Quantagonia Revenue (2024)

[00:00] Folks. My guest today is Dirk Zechiel. He's the CEO of a very cool company called quantagonia. They provide a quantum and hybrid computing SaaS platform for enterprises. Dirk, you ready to take us to the top? [00:11] >> Yes. [00:12] All Alright. So what does that mean? Quantum computing platform for SAS for for enterprises? [00:17] >> Yeah. So as you said, we are providing a SAS platform. And for us, SAS stands not just software as a service. It's more about solution as a service because our platform helps companies make better decisions in less time, and these could be these decision problems exist in the current HPC, the high performance computing space, so we are talking mainly about problems in the optimization, simulation, and AI space. [00:41] Mhmm. Okay. Interesting. And so, I guess, give me an example. Can you tell me specifically how a customer is using it? Do have any case studies you can share? [00:48] >> Yeah. So, for example, the big optimization problems in the world exist in almost every industry. Like, for example, if you need to schedule airplanes. Yeah? These problems are so big that it's impossible to schedule them by hand, and it's even impossible if you take the largest computer on the market to just put it on the computer and think this computer could could take all possible solutions and find the best solution. Yeah? [01:13] >> The promise of quantum computing is that these problems could be solved in the future when these quantum computers will be available. Industry availability of these computers will take at least three years, we estimate three to five years, and then putting these problems on a quantum computer will help to speed up really to solve these problems in less time, and you can even solve bigger problems of that. [01:36] So Dirk, how do you do that? I do you guys own a bunch of quantum computers? You rent out space, or you're using other pieces'hardware and people's hardware and processing power? [01:43] >> Yeah. So far, we have access to quantum computers, but all these quantum computers are more in research state because there are currently no real industry usable quantum computers out there. But we are currently so that's our hybrid classical compute way [02:02] >> we are going because currently, we are able to use these problems and put them on classical hardware, and this classical hardware could be CPUs or GPUs, FPGAs, so that these companies already get a speed up, and later on when quantum computers are available, we can internally move these programs on a quantum computer, and basically the customer will not see anything, but he will get an immense speed up out of that. [02:28] So just to be clear, are you using sort of a crowdsourced approach? Someone can say, I'm not using my laptop right now, give it to quantagonia and let them use the processing power in sort of a mesh network sort of format so that a pilot or or Delta can use them to schedule airplane tracking? [02:42] >> Yeah. No. No. It's not a quote [02:45] >> thing. It will be so we connect to computing centers in the back end, like we could rely on services like Amazon Web Services and so on, on compute centers providing these CPUs or GPU stuff, in the future, quantum computers as well. [03:02] Got it. So you're not you're not necessarily, like, owning quantum computer right now. Your your secret sauce is writing and taking complex things like tracking airplanes and enabling that problem to be solved with, you know, AWS right now, but in the future, easily switch your customers to quantum computers. [03:18] >> Exactly. Yeah. We are we are a software provider, software guys, and we help companies to make these better decisions through software. So the thing is because you cannot really you cannot just port existing software to a quantum computer in the future because it's a totally different architecture. It's a little bit like the new m one chip with Apple, so they have invented this Rosetta platform, the virtual machine, so that you could put in x 86 code [03:44] >> and run it on m one chip, which is a totally different architecture, we will do basically the same for quantum computing. So put your x 86 code in, and you can run it on the quantum computer in the future. [03:55] I see. Oh, what's going on there, YouTube? Good to see you guys. Now imagine this. You love watching these interviews with SaaS founders, but imagine if we took all of the valuation data out from over 2,807 interviews I've done manually. Saves you a lot of time. Well, we've done this. We've built it into the beautiful interface inside of Founderpath. Check this out. I'll show you how you can access this in a second, but you log in, [04:20] you connect your Stripe account, you see your valuation real time. You can see what it changed over the past eighty eight days and even set goals for valuation this year. Now the secret evaluation is there's many different ways to value a SaaS business. So the reason you're gonna see three or four different valuations inside of your Founderpath dashboard, this is all free by the way, is because depending on who's doing the buying of your SaaS company, [04:44] you're gonna get a different valuation. A VC is gonna pay a different valuation, Private equity firm is different. If you're gonna do a minority sale, that's different. And if you sell the whole business, that's a different valuation. You can see all those when I hover over here. Right? So the teal is what a VC would pay. Yellow is what private equity And red is if you sold the whole thing outright. Now what's cool about this is [05:06] this is not built off random data. Again, you guys hear these interviews on YouTube. All these datas are built from real time valuation data points founder share with us on the show. So traction 1,200,000 seed round 3.7 raise. They sold 22% of their business. Go in here and filter by the event. Maybe you only wanna see companies that have sold the whole business. Well, here are a bunch that have been acquired the valuation and the multiple. [05:31] Maybe you're going out right now and you're raising your seed round. We'll go in here and look at all this recent seed deals that went down, what they raised, what valuation they raised at, and what percent that they sold. There's never been a larger dataset of SaaS valuations than what you can get now inside of Founderpath. And we're thrilled to bring it to you. All right, we're gonna go back to the YouTube video here in a [05:54] second, but if you wanna check this tool out, if you wanna jump in and sign up, you can check it out for free to get your valuation at this link, this link, founderpath.com/products/valuations. Or if you go to founderpath.com and hover over products, click on get your valuation here, and go ahead and sign up to give it a whirl. Again, all that valuation data live right inside the platform. I hope to see you there. Alright. Let's jump [06:20] back into the interview. So these customers today, what are they paying you on average per year to use your technology? [06:25] >> So we have founded the company end of last year, end of two thousand twenty one. So the company is four months old, five months old. So we got the first investment in December four months ago. And so we are in development So [06:39] you're pre so you're pre revenue today then? [06:42] >> Yeah. So yeah. Exactly. So but we have signed up with ten, eleven customers on on an LOA basis. We're calculating the first real problems with them. So we could could already proven that we have a speed up in solving their problems. And, yeah, we are not yet charging them. [07:00] So, Dirk, let's go back to those 11 customers here in a second. But first, obviously, you have to pay yourselves while you guys are building this if you're not making revenue. So you guys have raised capital. How much did you raise in December? [07:09] >> We we cannot disclose that because it's under NDA, but it's enough for this year to grow up to 20 people. [07:16] Well, sorry. Why can't don't I mean, most governments require when you raise most most governments require when you raise your investors that you file government forms to to basically say that. And on your Crunchbase profile, it says last funding type precede. Why can't you disclose the amount? [07:30] >> It's on the investors didn't want to disclose it. Yeah. [07:33] But but why is that? It's your company. Why would the investor why would you give investors control over that? [07:37] >> I I I don't know. I need to check with them. Sorry for that. [07:41] Well, you work directly with them. You didn't ask them, hey, guys. Why is it important for you not to just, like, to keep this private? [07:46] >> Not yet. Sorry. [07:49] Well, I guess that's a The reason I'm asking is because your ability to retain talent, people aren't gonna join you unless they know you have runway. And so putting a press release out that says we raise x, right, gets people confidence. It also enables you to bring on customers faster. This had to have been a conversation during the raise. [08:02] >> I don't believe this never came up. [08:03] So I'm just trying to understand strategically why you were okay with it. [08:07] >> Yeah. I need to check with them. So and we are not disclosing it. So that's that's our point. Yeah. So [08:13] Dirk, you're missing my question. I'm not asking you to disclose how much you raised. What I'm asking is strategically, why did you decide not to disclose it? It doesn't help you get talent, and it doesn't help you communicate to the market that you're gonna be around for a long time to get big enterprise accounts on day one. [08:26] >> Yeah. Yeah. It's a strategic decision decision which has been made, and that's we we are not disclosing that decision. Yeah. Sorry for that answer. [08:36] You're not answering my question. Off your website. I've asked about four times now, so I'm not gonna ask it again. We'll we'll move on. The I guess I guess, let me then pivot. Right? So how many folks are full time today on the on the team? [08:49] >> We are now with 12. I need to think about it because we're adding people every week. Yeah. 12 itself. Yeah. [08:55] Okay. And how many of those folks are engineers? [08:59] >> Out of the twelve, seven are engineers so far. [09:01] Okay. And how are you able to recruit these engineers? I imagine this requires top tier talent. [09:08] >> Yeah. We have a very strong network. For example, two of our founders, Sebastian, he's vice president of the Zuse Institute in Berlin, which is one of the top HPC institutes centers here in Europe. So he is also professorship for optimization and machine learning, so we could attract through his network a lot of people. We have one of our co founders, Sabina Jeschke. She's also professor two professorships at TU Berlin and in Aachen, and she is a [09:36] >> former board member of the Deutsche Bahn. That's a German railway here in Germany. It's a top company, belongs to the top 50 companies here. So through that network, we could hire a lot of hire and attract a lot of people. And, yeah, myself, I'm in since twenty five years in this business of optimization simulations and machine learning and, yeah, basically, mainly through our network, we are able to get the people. [10:00] So you're titled CEO, but just to be clear, I mean, you two are basically co founders. Right? [10:04] >> Yes. Exactly. So my career is I'm a computer scientist. I started in technical positions, but then I moved pretty fast to sales positions, leading whole sales teams, and then I was the co founder of a company Gurobi GmbH in Germany. I was building up the whole operations here for the German market. They they are the market leader for optimization and software based. That company got sold in 2017 to a private equity firm, and I also founded [10:35] >> a company doing spot scheduling, which is also related to optimization because you cannot imagine, but these problems are also really complicated in terms of how many solutions you could find and getting the best schedule out of it. Like the NFL, they are running several thousand nodes on Amazon for a few months just to get the best NFL schedule in The US. Mhmm. [10:58] >> So how consuming. [10:59] So how so what? There are three I mean, doctor Sabina, doctor Sebastian, you, and Philip, there's four cofounders? [11:06] >> Yeah. Exactly. Four. [11:07] Okay. Got it. And was this was this a I mean, based off those backgrounds, there's a lot of connections to sort of institutions. Right? Was this a IP spinout developed inside of an institution? [11:17] >> It's not a no. Not totally IP spin off. So we are building our own IP from scratch. [11:24] Oh, okay. Got it. So there there are there are no institutions that that you're licensing this IP from? You don't have any license agreements like that? [11:30] >> We are strongly connected to Fraunhofer Institute here in Germany, which is a large research organization. And because Fraunhofer Technology Funds, they are one of our investors, so we are strongly connected there and having research connections there. You could say that in some part, we are a little spin off of them. Yes. [11:47] I see. Okay. So they they true. I mean, true or false. They own equity in the business to some degree. [11:51] >> Yeah. Exactly. [11:52] Yeah. Okay. Interesting. Okay. Talk to me about the first 11 enterprise customers. Right? A lot of people don't they they're not always sure how to land an enterprise customer, especially as a start up. Some people say, you know, send them a a POC, then sign on as a design partner, and have them sort of prepurchase a software license that doesn't exist yet. Help me understand how you're closing this. [12:10] >> Yeah. So those those partners so we we know them from our business network, and they already have these kind of problems modeled in a way so that they could easily export those problems and ask us if we can make some some benchmark ones and see if we could also solve their mainly scheduling problems, like for production scheduling, job job scheduling, for example, one we have in in energy scheduling. It's like the power plant scheduling, and then [12:34] >> it's quite because we have some import interface, we could quite easily put it on our platform and run these first benchmarks. Yeah. [12:42] Okay. So, yeah, so my question is, contract wise, what are you selling them right now? Is it a POC? Is it an RFP? Is it a prepayment of a software license? What are you selling? [12:53] >> Yeah. We are selling them a partnership. So it's in the beginning, it's like an LOE, it's an understanding that we are working together on these problems, elaborate if our solutions would work for them, and the next step would be that they are paying for the solutions and if we could prove that it's working. So as I said, we are just releasing version 1.0 of our software, and so that will be the work for the next few [13:13] >> weeks to really prove that we are bringing benefit to them, and then the next step would be that this will turn into a commercial relationship then. [13:21] Okay. I'm sorry. What what does LOE stand for? [13:23] >> Letter of intent. [13:24] Oh, [13:25] LOI. Letter of intent. Oh, sorry. Yeah. I'm going. What's an LOE? Got it. LOI. You've signed you've signed LOIs. Now it does do the LOIs say something like we're going to deliver x product. If x works defined by y, then you'll pay z? [13:42] >> No. It's not paying z, but it's it's stating that we have a joint collaboration. And if that turns out, then we work on a commercial relationship. Yeah. [13:51] Okay. How do you define do you define in the LOI what success means? [13:57] >> Yeah. What success means if we are faster than the current stuff available in the markets, then that's defined as a success because we can really pretty easy benchmark how long they need to solve the existing problems on their hardware with current software they have. [14:12] Yeah, Dirk. Give me an example of that. So a power plant. How long does it take them to solve one of their big what's what's a problem a power plant has, and how long does that typically take them without you? [14:20] >> Yeah. For example, in Germany, all the energy is traded within windows of fifteen minutes. So big energy companies, they make every fifteen minutes a decision. Should we buy energy? Should we produce energy? Do we get enough solar energy for the next fifteen minutes or wind energy? And so they have a time window of these fifteen minutes is five minutes data in, five minutes kept making the next right decision, and then five minutes data out. And if [14:43] >> they could if they could solve in these five minutes a more complex problem, that's a huge business impact for them because then it's like a trading for in in finance. Yeah? And so that's a benchmark. How much could we calculate in these five minutes? If we could do it faster, if we could calculate it in three minutes, then they could put more value. [15:00] But calculate what? So, like, how do define how much you can calculate? Is it, you know, is it n data points? Like, that's what I'm trying to quantify. [15:07] >> Yeah. Yeah. It's basically their problem. So they can what they currently calculate in five minutes. So they have, yeah, maybe 10,000 data points and an objective function. If we could solve the same in three minutes, so then it's comparable. [15:20] Okay. Got it. So you'll say current your current thing in the LOI, your current solution solves 10 k objective functions over five minutes. We can solve 10 k objective functions in two point five minutes. If we do that during the LOE, then we set ourselves up for a commercial relationship. [15:34] >> Exactly. Yeah. [15:35] Ah, very interesting. Okay. That's very helpful. And then okay. So next step is how do you think about pricing? Let's say you have successful PO LOIs. Right? How do you decide what to price the thing at? [15:45] >> Yeah. So that's what what we are currently working on. So it depends. So because our customers, they trust one problem twice a year because it's a strategic decision. Yeah. How do we build up our supply chain network? So that's a decision you make once every few years. Yeah? Or, like, if you do pass a delivery, big company, for example, like UPS, so they make a decision for their network once a year. So then it might be [16:08] >> more expensive to create this one solve this one once in a time solution instead of companies like, I said, the the electricity power plant companies doing that every 15 minutes, so they might buy more subscription which allows them to do, yeah, calculations all the time, for example. And that's where we are currently working on to make a price model which adapts to to everybody. So we have benchmarks because from our previous experiences, how how much we [16:38] >> could charge for that. And they as I said, they are saving a lot of money if they get to the best solution, and they're easily willing to pay in the 6 digits US dollar space per year, for example. [16:53] Do you tie the price point to number of objective functions you're solving over a standard period of time? Like, what's the utility based thing you price against? [17:03] >> Yeah. So a number of objective function doesn't make sense because or it's a number of variables because some some people have a small problem which brings a lot of business value and some have mathematically speaking. [17:13] So yeah. So what do you tie pricing to utility wise? Is it an amount of data computed over a certain period of time? Like, do you quantify it by? [17:19] >> Yeah. Will be more related to the value we could bring to solving their problem. That's what we are Okay. [17:25] So that's hard, right? Because then you have to prove attribution, right? So that is basically custom pricing every single time. It's very, very high touch. It's a you know, you need to hire a bunch of AEs, etcetera. [17:35] >> Yeah. We we will have in the in the future some standard pricing. For example, if you if you utilize our service for for the, like, for the whole time, you need that kind of speed up, you need that kind you have that kind of model size, then we could put a price tag for it. Like I said, something like a 100 k a year if you have a power plant, a power plant scheduling, for example. But yeah. [18:02] >> If you have just if you need to because you cannot make a pricing based on on time, as I said, because one customer is running it for ten minutes once a year having high value. Another is needs to run it the whole year and having low value and high value, but low value per time. Yeah? So that's not comparable. [18:21] Well, we'll see what happens. The question is, is the funding you raise give you enough time to prove these things out to drive some revenue to either get profitable or get into your next round? And we can look at one of ventures and FTTF, their typical deal sizes are anywhere between 500 k and €2,000,000. So we can assume you sort of raise something in that range. How much time do you think you have to start proving [18:41] out contracts before you have to think about raising again? [18:44] >> So plan is that so we we might have time for another year, but the plan is maybe to raise end end of the year. But we are not currently in the raising phase. [18:55] Alright. We'll see what happens. In the meantime, Dirk, let's wrap up here with the famous five. [19:00] >> Number one favorite business book. [19:02] What's your favorite business book, Dirk? [19:04] >> Oh, my my favorite business book is [19:09] >> it's an old book. It's large. It's called LAMP, large account management process. So when I started to to to become from a technical person, a salesperson, I bought this was my one of my first sales books I bought, and because I saw sales not like an art, but it was more like a process, and to understand the accounts, that gives you a pretty good perspective on how to understand large accounts, how to deal with the sales [19:36] >> from the sales point of view, how to identify the objectives and the goals of this account and make account management in a really structured way. So that's that's the business book. It's old, I guess, twenty years, but it's still current, like, I think. [19:49] Mhmm. Very cool. Number two, is there a c is there a CEO you're following or studying? [19:54] >> CEO I'm following studying, so it's a good question. Not not a single one. I'm following a lot on on LinkedIn, not a specific one. I couldn't name a single person. [20:07] Okay. Number three, what's your favorite online tool for building the business? [20:12] >> We have several, but I liked a lot to work with Notion in the past. That's that's pretty helpful for bringing information for the team together, and that's yeah. [20:23] Number number four, how many hours of sleep do you get every night? [20:27] >> Six. [20:28] And what's your situation? Married, single, kids? [20:30] >> Married, three kids. [20:32] Wow. Busy guy. How how old are you, Dirk? How old are you, Dirk? [20:35] >> I am I am 47 and [20:38] Great. 47. Last last question. [20:40] >> Something you wish you knew when you were 20 years old. [20:44] >> I wish that's a good question. I thought about it yesterday already, and I wished to meet my wife earlier. I met my wife when I was 30, and I wish would wish to meet her 20 already. [20:53] A good answer. I've never heard that one before. Over 3,000 episodes. I've never heard that one. That's a really good one. All right, guys, there you have it. Quantagonia.com, helping big corporations, enterprises, power plants, Delta, right? Plane companies understand big problems that need quantum power, but how to solve those problems today using things like AWS. Sort of sit in between with the idea long term to move those problems onto quantum power when quantum is more available, [21:16] quantum computers are more pervasive. We'll see what happens. They raised a pre seed last year to fund their growth. They're at 12 people today, pre revenue, but 11 enterprises in LOIs right now. We'll see what happens next as they launch pricing. Dirk, thanks for taking us to the top. [21:29] >> Thank you. [21:32] One more thing before you go. We have a brand new show every Thursday at 1PM central. It's called Shark Tank for SaaS. We call it deal or bust. One founder comes on, three hungry buyers, they try and do a deal live and the founder shares back end dashboards, their expenses, their revenue, ARPU CAC, LTV, you name it, they share it and the buyers try and make a deal live. It is fun to watch every Thursday, 1PM [21:57] Central. Additionally, remember these recorded founder interviews go live. We release them here on YouTube every day at 2PM Central. To make sure you don't miss any of that, make sure you click the subscribe button below here on YouTube, the big red button, and then click the little bell notification to make sure you get notifications when we do go live. I wouldn't want you to miss breaking news in the SaaS world, whether it's an acquisition, a big [22:20] fundraise, a big sale, a big profitability statement or something else. I don't want you to miss it. Additionally, if you wanna take this conversation deeper and further, we have by far the largest private Slack community for B2B SaaS founders. You want to get in there. We've probably talked about your tool if you're running a company or your firm if you're investing. You can go in there and quickly search and see what people are saying. Sign up [22:41] for that at nathanlatka.com/slack. In the meantime, I'm hanging out with you here on YouTube. I'll be in the comments for the next thirty minutes. Feel free to let me know what you thought about this episode and if you enjoyed it, click the thumbs up. We get a lot of haters that are mad at how aggressive I am on these shows, but I do it so that we can all learn. We have to counter those people. We [23:01] got to push them away. Click the thumbs up below to counter them and know that I appreciate your guys'support. All right. I'll be in the comments. [23:08] >> See you.