, for example, will pay charge tax on their transactions to customers, but they also have expenses that they pay tax on. And that tax can be deductible against the output tax, but it's based on the rules of the region. Right. And so again, AI native tax engine understands the rules, can ingest the expense data and figure out what is the actual amount of input tax they can deduct against the output tax or the sales tax. So input tax is something we're launching and that will just be another regional fee. Withholding tax is very important for cross border B2B transactions, again would be another regional fee. And then E invoicing, which is very topical in the EU right now, that would also be a usage base fee. And combining all those things in one platform has really never been done before. Natively. There's been other companies who've tried to do it um, through acquisition, but they lack this centralized data model. And yeah, the way we see it, as I said, it's like Rippling's a good example of doing this, being very effective in this multi product play. But for a different area of compliance, we'll be adopting a similar strategy.

Speaker B: I see. All right, so you already mentioned the uh, clients. Right. So it's great that you have different products versus let's say within one vertical. Right. You said indirect access, different revenue streams, you have different countries, you talked about clients, so let's talk about categories. Right. So who are your target clients or customers?

Speaker A: Yeah, so we've definitely made our name for ourselves in the software space. And if you think about software companies, they sell all over the world. Right. So it was very relevant category for the differentiation that we are uh, showing the market which is like this global platform that can understand rules globally and also transmit data to tax authorities globally. So software is where we got our name, but we are expanding very rapidly into these other areas like physical goods. Usually like if you were one of the uh, traditional vendors, it would take you months if not years to move into these new categories because you've got all the rules change by category. But for us, as I've mentioned, it's a lot faster because we can automate a lot of the research. So yeah, on a category basis that's where we're moving into, is really to cover the universe of products, not Just software to give you a bit of a sense of like other attributes that are really key to our icp uh is we look for series B to pre IPO based companies. We're not focused on like smaller uh, companies. We're looking for the complexities so that's usually at a larger end of town. We also look for the global customer base. That's very important. If you just sell in the US slightly it's still a good value prop. But I, where we shine is international and then the last thing I would also say is high transaction volume. So again that's where there's more complexity. So that's what we look for.

Speaker B: All right, great stuff. Now you also mentioned that you are based in San Francisco. It's a global business. So do you have also offices elsewhere or people work remotely? Uh and I don't want to get you to trip on tax compliance or such a thing but uh, where are you based and are you looking to expand potentially? Is it needed? Maybe not?

Speaker A: Yeah, uh, our hub is in SF right now but we have a huge focus on international companies right now. We obviously have got a lot of US clients but because of the international capabilities we've built we are very attractive to international companies at the moment and there's much less competition internationally. So we're very focused on international businesses and that means that we are expanding our uh, footprint in the EU as a first step. That is something that we're actively doing at the moment. So we are hiring across engineering, sales, gtm, more broadly, tax, uh, in, in the eu. So that's a big focus for us right now. We've also thought about opening a New York office as well just to cover both coasts. But in the immediate term that's where. But yeah, as you said it's a very global focus. We're also later on in the year going to be pushing operations in APAC and latam. I think by beginning of next year we should have a fairly global footprint in terms of operations.

Speaker B: Okay, fair enough. And you said you are fewer or you have a less of a headcount than uh, maybe other people. So how many people are we talking about?

Speaker A: Yeah, so right now we're sub 50 people. So fairly small. But I just think that the days of I see a lot of up heres and people that are maybe a little older than us and, but not that much further ahead and at 3, 400, uh, 200 people, 2, 300 people. And I just think those days are just gone. I don't think you need to have that amount of people in this age of AI and so sure, we'll expand. No doubt about it. We still definitely need really good people, but I'd say we're getting an amazing amount done with a very nimble team and I don't want to lose that, if that makes sense. Obviously, yeah, there'll be demands of the business, but keeping that operating leverage will be key.

Speaker B: All right, I see, I see. All right, now I wanted to follow up on one thing, though. So you started selling, let's say the product before was built. You said you didn't have a technical co founder. Great. But how did you find these first few customers? Right, Yep. Obviously you're a serial founder, so you know about prospecting, you know about networking, you have a reputation, but still, how did you go from 0 to 10, 100, etc.

Speaker A: I will say, like when I started the second, it's not like the first business was wildly successful, so. So I don't think I had that much of a reputation. So I was very.

Speaker B: You got street creds already, so it's fine.

Speaker A: Yeah, maybe a little bit. But the way I went about finding those initial clients was extremely methodical, actually. And basically what I did was I had the inkling of an idea from obviously the problem I faced in the last business. And I also had the lane that I wanted to focus on, which was finance. I think having the lane is so important because if you just keep thrashing in different directions, I don't know, you want to build a. You want to focus on operations as a customer set or and then go to finance as a customer, then to sales as a customer set. You're just. None of your learnings will compound. So I sort of had my lane and I had an inkling of something that I knew was a problem and then I was very methodical about. I treated it as a sales process. So I would reach out to 20 heads of finance here in the Bay Area, reputable SaaS companies, and I would treat those first 20 conversations as discovery. I would basically ask them some pretty pointed questions that have done very well for me in the past, where you ask things like what are the projects that you're allocating budget to this year? And that is immediately a question that gets to the heart of what are you willing to part cash with? And it gives you a good proxy for product market fit, I would say. And you treat those 20 conversations as pattern matching. People say a lot of different things. And the thing that you. I did hear come up a lot, which was linked to my prior experience in the marketplace was tax compliance and that was something that they were looking to invest in. And so then the next 20 conversations I would come up with a FIGMA prototype. So this was a rough FIGMA prototype. Uh, it wasn't too rough, it was pretty high fidelity, but it wasn't perfect. And the idea of the next 20 conversations was to go to more heads of finance and put something in front of them and iterate importantly, it's about iteration. You're not selling yet, you're just trying to get an idea of what would be useful to them. And then by the end of those 20 conversations you're in a place where you have a hypothesis on something that could be valuable. And then you treat, then you go to the last 20 conversations and that's when you are trying to sell the prototype on FIGMA and get what's called like Lois, letters of intent. And letters of intent are non binding but they're still good signal that someone is willing to be serious about what you've put in front of them. And uh, by the end of those last 20, so like the 40 to 60 conversations I had five letters of intent. And that gave me good signal that this was something that people wanted. And the good thing about all that process, the three stages is that because I was always going to heads of finance, when I got to that last 20 conversations, I could go back to the first 20 and re engage them. Um, and again you get this compounding of learning. Whereas if you start fresh every time, as I said, it just doesn't work.

Speaker B: Wonderful. Right. This is what I always say to people, don't ask your friends and family if this is a good idea. Of course they'll tell you yes.

Speaker A: Right, yeah. And I was very purposeful also to not sell to Y Combinator companies. There's definitely, it's a good thing where they help YC companies, help other YC companies out. But sometimes that's not good signal because you want to. What I was very purposeful on is selling to companies that I had no prior engagement with to see if this was, yeah, I guess something that was valuable to them.

Speaker B: I got it. Perfect. Okay. I know that you raised some good chunk of money from Andreessen Horowitz. So can you tell us a little bit about that and uh, how does that fit into your plans versus where you are today, what you want to achieve this year and, and later?

Speaker A: Yeah, so look, I think, yeah, November last year we raised 21 million from Andreessen Horowitz and Y Combinator and 20 VC and Felicis, a few others. The idea of why we raised that money is we have a very big ambition and a very big vision which is to become this revenue based compliance platform. And it feeds into this vision and mission that we have of making the world 1 market. Because we feel that if we can collapse uh, the transaction cost that is tax compliance, then that opens up trade corridors and you make selling internationally as easy as selling locally. And uh, that's a vision that like it's a big one and it's not something that's like a sort of side hustle or like a. If it works, it's really going to work. And to do that we need to build not just what we're doing now which is output tax, but we need to do input tax, we need to do E invoicing, we need to do withholding, we need to do tariffs. Each of these are like different products that are going to require a decent, like a sort of lot of investment. On the engineering side, yes, AI can help with a lot of that. But it's, you still need the boots on ground and you still need not just the engineering but the GTM to support that, the CS to support that. You need the global, you need the global presence and yeah, that takes money and that's why we raised that money.

Speaker B: We're also seeing also people, not just robots, right?

Speaker A: We will be hiring people. Yes. I think we're still just like we are with tram. I think like we are still in an assistive stage of AI. You notice DRAM doesn't replace tax researchers completely. There's still experts in the loop. Just like coding agents don't replace engineers just yet, they're still assistive. And yeah, I think maybe that changes over time and it will, but we're not there yet so we still need people.

Speaker B: Like self driving in San Francisco.

Speaker A: Exactly, exactly. Yeah. You start small and then maybe it takes over more and more over time. But yeah, so right now we need people. I think that the opportunity is absolutely enormous. There are huge regulatory tailwinds that are also spurring a lot of demand for what we have. Basically tax authorities around the world are really clamping down on this type of compliance, this revenue based compliance. They want real time data feeds of transactions that are happening cross border and that positions us really well. And I think if you even think you extrapolate this a bit into the future, like in a world where AI continues to replace jobs and you know, when the biggest source of revenue for the government is income tax you know, it's 50% of federal receipts in the U.S. so if that starts getting a dent hit in it, uh, where people start losing their jobs and there's less income tax for the government, I can tell you right now that they'll find other vehicles to make up that downfall. And what do you think is the first thing they'll look at to tax the companies that are creating these AI systems? It's going to be indirect tax. So I think we're in an extremely interesting position, not just in the short medium term with these regulatory reforms that are happening right now, but also in the longer term where. Where maybe AI starts shifting the revenue mix for governments.

Speaker B: All right, understood. So great opportunities ahead. You are well funded. There's still jobs to do by both agents and humans, so that's great.

Speaker A: Yes.

Speaker B: Now, where can interested parties find you? What's the easiest way to reach out? And who would you like to hear from most?

Speaker A: Yeah, uh, so look, you can find me on LinkedIn. Nicholas Rada. Ah, I'm also on Twitter, nrudder. Uh, if you're ever an SF as well, would love to hear from you. I think the people that I'm really interested in hearing from is obviously if you're a business and you need help on the tax compliance side, we'd love to chat, but we also are very hungry to meet engineers. Uh, we're very hungry to meet salespeople and GTM folks. I think we're on a. As I said, we are aggressively hiring both in SF and in the eu. Would love to hear from you, please.

Speaker B: Dm.

Speaker A: Ah, me and we can have a chat.

Speaker B: All right, wonderful. Thank you so much, Nick, and good luck to you and Sphere. Thank you for listening to Voice of Fintech podcast. If you haven't already, check out also voiceofintech.com where you will find all the episodes and additional resources related to the podcast. You can also subscribe to Voice of FinTech on Apple Podcasts, Spotify, Google, or any other podcast app that you like. If you have any suggestions on the topics or guests or how to make this podcast better for you, please email us@infoooiceofintech.com Happy to hear from you. Thank you.