How GetBruin grew to $1M revenue and 40 customers in 2026.

Nathan Latka (00:00) Hey folks, my guest today is Brock Krakan. He's a Berlin based software engineer turned founder who previously worked as an engineering manager at HelloFresh. He co-founded Bruin to replace the fragmented modern data stack Think5Tran, dbt, airflow and other BI tools with one unified platform. Brock, you ready to take us to the top? Burak Karakan (00:18) ⁓ Thank you so much for having me, Nathan. Nathan Latka (00:20) Alright, 5.2 Valuation 5 Tran, you're taking them down, right? Burak Karakan (00:24) Absolutely. We're taking anyone that stands our way down. Nathan Latka (00:27) Ha ha ha! How are you gonna win? Tell me what you launched. It looks like your mousetrap is your CLI. Tell me more about that. Burak Karakan (00:35) we are, we're building it a unified data platform and an AI data analyst that allows people to ask questions and get answers in, in minutes. we are the only platform in the market that allows, ⁓ building the full life cycle of data. So it essentially allows us to, ⁓ go to from a question to an answer in minutes rather than, than weeks within, ⁓ compared to other organizations and, And we can do that because we have built a unified data platform. The essential, the core idea is you connect your different data sources to our platform. And then our agent learns from all of these different data sources that you have. You can connect your data warehouse ⁓ and it lives in your Slack account or a Teams account, et cetera. You ask a question and you get an answer within a couple of minutes. And the reason we're winning is because we are the only tool in the market that connects to this many different platforms and that has a full understanding of the life cycle of the data. Nathan Latka (01:36) So a couple of things I want to touch on here. Um, context is obviously what a lot of people are saying is going to win sort of the AI space or whoever has the most context, the brain and can organize the data in a structured way to help users is going to win. love your background. You're an engineer. see GitHub feature on your website. You mentioned integrations. This graphic is powerful. So let me dig on a couple of these concepts. How many integrations do you support today? Burak Karakan (01:54) Yep. we scored more than 200. Nathan Latka (02:00) Okay, that's really hard to maintain. How big is your team today and what's your secret sauce for keeping all those live and active? Burak Karakan (02:06) We are a 15 people team. We are using AI very heavily, but more importantly, we are building a lot of things in the open source. So if there's anything that we're holding behind that we need new kinds of integrations, it doesn't have to be us that just builds that. We get a lot of open source contributions as well. And people join our community, help us build better connectors with all of our tools. So you can see we have quite a bit of stars for, of course, all of these different tools that we build as well. But basically a creative use of AI, ⁓ smart team and building things in the open source. Nathan Latka (02:41) Your ingester is by far what is like the most popular thing. think about how lovable launched. was a side project. He launched as open source on GitHub before it like totally took off. You're, are you following that same growth playbook? Burak Karakan (02:48) Yeah. Yeah. We are, so we're building all of these open source products to be a part of our product as well, but also making them independent, useful tools for others to adopt what we build here. This is generating a lot of inbound interest for Bruin in general, because people are already using the tool before they even talk to us in any shape or form. So this pre-existing trust relationship helps a lot because we're selling a core data plan for our product. Nathan Latka (03:19) Barack, I can't help but do this, but I'm pattern matching. I've done 3,800 of these interviews back to 2017. can generally like quickly recognize like who I missed out on that was a winner. When I think back to when I interviewed get a sit at GitLab and he was thinking the same way, right? When he eventually launched the monetization product on top of the open source, the community revolted and it took him a while to figure out how to do that. Are you see like, let's say you turn into a hundred million, 500, a billion dollar ARR company. Will your open source community revolt? How are you balancing that? Burak Karakan (03:47) I think we have this principle that the core of our technology will stay in the open source. It will still be open because I do not believe in, there's almost an emotional connection between open source software and myself. I have learned a lot of stuff for open source. So I would like to be able to build it in such a way that it can be built in a sustainable manner. That is why our open source product and a closed source platform are not competing with each other. They are complementing each other. People can use our open source tooling without having to be a Bruin customer, but they're going to get a much better experience if they use both of the tools and the platforms in the same place. But this relationship where both of these things are complementing each other allows us to build it in a sustainable manner where we don't have to monetize our open source users. We can instead build a sustainable, reasonable business where we generate a lot of value in a managed product. while still keep our core technology open source if people want to build things by themselves. Nathan Latka (04:50) Tell me more about this. You're also seeing in the press right now, obviously WordPress and automatic suing WP engine, same sort of concept here. There's open source automatic didn't like the WP engine is making 600 million of ARR per year. And in their view, not contributing enough code back to the open source platform. You're, you're sort of managing this balance, right? So at what point would an open source user hit a paywall, right? And say, Hey, you should use Bruin cause you're to get X, Y, and Z more value. What does that sound like? Burak Karakan (05:07) and ⁓ there, would be very sad if they are refining themselves at a similar point. So we are building all of our core products to be independent. They can, we have three major products that we launched open source. have ingester, burn CLI, and recently DAG. Our dashboard is called product. They are all independent products. yes. And they are all independent products that allow people to use it without having to have any sort of paywalls or, or anything related to us. Nathan Latka (05:32) That's these three, right? Burak Karakan (05:44) ⁓ so the only reasonable alternative that I could think of is if someone wants to have like a managed platform that like auto scales with all of your workloads, et cetera, and you do not want to build that. You can use brewing cloud. You get a lot of things out of the books with that, but you do not have to. And it's very important for me that no one has to do that. Nathan Latka (06:03) I I see. I see. And what do you have? Are you still building your distribution channel open source today? Or do you have people that are now paying for the cost? Do you have paying customers already? Burak Karakan (06:14) Yeah, we have around 40 customers companies around the world that are paying for Brune. Thank you. Thank you. Appreciate it. Nathan Latka (06:18) Barack, congrats, that's awesome. That's awesome. Can you give me a general sense of how your pricing is it? I don't know, number of modules, product, seat base, usage base, upselling, what's that look like? Burak Karakan (06:32) We are selling, so our pricing is generally in the pay-per-use model. So you basically use either our AI analyst or our ⁓ compute platform. So based on which of these ⁓ modules that you use, you pay based on how much you used it. You can think of it similar to how cloud providers charge you for the compute that you use on their platform. ⁓ And ⁓ once they go above a certain certain stage in terms of platform usage, we offer them fixed price plans. So they get a lot of compute, a lot of features included, and they get our enterprise support and stuff ⁓ for a fixed monthly fee. Nathan Latka (07:10) Okay, God, can you give me a general sense? Are these folks that are paying 100 bucks a month on average or like 20 grand a month on average? Burak Karakan (07:16) It's a couple thousand dollars a month, roughly. Nathan Latka (07:19) Okay. So do you, with your current pricing model and your current three products and how you're sort of structuring the value and the sort of feedback loop, do you think you can get to, know, your first hundred thousand dollar per year customer pretty rapidly? Burak Karakan (07:32) Yeah, we're already there. it's the general. so not 100,000 customers. I thought you said $100,000. Nathan Latka (07:35) you already have 100,000 customers. No, no, 100,000 customer. You already have one customer that's paying at least 100 grand per year or run rating to 100 grand per year. Burak Karakan (07:45) ⁓ very, very close to that. like, like numbers, very close because like this is an important thing to understand is we are building a platform that take that replaces like six different tools within the organization, as well as a huge amount of, ⁓ engineering effort, which means that there is already a multimillion dollar opportunity value that we generate for the organization. And, and, and we take a part of that essentially. So it becomes a win-win for both them and us and, ⁓ Nathan Latka (07:47) That's really exciting, Brock. Burak Karakan (08:14) On that scale, it becomes very easy to demonstrate the value once they adopt our product suite within the organization. Because think about it this way, try to hire an engineer, try to hire a data engineer. Try to hire one in the US. You're going to pay a couple hundred thousand dollars a year. Easy, easy. None of my customers had to hire a data platform engineer once they started working with us throughout the past three years. Think about all the money they saved working with us. Nathan Latka (08:22) So average, yep. Burak Karakan (08:43) let alone the other benefits of every other advantage they get becoming a customer. Nathan Latka (08:50) So you said last three years, do you launch in 2023? Okay. Very cool. And just going back, you know, are you still finding time and you and your full-time team finding time to contribute back to the open source models so that those three free products are always getting more valuable? Burak Karakan (08:53) Yeah, exactly. Of course, all of our, ⁓ so the value chain for us goes from open source all the way to our cloud platform. So this means that any new feature that we build in our cloud, 99 % of the core work happens in our open source product. So that's why you see like, if you go to any of our core repos, if you go to Bruin CLI or DAC, you're gonna see commits from today. So basically a lot of our work is happening going through. Nathan Latka (09:32) And gestures are most popular though, right? Burak Karakan (09:34) Ingestor is very popular, yes, because it appeals to a larger audience. If you click the Bruin one on the right side, that one is the... because Ingestor is about to get a large launch next Monday. But basically, Bruin is the one that gets a lot of commits, and you can see we make like tens of releases every week. So... Nathan Latka (09:52) There we go. This is what I was looking for, right? When I see that the founder of the company that's monetizing is also the biggest contributor to the open source code, now I know you're not lying to me. There is direct alignment. Burak Karakan (10:04) Yeah, so I would dread to not be able to contribute back. I'm very much in the trenches in that sense. ⁓ Nathan Latka (10:13) Very cool. Okay. This is very fascinating to me. Look, I'll tell you why. ⁓ This is a little self-serving, but I think it is really relevant. Founder Paths, you our goal is to deploy money to founders fast. We spend a fortune on iPass tools, right? We built the Stripe integrator directly, 4,500 connected accounts, but like accounting, QuickBooks, Xero, the bank, you Plaid, Saltage, Teller, Kodat. Are you effectively saying that what you've built, I mean, I look at this graphic. what you've built, can use the open sources and save like 30, 40 grand a month of spend I'm paying to other iPass tools. Burak Karakan (10:44) 100%. 100%. You can, you will also save a lot of time and effort from like engineering and people that you'd probably hire for that, cetera. It's not just tools. And you get to do a lot more stuff a lot faster. So you should give it a try. Nathan Latka (10:57) Okay, I'm going to sign up and test this and contingent on me falling in love Barack with your product. I will you let me invest if I fall in love and I want to help market the hell out of this and use it as a customer. Can I invest? Burak Karakan (11:07) ⁓ Well, ⁓ why not? So let's see, let's get you using the product first and let's see how you like it and tell me something to make better and then I'll think about it. Nathan Latka (11:19) I that that is exactly what I'm also looking for. Right. I think this is the future. I think what's interesting about this, right. Is there's everyone building like historical software companies, just building like chat on the side of their dashboards, but all the data they've ingested is dirty data. It's not cleaned in a data lake. It's not stored privately in a rag DB, right? You know, it's expensive. If you're truly solving that problem, then you will own the context brain for anyone wanting to do something related to CRO work or data engineering work or conversion work. Burak Karakan (11:47) 100%. Nathan Latka (11:48) Right. And, you, I mean, you can effectively and say, look, instead of to your point paying 300 grand for that employee, pay 20 grand a year for brewing. Burak Karakan (11:56) 100%, 100%. I think people miss like even in the, just asking questions to data and getting an answer, people think, okay, like it's, it's, you generate SQL from texts, you know, it's so much more than, than the whole thing where if you do not have an understanding about where the data comes from and you cannot connect it back to the business context, you cannot have a reliable agent that will help you understand your data. More importantly, it's actually like Calling this an AI data analyst is like an easy way to explain this, but in reality it's closer to an AI data team. So it can actually create pipelines for you, it can ingest data for you, it can inspect data quality issues, it can check your pipeline logs, it can do all of those things out of the box. Nathan Latka (12:38) Why don't you sell it that way, Barack? Why don't you sell it that way, right? Like the founder like me knows I'm going to pay a CRO 200 grand to join Founder Path or a software company. If you tell me Nathan will be a much better CRO for 50 grand a year, I'm going boom, sign me up today. Like, why don't you sell based off like the head count you're replacing? Burak Karakan (12:54) I mean, sometimes it gets offensive. So people are, people tend to get a bit more, you know, people think it's like too strong ⁓ of an argument to say, Hey, like you're just going to replace all that hat count. ⁓ The way I like to talk about that is these are problems that are already solved. You know, if you have people in place that you already hired, these people should be working on like higher leverage problems to solve for the organization. And you don't need to hire new ones if you did not hire them already. Right? So, ⁓ depending on what part of that, that, that journey you are, ⁓ you either are going to avoid a lot of hires or you're going to have your existing people to do a lot more valuable work. What we see with our customers is they do not stop hiring. They start hiring different profiles. They start hiring different people. They start using that budget for, you know, different personas. Instead of hiring a data platform engineer, you hire data scientists. You hire someone that actually sits next to your business teams and actually understands what they're trying to do with data and help them build better models, help them use the data better and ingrain it within the business logic itself. So ⁓ it's not replacing that sort of ⁓ budget. So you like don't spend it at all. It's more like maybe there's better ways to spend that money if you can, if you want to. Nathan Latka (14:12) If I use Bruin and I want you to have access to my QuickBooks profit and loss to help me better, right? You're like a little CRO inside my company. And this is on an open source tool. How do I make sure my data is private? Burak Karakan (14:24) So for open source stuff, everything that you run stays within your computer or wherever you want to deploy. We basically have like a very simple telemetry that tells us like someone ran something or not. We don't even see what you actually ran, but you can disable that too. But all of your data, all of your credentials, all of your connections lives in your computer, on your device, on your infrastructure for all of our open source stuff. For our cloud platform, You obviously share some credentials for our platform to be able to pull data for you and move it to your, to your warehouse. But essentially every data we pull lends into your warehouse, passes through our infrastructure only when it's absolutely needed in ephemeral physically isolated environments so that they do not have to share data or resources with anyone else. we go through like we were SOC 2 certified, certified, where we go through regular. pen tests and stuff. it's like a very, quite a bit of a thing to run like a multi-tenant infrastructure like that. For open source, you do not have any of these things. Like everything runs in your environment. You could run it in like a very, very restricted environment, which some of our customers do. Nathan Latka (15:37) FTS to how many folks are full time you said 30 Burak Karakan (15:39) ⁓ No, we're 15. Nathan Latka (15:42) How many are engineers? Burak Karakan (15:43) Yeah. Um, 12, sorry, 12, 12. Yeah. Very, very engineering, I mean, engineering is engineering and like, these are product minded engineers. So everyone is both an engineer and sort of owning that product. Nathan Latka (15:45) 11, okay, so heavy engineering. Okay, 12, 12. That's great. Yep. That's great. Okay. And then to help me understand if you've bootstrapped raised, did you do a seed round? Burak Karakan (16:03) We did do a seed round recently, which we haven't disclosed yet, but yes, we are VC backed. Nathan Latka (16:09) Should we, should we announce that on the show or no, you want to keep that private for strategic reasons. Burak Karakan (16:12) I would like to keep that private for a bit more. Yeah. Nathan Latka (16:16) Why did, why did my research team, why did my research team tell me they found a public source that said you guys had raised 4.9 million per pitch book. Burak Karakan (16:23) ⁓ I don't know. I guess maybe they have good sources, but we did not announce it anywhere. Nathan Latka (16:30) Okay, got it. So you're saying that pitch book data, maybe they guessed, maybe they guessed, but you didn't give them that data. Okay, fair, fair, fair enough. That's great. Okay. And you mentioned 40 customers today. You're right. You've got some that are scaling, you know, a thousand a month, others that are getting even bigger. Are you comfortable sharing if you're north of a million of ARR at this point? Burak Karakan (16:35) Simso. Yeah, no, no, we didn't. ⁓ We're not north yet. We're very close to that. Nathan Latka (16:52) And what enabled you to get like your first 500k of ARR in the first two years pretty quickly? Was it mainly open source community or a different growth channel? Burak Karakan (16:59) Um, I think the channel was basically like founder, like sales. We have taken it upon ourselves that we're going to help people no matter what they're going to be a customer or not. So every time we start talking to some friends, some people in the industry, we're going to be like, okay, here's a platform, here's a product, but we're actually going to sit down with you and try to understand what you're trying to do. Try to help you solve these problems. And eventually that turns into like a customer relationship very quickly. But what turned out to be like a biggest leverage for us was. A lot of these learnings replicated themselves very quickly across the, across different companies. So we sold this like, I don't know, a few set of problems for a gaming company. Suddenly the stuff that we have built, the capabilities we introduced into our product can solve these problems across 20 other gaming companies. Solve these sets of ⁓ problems with, I don't know, LTV prediction or ⁓ marketing attribution and whatnot for, for an app business. You can suddenly replicate all that solution to, to, I don't know. 20 other companies, same for retail, same for e-commerce, same for climate tech, whatnot. So essentially what allowed us to get a lot faster was going quite a bit slower initially, which was painful for us personally to sort of hold ourselves back a bit more. But eventually we found ourselves in a pretty advantageous position to be able to replicate that capability. Nathan Latka (18:21) Look, I think if your product does what it says it should do, I think you should be growing much faster than you are. mean, this is a huge opportunity. Whoever wins the context layer of this sort of data and then builds agent wrappers on top of it to actually get work done is just going to build a massive business. have to ask you're in Berlin, I believe, right? Do you want to be in San Francisco? I mean, how, what's it like building in Berlin? Burak Karakan (18:41) ⁓ So I am not in Berlin right now. I'm in Istanbul. We have some people in Berlin. used to live in Berlin. Berlin is a very different culture. It's not, I love Berlin, beautiful place, but maybe not the best place to build an ambitious business, you know? So there's a lot of, it's very nice place to be an employee. It's, yeah, well, at some point, yes. So right now there's some, Nathan Latka (19:00) Well, what's Istanbul? I mean, come on, if you're going to go for it, move to San Francisco and let's hit 10 million of ARR in six months. Let's go. Burak Karakan (19:10) There's some family reasons that I need to be in Istanbul for, but ⁓ yes, ⁓ with that being said though, ⁓ San Francisco, amazing place to be, but I think there's a lot of opportunities in other parts of the States as well that I think that's very interesting to keep exploring. I am definitely eyeing New York as well. So ⁓ that could be like a nice middle ground. Nathan Latka (19:32) Well listen, come explore, come down to Austin, like I'll show you guys around if you wanna come explore, but man, get down here, get in the States so we can just start selling this, selling a CRO agent, selling a CSO agent, selling an AE agent, you know what I mean? If you have the data, you win. It's gotta be the best data though. It has to be the best, cleanest, most contextual data ingestion of anyone on the planet. And if that is true, the rest is history. I mean, this is gonna be a big business. Burak Karakan (19:39) Yeah. Yeah, yeah, yeah. Yeah. Yeah, yeah, well, fingers crossed on that and maybe we'll talk in a year. Nathan Latka (19:57) ⁓ Alright, if people want to follow your story online, where can they find you? Burak Karakan (20:03) LinkedIn is the best place so you can find me at product.com there ⁓ and ⁓ if you ever want to talk about these stuffs feel free to drop me a note. I battle a lot on LinkedIn so get ready to have your feet disturbed a bit. Nathan Latka (20:18) Guys, there you go. Get Bruin.com your new AI data team, your data analyst, et cetera, launched in 2023 been founder led sales so far launched on three core open source models, 5,500 GitHub stars. So very healthy community. They then let people pay per usage as they scale. They already have a customer approaching a hundred thousand dollars per year. So a contract value, most customers paying quote a couple thousand per month. They're about to break. We'll say about to break a million of ARR 15 folks on the team. Very engineering heavy 12 engineering full time did their first round of funding, but now again, really looking to scale or see where they go. Barack, thanks for taking us to the top. Burak Karakan (20:51) Thanks a lot for having me. Thank you, Nathan.