EP #344 - Tim Beck: Using AI to Automate ERP Processes

I think it's a choice. If you want to do entrepreneurship, if you want to build something, if you then also want to scale something, it shouldn't be for the money that you can make right away. Because then, in my opinion, you're doing it wrong, because the more money you invest in it, the more chance it has to actually grow. Welcome to the Swisspreneur Show, a podcast about startup stories and learnings from experience entrepreneurs. Here's your host, Sullivan. Tim, a very well-welcome to the Swisspreneur Show. It's a pleasure to have you here today. Thank you for having me. You're the co-founder at BLP Digital and ERP Automation Solution. And you actually studied at the Technical University in Germany in Aachen. And I was wondering, was entrepreneurship already on your mind back then? Well, it's always been part of my life, actually, because my parents are entrepreneurs. So, entrepreneurship has been a daily topic, I guess. My team is always joking when they could talk about soccer, I had to talk about ERP systems at home. So, kind of yes. So, you grew up in an entrepreneurial family, and you have entrepreneurship in your DNA to a certain degree. Can you talk a bit more about what your parents did? Because that's very relevant to what you are doing today to a certain degree. Yes. So, in the 90s, they started an enterprise resource planning software company in short ERP. And they're still doing it. So, the company is around 30 years old now. Wow. And what ERP is, is every company needs to manage different processes from purchasing procurement through production, sales, managing all the activities and data that is within those processes. And the ERP system is basically that the most common one is SAP, for instance. Right. I think we all know it for the better or the worse, to use it or to have heard about it. Having an ERP business as a family business, was it ever an option or maybe even some pressure from your parents to say, "Hey, team, we want you to take over our family business one day." No, never enforced or not even encouraged. Our parents always encouraged us to, as my father said, do something right. He started business. He said, "You cannot study business. You can do anything else." So, engineering it was. And after engineering, I went to strategy consulting. Only after that, when coming in touch with machine learning, we went back to ERP because we really knew about it. But to come back to your question, no pressure. Not at all. However, you then sort of stick to the family business in a very different way, not only in the ERP connection, but you actually co-founded BLP digital together with your brother in 2019. How is it to start a company with your brother? Maybe you can talk a bit about the pros, but also the cons. Sure. So, I mean, the pros are definitely, you know each other for so long. There's a trust base that I think you can't learn or it's really, really difficult to build that up with a person that you haven't known for 30 years. That's definitely the pros. Also, you know about your strengths, you know about your weaknesses, you know about your reaction. If somebody is tense and you've realized that for so long that you just feel when it's not the right moment to bring something up or when you actually have a fight, you don't need to apologize. You just handshake the day after and things are forgotten. So, that's definitely the pros. In our case, also a pro is that he's more focused in all the tech part. I was more focused in the business parts where there was a lot of synergy there. The cons maybe is that if you found something together and it's really a big part of your life, the rest of your life just gets a little bit in the background. Sure. If that makes sense. So, usually you will have your brothers in sort of independent advisor on your job situation but now you're working at the same job basically. Yeah, or normally you just, when you see your brother, you talk about lots of other things than work. And suddenly it's all about the business. Right. But yeah, it's a small price to pay. That makes sense. We started the company with your brother, but then later on in the journey, you also brought on two additional late co founders Sabrina and Torre. When does it actually make sense to bring someone in as a late co founder versus saying, hey, you're part of the management team. We give you a very specific role within the management team, but not the co founding role. So in our case, we were a really technical company. So when we started five years ago, because of our parents, because of what they were doing, I think we will come to the product later. We had a lot of customers from the beginning and we knew what we needed to do. So we didn't really need anyone back then to go out in the market to search for customers to search for the content to create a product. We had that. So our team for the first two and a half, three years was really only engineers and me. There were like ten people coding and me doing everything else and then it made sense once we actually wanted to enter the market like beyond what we had with a ready product, then it made sense to onboard them and to bring them in as co founders in our case. And I believe a lot in sharing ownership. And I feel that if you want somebody to take over ownership, the best case, or the best thing you can do is give them ownership like real ownership. Because if you have stakes in the game, you feel it differently. You behave differently. You decide things differently. Absolutely. And that's where co founders are having more skin in the game than a pure management position only from your perspective. Definitely. And in our case, we really want that everybody has a small ownership. So company shares for us is a really important topic. You have to written nice in your email signature. I think I saw it with Sabrina's email signature. How I scanned the front ETH in the back. So you were born at ETH basically with the research. So what makes your ETH spin of different compared to other ETH startups? Well, that's an interesting one. So I think what makes us really special is that while my brother's research is coming out of ETH and the machine learning research is making us an ETH spin off. Really from the beginning, we had this strong background in earpiece systems like in our parents company. So we really knew the industry problem. We really knew the processes we were going to solve. We had the connection to companies that we were working with. And I think to have that as a young company, as a tech startup, as a spin off from a technical university, that's very rare. That's a huge bonus. And then to find qualified people like Tori and Sabrina, who then can help to actually once there is a product, bring that to the market, leverage network and Switzerland is small. So networks everything. That makes us as BLP different from many other spin off. So it really is then this combination between the ETH and the highest key. Yes. And the family back right by what's next. Let's talk about what we actually do. And I like to start with the biggest problems or pain points that you solve. I think in your case, you have two big challenges that you tackle. Can you talk a bit more about, you know, sort of the high level where the world or your customers are shifting in terms of problems and challenges and how you solve them? Sure. So from a demographic perspective, a huge thing is that there's a lot of people retiring in the next years. Like the shift started in 2019, the first year that more people retired than new people entered the workforce. And somehow we need to bridge the gap from less people, same amount of work or even we want to grow the economy so more work. That's one problem from a big perspective that we're trying to solve. The other one is there's a lot of disruption in supply chains since COVID and the war in Ukraine. And that's also something that is in our environment that is that we're dealing with daily. So coming back to what we actually do, that this is combined. We automate ERP process. processes based on machine learning, what sounds complicated is actually quite simple. So lots of processes involve documents being exchanged between companies. Let's say you order something, then your supplier receives your order and needs to register a sales order in their ERP system, then they send you a document that's an order confirmation. You on the other hand, then have to check this order confirmation if what they confirm you is what you actually ordered. And here comes in the supply chain disruptions that I mentioned earlier. Let's say your supplier doesn't have those kind of things at the moment you want it. So they confirm your different delivery date. Or even you order 10 pieces, they confirm you five and then five two weeks later. So you need to update your data in order to manage your production in order to communicate properly to your clients. And where we come in is that this problem has been around for centuries, right, like since ERP exists, that problem exists. But now there's a real paradigm shift in terms of machine learning, being able to actually understand documents or in our case, understand documents and understand ERP system data. Actually do the comparison and solving the whole process and to end where it's possible or connecting you as a person with those documents and highlighting, hey, here you have to check something or not you, but your colleague or whoever is responsible, so really understanding the whole thing, connecting multiple people or fully automating everything in the background. That sounds like a very, very specific but also very real problem that you solve right there. Why is the timing to solve that right right now? Is it mainly technologically driven that it is possible from a technological perspective to solve it now or are there also other reasons why the timing is good right now? Also two things definitely tech, because what they did years ago is they tried to solve those things with templates or rule-based systems. So let's say you get a customer order and you know that this customer is always using the same format to order something. So you try to build a rule-based system or a template that just looks at the top right that there's the customer order and then looks where the table and always has the same structure, etc. That's how it used to be. Now if you have many, many different stakeholders, like suppliers and customers, then there's very many different formats and especially if tables change a lot and have variation, those templates and rule-based systems fail and what we are is kind of a chetchy PT for documents if you will. So those neural networks that we are working on are really capable of just understanding new documents without having ever seen them, understanding the logic and still being able to translate that and compare it against the European. And this new technology abilities, that's what's the cool thing in the market and that's what makes it possible for us to really completely offer differently our service than our competition. Just to give you an insight, we really sell proof of concepts, POCs with real data. So we just tell people, "Hey, our integration is just a day of work. We integrate in your production system. You can test it with real-life data. If you like it, if we keep what we promise, you can have it. You can save money right from tomorrow if not, you don't have to buy it." And with those old technologies, if you imagine, that's not possible at all because you need to build the templates, you need to set up the rules two years later, it doesn't work because everything changed. Like, exaggerating, but kind of that's the case. So you're much, much faster with the implementation, basically. Because there's no setup, right? You just have to integrate to the European so that you can compare the data and then you're done because the neural networks work across all companies. You don't have customizing for one client. It's one big brain that just works perfect. And how do you make money? What is your business model behind this amazing technology? So what we do is we sell per document and the more documents somebody buys from us, the cheaper the price gets. So it's a SaaS model, software as a service. Everything that we have is in there and you just pay for what you consume. But with the difference that you pay upfront, so that we can manage our cash flows. And the more documents you pay upfront, the better your price is per document. And usually in the space that you're active in, right? The ERP space. I heard that there are a lot of, you know, set up fees, implementation costs, et cetera. You seem to have found a different model that works very well for you with comparably low service fees in there. Yes, so we really do not want to optimize for service fees in terms of making money from that because we really try to solve the problem. And if we can integrate something in a day, why should we not do it? So what we really optimize is to everything that has a service component, try to make it as efficient as possible. And for instance, I mentioned integration earlier, one of which we have is an SAP integration. And there we really down to the customer only needing to transport our SAP package, which is kind of the language for install it. We have an eight step manual where you just have to do step by step. You're done after half an hour. And then everything from the customer perspective is set up. And that makes so much sense because who has IT resources nowadays? No one. Exactly. No one. So we'd rather focus on not needing them, enabling them to be fast with us and solving their problems, and then charging for the actual service, like the automation instead of the project. This sounds interesting because of two perspectives. One is the implementation. You don't need additional resources, which could slow down the sales process tremendously. At the same time, it also allows you to charge for the value for the product and you do that with a recurrent revenue. So that makes your company more valuable compared to service income. Yes. And we actually solve problems. I also want to talk about some challenges along the way. And let me focus on the first part, starting out. When you start about with your company, I assume as many founders have to go through, you paid out a low salary, you were living in Zurich, you have to probably high living costs here. So how do you go about these early days of living with small cash flow, paying a low salary compared to you could go to strategy consulting again or have a job in the industry, and you probably make much more money. How was that for you on a very personal level? I think it still is. Because then, in my opinion, you're doing it wrong because the more money you invest in it, the more chance it has to actually grow, right? So you should never optimize for that moment, and you have to be okay with not living the life where you go to restaurants every night, and partying every weekend, spending way too much money in clubs. That days were over then, for sure, but for me it's okay, I really like it because we can decide what we solve. There's no politics in companies like ours, you can just really try to understand a problem, solve the problem, and find the best solution. Instead of knowing the best solution, but having to convince five stakeholders that might not want the best solution, but have other interests. So for me, that's what it's really about, working with great people, being able to solve stuff, and then the paycheck needs to be good enough to survive. Of course, you seem to be really motivated by solving the problem. I think that's remarkable, and I can feel that here in the interview. Another thing I want to talk about when you started out, you first saw, okay, there's a chance in the market, but at one point, you probably have to go out there and validate that your technology actually also works, and that you are solving a problem that companies are willing to pay for. So how did you validate your business idea, basically, and the problem you're solving? So really early in the beginning, we, when we. And we had the idea that this could be something companies need. We went to those first companies, partnering with our parents company and talked to them. This is our idea. Is it really a problem? Then we created products. So first product was the auto confirmation process. We understand the procurement department has problems checking those. Second was okay. What about logistics? Alright, they have problems when they get delivery notes. So let's make that a second problem. Third was finance for all the invoices and stuff. And then sales for incoming requests or incoming orders to generate offers respectively generate sales orders. And then we had this product suite that we understood there was need. And then we really worked closely with them. So we kind of just gave them intermediate products and said, test, tell us what you need to improve. And this has been for that like five years. We have really well working products. They're amazing. And still we get feedback every day, which I believe is super valuable. And we've even implemented it in our software. So we have two buttons where you can tell us. This document could be used for retraining the models because apparently there's something wrong or another one, hey, here a feature could be super helpful for me. In those cases that you have to take decisions or in cases that you need to work with the software and it's not fully automatable just because of the process. And yeah, that's how we still do it. Very close with the client. In the early days when you know, you didn't have the perfectly functioning product yet. Because I assume with the ERP companies, basically companies who use an ERP, these are rather bigger companies compared to a startup size. Was it difficult to get them on board for validating your idea and saying, hey, we have something. It might not be perfect yet, but we're on to something. Was it difficult to convince them to work with you and give you feedback without having to perfect solution in place yet? For sure. Definitely. How do you do that? How do you do risk that big thing that might not be perfect yet from their perspective? Yeah. So one thing is we were really lucky that we could start with those 60 companies that we already knew. But they were smaller. And the more we went to bigger companies in the market, the more we made deals. So making them understand the problem is the same, just the scale is bigger and giving them the option to develop it together or giving them the option to drop out of the contract if it doesn't work, those kind of things that they don't have the risk internally to direct the go into a three years contract. And typically it worked out because the problem is the same, just the scale is bigger. Right. So it is very much about derisking it from their perspective that you can get them on board. Totally. With everything like now we're doing ISO certificate for security. It's another like we are secure, right? The tech doesn't change is just that you have the certificate. So it's another derisking fact like signaling. We have to label so it's more safe, although nothing changed or not much changed. Exactly. We have those big companies where you have the brands and you can mention them in sales interviews, then it's also easier because if they have been doing it, then it's probably okay. Absolutely. Self-fulfilling prophecy. So the trust is one key part. The other one is how much do you still have to educate the market? Of course there is a paradigm shift in the industry with the new technology available, but big companies are moving slower than smaller companies. So how much do you still have to educate them that they should use a solution like you are offering compared to doing things the same way as they have always done them? You completely write. It needs education and companies understand that they need to change. That's not much of a problem. They want to automate. They want to digitize. But they do not understand that there's completely two different kind of solutions. There's us as the machine learning native company, if you will, and there's these companies that have been doing things for 30 years, now claim that they also are machine learning of native. And to educate them was the differences there if the websites, if the marketing material, if even the sales pitch says exactly the same thing, that's difficult and that's why we came up with this, just test it. You know, don't buy something, like in German we say the cat in the sack. I'm not sure what the phrase in English is, but don't do that. Just test it. Go with the POC, implement it super fast, see that it works and if the other company doesn't even offer you that, you probably know why. Actually, is it easy to get them on a pilot, on a test with their data, because sometimes you know, again, big companies are a different clientele, sometimes they have a lot of processes to even allow you to plug into their systems and work with their data. Yeah, sometimes it feels like you have to sell the entire project just to do the POC, definitely. But it's gotten easier since we really went all in and spent so much time on creating these standard integrations. Because once you have those, once you speak the language of the IT, once they understand that there's not much risk involved, it's easier of course. I love this, because I think it's a great learning. Not every startup can do that of course, but if you can get them on a test on a pilot, you can really build this trust much faster and also have a good edge against your competitors who might say that they offer the same, but they actually don't. It's a true story that competition tells our clients that what we are offering is child's play, that they can't take it seriously because it cannot work. And that says a lot about how they try to maneuver they were around it, right? Because obviously they can't offer the same proposal, of course. We also talk a bit more about your custom acquisition, the sales process. How do you win customers? Do you do most of the heavy lifting of the sales process yourself? Do you work with resellers or partners? How do you win new clients basically? Yeah, so most of it so far came from cold calling and then during the sales process ourselves, we have some selected partners that we're building up and working more and more with them, but that's still early. So most of it was us doing the heavy lifting and we will always stay in that field of being close to the customer, being close to the market. And then what we do is we really involve our engineers also in the sales process. Because once you understand the customer, you can create the product. Right. And how long does your sales process roughly take? Let's say from you pick up the phone for the first cold call until they sign a contract with you roughly. It really verifies also because our smallest customers, they have like 50 ERP users. Our biggest customers have thousands of ERP users, so it really depends. A quick sales cycle would be something between two months to three months. That's rather quick. A long one would be a year. So somewhere in that range, if it's longer than a year, then something is wrong. Okay. They probably, yeah, they say they're interested but it may take some more time. It's difficult. Yeah, and getting priorities straight, right? There's so many projects that compete against each others. And even if they are interested, sometimes they, yeah, they don't see the priority. But really impresses me about your companies that you are still until today, you are bootstrapped, which is really impressive to get to the level where you are today and finance everything yourself. What are some tough trade-offs that you had to make along the way to not take external money and investors on board? I mean, you cannot grow as fast. Right, and you have to do a lot of the work yourself also, like the whole admin around it and everything. And of course, you have less money to pay in salaries, so you need to find the right people who are in it for the shares, who are in it for the fun of it. I think there you have a very interesting system in place, right? Yeah, so in really the early days, we had already company shares, so all the key employees like the first 10 got very nice packages but then we still decided that we don't want to limit us just to 10 people but we want to have everybody or to give everyone the option to have ownership. So what we do is that our salaries are a component that is fixed and a component that is variable and you can exchange the variable component as much as you like into shares. So you can do 1% 50% or 100% it's up to you and I'm talking about real shares and not phantom shares and not options but the same rights as the founders because I believe that this is what then is very interesting and also then you have ownership you want to build something and you're in it. Real skin in the game. Exactly. From all the employees that's like the dream scenario. How do you arrive at devaluation when you want to convert your bonus into shares because you don't have any investors on board so that's probably tricky. There's no third party telling you how much your company is worth. Yeah it's actually very tricky. So what we did is we did a market analysis like you would if you would suggest a VC to evaluate your company. The tricky part was because we're self-funded. We kind of better in all the metrics because we don't burn cash. We grow very fast and then we just looked okay in all those metrics where are we? What multiple would that result in? And then we looked at it over a period of 10 years and just took the average. Yeah. Because we don't need those sparks like three years ago or now. Of course. Because it's two extremes that us who want to build a sustainable business want something that kind of works every year. You said before that because your bootstrapped one of the tough trade-offs to make is that you cannot grow as fast as you might like to or want to. Where do you then allocate your resources? Like they're obviously limited. There's like limited cash flow coming in. Although it's usually prepayment as you described. But you need to make tough decisions. You don't have the millions of VC funding that you can deploy across all departments. Where do you invest your money to grow the company in a meaningful way? Yeah. So far we always invested in tech because it's impossible in our market to say we're product-led. Because that's not possible. You have to explain everything, right? You need to explain the process. You need to explain the product, etc. But we believe that if we build the product that solves the problem and we make the customer happy, the rest will follow. So that means we have a marketing budget of zero. We really in five years have not spent a single penny on marketing. And now that we are 30 people still I think more than 20 are in tech. So the majority still is techy and now it's starting to shift. Because now we see that if we want to continue with the growth that we have, we just need more workforce in business. So you really do focus on the tech, on the solution, solving the problem. Do you anticipate that to grow further as a company? You also need to now heavily invest in marketing and in sales to push the growth to new limits? Or is that not even necessary? I don't believe in us as a self-funded company to spend money in marketing because I don't think we can compete. If there's competitors out there that have millions budgeted for marketing sure, they will always win that race against us. What I think, and that's really our strategies, if we make our clients happy, if we solve their problems, work to mouth is very powerful. So if we stay focused on solving their problems, helping them, and then our sales teams can work with them, that will work out. So we need salespeople we don't need marketing. Got it. And to get salespeople, would you ever consider, I know this is a broad question, would you ever consider to take on external money to speed up this scale of face or this growth face to get more salespeople on board and grow faster than doing so as a bootstrap company? I mean, never say never. But one thing that is not completely accurate is that we do have a government grant right now. So we have this Swiss acceleration, Swiss accelerator grant, and that helps us to grow right now just over our usual limits. And then because of our model that clients pay us upfront, we can kind of organically finance growth. Right. And so far this worked out. And I hope that it will continue to do so. If not, we have to look for other options. Sure. You mentioned competitors, right? Spending millions on marketing, etc. How do you deal with them? You know, if someone, let's make a hypothetical assumption, if they would be a startup, very tech driven, but heavily VC backed and funded, entering the same market. And they would just have so much more money to throw at the problem and probably invest millions in marketing and in sales. How would that make you feel? Because at one hand, you know, you really understand your problem and the market that you're in, but you on purpose don't want to sort of compete with the VC game. But what if they do become your competitor? I see there's not a lot of chances that this will become the reality because we have a really, really complex product. Yeah. And typically the companies that are VC backed, they focus on something that's less complex or a smaller scope of what we're actually dealing with, doing that really, really well and scaling it very fast. And our problem is just way more complex than the typical company for that because we do the machine learning the neural networks to understand the documents. We have custom ERP integrations. We then have neural networks that take the data from the ERP and compare it against the data that we actually extracted from those documents. That alone is, I don't know, 1520 machine learning services that we're talking that we're developing. Then we have this whole web app tool that the users need to still solve cases and work with the software. And then we have our own workflow engine. So it's so much complexity. And typically you wouldn't do that if you were VC backed. I mean, we've been talking to investors throughout our whole journey. And it came step by step that we developed that. And whenever we told somebody, they told us what you have right now, take that and scale it. And we always went the other direction and said, no, we want to also build that because this solves the problem more. We'll see. I think that's a beautiful example that money doesn't solve that problem, but you're understanding of the problem and the customer actually does. That's what got you there in the first place. When everyone told you this, take this scale it, but you decided to go against it. What gave you this confidence to say, nice recommendation, but we go our own way. Yeah, I don't know. Maybe we're just too proud of our own opinion. No, I think we really want to find the best solution. And it's not the best solution to just build a neural network that understands the document if you can't compare it against the ERP data. It's just not the best solution because then you just hand over a different problem. Instead of unstructured data, you hand over structured data, but the problem of comparing stays there. So that's one example. And if you now take this example and you hand over the comparison, but still you need somebody to look at it to take a decision, then of course you can do that in the ERP. But instead having a web app like ours that shows you the documents that highlights the exact line in the document and tells you look there. By the way, this is in your database. This is on the document. This is my suggestion for you to do that. Right. That's just next level cool. And yeah, that ambition to really bring out the optimum. That's I think what brought us there. Because in the end, what we try to do is make our clients efficient and efficient does not mean full automation in many cases because it's not possible. So you really need to check how can I become way more efficient? How can I do five times as much in the same time? And for that, you'd need so much more than just one service. And again, it really shows how deeply you understand and want to solve the problem that you're tackling. It's a things beautiful. So you're obviously in a market that is ripe for innovation disruption. You have been five years in. It feels like you're just getting started. You know, you're really picking up speed. What's what's next for BLP digital? What have you planned? What's next on your milestones? Yeah. So what we always focus on is to solve the problems that we have for existing customers to make sure that they stay happy. That's pry off number one. And then to talk a bit further, what we're doing now is just we go broader because what we have the fundamentals that we developed, they can be used for many more document types than just those six that we have in our product portfolio right now. So that's the next step in terms of development. And we're also checking now structure data. So many of our clients get EDI data. That means they don't get documents but already structure data. Okay. But that data deviates. So you get perfectly structured data, but it's not the same as in your EOP and you somehow need to check deviations or better case learn how to automate it because the decisions stay the same. So that's one other thing that we're digging into. And other than that, just grow our markets because we've so far we've only targeted Switzerland. Nevertheless, we are in I don't know 17 or 18 countries because our customers usually have sites outside. And now it's about growing the business. That sounds like two things. Revenue growth by expanding the markets, but also more upselling possibilities by improving and developing the product in terms of use cases. Yes, and it makes so much sense because you don't want to buy five different solutions for five different problems, especially if there's overlaps. Of course. Yeah. Like procurement needs to check invoices. So it's not a finance problem. Because let's say you ordered something, you get an invoice for it. The invoice deviates. Finance can't even take that decision, right? Because procurement ordered it. So they need to check it. And then if they need a tool to check the auto confirmations, it makes a lot of sense that they use the same tool for it and not two different ones. Of course. So the company's also benefit from it. So yeah. You really are getting started. Yeah. Yeah. And how do you see BLP digital as a company? Do you want to build a profitable SME? So to speak, do you want to get acquired? Do you even want to do an IPO one day? What's your ambition with the company? The latter. Yeah. I really think that if we can manage from like ground zero to an IPO, eventually, that's a super cool journey. And I've really enjoyed so far. And I'm looking forward to the next five years. And let's see where we stand. Nice. And to wrap up the conversation, we also have some rapid fire questions prepared for you. I give you a short question and you have to answer in one sentence. You ready? Germany or Switzerland? Switzerland. Clear choice for you? Clear choice. Okay. What excites you the most about BLP digital? The team. Nice. How many hours of sleep did he get last night? I had seven, but I woke up during the night. So six. Okay. ETH or high-skate. I will not answer to that, but my hardest technical the combination of both, right? The combination of both. And what's your dream scenario? I know we touched up on that a bit, but what's your dream scenario for BLP digital? I hope that we can continue the ride and that we don't come into situations that force us to do the wrong choices. Solving meaningful problems with an amazing team. Exactly. How much better can it get? I hope that it stays like that. Team, thank you so much for coming on the show. Lots of success and all the best for the future. I'm sure we're going to hear see and read much more about you and your company. Thanks a lot for having me. It was great fun. Thank you. We hope you enjoyed today's episode. 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