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Andrew Warner: Hey there, freedom Fighters. My name is Andrew Warner.
I’m the founder of Mixergy, where I interview entrepreneurs about how they built their businesses for an audience of ambitious entrepreneurs like me, like you, like today’s [00:00:09] guest. So get this. Imagine you’re running a company and people tell, use the data, right? The data is the answer for everything. But fricking a going and getting the data is [00:00:18] often harder than it seems, and the bigger the company is, the harder the data seems to be.
And so most people will say, okay, we’ll run the data once a month or once a quarter whenever we can. [00:00:27] But to get it on a daily basis, or even frankly instantaneously would be dramatically different for a business. And so that’s what today’s guest set out to [00:00:36] do. He created a company that does that. I met him last Friday and I said, oh, these stories that you’re telling me are killer, we gotta do an interview about how you built it.
His name is [00:00:45] Pavell. Oh wait, let me make sure I’m pronouncing it right.
Pavel Dolezal: Perfect.
Andrew Warner: Pavel Company [00:00:54] is Keboola. They use AI to make data more accessible for more use cases. Pavel you were telling me about that stationary story. That’s a client of yours. Tell the [00:01:03]
Pavel Dolezal: Yeah. Yeah. Hi Andrew, by the
way. Thanks. Thanks for inviting me. You know, mixer is OG of podcast, you know, like, so thanks. Uh.
[00:01:12] Well, uh, the stationary company is actually called me Pen. And uh, the guy who actually runs it, he was working for the large, you know, enterprise and they [00:01:21] kinda like were shutting down the business and he bought, I think one or two shops out of them and then he started to grow them and then he, [00:01:30] he, he knew that he needs to borrow money to grow them. And that he needs data to run them. And he saw that in the enterprise, right? They had a huge team of [00:01:39] dozens and dozens of data people to run the data. He didn’t want that, right? He didn’t want huge team of data people. And his vision was that he’s gonna teach. [00:01:48] clerk, you know, every seller on the floor.
And this is stationary business that they’re gonna, they’re
selling pens, you know, rubber [00:01:57] gums, you know, uh, back to school, you know, items. And that every single person is gonna be a data analyst and it’s gonna contribute to [00:02:06] actually, you know, making business better. Kinda like when you read the stories of Walmart, some
Walton, they would meet every Saturday and they would benchmark who is [00:02:15] selling what, and, and he was like. Now everybody’s gonna do that daily. So he reached out to us, uh, we built a project for him. [00:02:24] We used Kebo to integrate the data. We clean up the data, we set up automation, so it would be always fresh. And then, um, we set up dashboards in the [00:02:33] software called Good Data, and then it was kind of like one o’clock in the morning.
I remember that very vividly because like we gave access to every single employee. [00:02:42] To dashboards. And he calls me like 20 minutes later and he’s like, you fucking sorry,
you
Andrew Warner: let’s do it. Okay.
Pavel Dolezal: I’m like fucking [00:02:51] crazy. This is not how you do it. Immediately turn it off. And I’m like, no, no, no. You wanted data democratization.
He says, yes, but this is anarchy. [00:03:00] If you want to democratize something, this is not how you do it. You need to have a change management plan. So, uh, he actually forced us to lock down the [00:03:09] system and for the first three months. We worked only with him after he started to understand it, get hands on, you know, then we [00:03:18] expanded to his leadership. After his whole leadership started to understand it, we expanded to everybody in the company. Long story short, [00:03:27] the company grew from five, you know, like five uh, locations to over 60 in like three years. And he [00:03:36] didn’t, you know, have any VC capital or anything. He borrowed money from bank, he paid it back.
They went through Corona, they went through Russian invasion of, of, uh, [00:03:45] of Ukraine and the hike in prices, everything profitable. And what they do, this is like, sorry, this is like, you know, [00:03:54] today we have a lot of AI clients. You know, everybody’s crazy about ai, but. Uh, a lot of cool businesses, but this is kinda like the most old school [00:04:03] business in the world.
They sell, you know, pens and papers and every day, you know, the, the, the, it’s mostly older ladies, like 60 plus [00:04:12] who actually sell there. They come to the office, they turn on their computer, which is their BOS system as well. They log into the good data and they see the [00:04:21] data that they sold yesterday and they benchmark with everybody else, right?
So have a leaderboard and what the questions he told them, [00:04:30] question they should ask. So they’re selling so. What would be a good upsell? So like when I’m, you know, when, when, when back to school is coming,[00:04:39]
is the, is it the best to actually upsell the rubber gum or is it best to upsell? You know, can they or whatever.
And they compete with each other and this is[00:04:48]
Andrew Warner: And that’s what, that’s what this up to. The minute data that’s accessible to everyone can do. It means not only that they get to see how these ladies stores are comparing to [00:04:57] others and how they’re doing as salespeople compared to others. They’re also getting insights into, at. At this point in the year, today, if somebody buys this [00:05:06] one thing, they’re more likely to buy the other.
So when you’re selling the one thing, make sure to sell the other. The example you had given me was back to school. When someone comes in to buy a pencil, ask [00:05:15] them if they wanna buy an eraser. And it’s an overly simplistic example, but at scale you’re talking about real impact to their business. That’s what you’re making available.
Pavel Dolezal: and [00:05:24] this, this is saw, saw, saw huge impact, you know, because like you can, you can literally double the profit margin. Just by these simple things. I always, you know, [00:05:33] compare, remember kind of like, it’s like a digging for gold, right? Either you go and you find a big, big nuggets, there’s just a couple of them, [00:05:42] or you have a river and everybody sits alongside the river and they just, you know, like do this and everybody finds a one [00:05:51] small gold flake and a day.
But if you have a thousand people. And they do it every day. It’s more than a big nugget a day. Right? And it’s kinda like what you can [00:06:00] compare the company to. You know, the river is your processes. People are everybody who works there and they’re using data to get insights. And if they
find one flake [00:06:09] every day.
Andrew Warner: Alright, let’s go back a little bit. You ran a huge portal back in the days when portals actually meant something. Portal was like supposed to be the [00:06:18] place where a user would get onto the internet and then from there figure out where to go. It’s a portal called Atlas. You had a problem there that led you to launch this [00:06:27] company.
Um, Atlas was what I, I don’t know, Atlas. I’ve never been on the site before.
Pavel Dolezal: Well, you would know be, yeah, well of course it was a [00:06:36] clone of Yahoo, if you would say
Andrew Warner: It was.
Pavel Dolezal: Yeah. Yeah, of course. Uh,
Andrew Warner: big and famous did you get from it?
Pavel Dolezal: oh, it was, it was for Eastern Europe, so [00:06:45] we were, you know, like, like, uh, very large in Czech, Slovak number one in Ukraine. And so it was like 15 million people using it every single day. We [00:06:54] actually
had, you know, like online maps in 99, you know, like Google Maps was
2004. We had the online maps in 99, but it was [00:07:03] awesome. But honestly, we didn’t know how big it can get, know how, how, how big of a business it can be. And we sold it to Warburg and Pincus, [00:07:12] uh, a couple of years later and
Andrew Warner: The
Pavel Dolezal: of like, yeah, it’s, it’s, yeah.
Andrew Warner: did you get rich from that
Pavel Dolezal: Oh, I didn’t, I had just a couple of percentage, but, [00:07:21] but my, my, my friends who actually started there with me, they, they got, yeah.
Andrew Warner: because you were the chief product manager at the time? Not the
Pavel Dolezal: yes, yes.
Andrew Warner: [00:07:30] Okay. Um, and then right
Pavel Dolezal: I joined, I joined, I joined two weeks late.
Andrew Warner: Seriously.
Pavel Dolezal: Yes. Seriously?
Yeah. [00:07:39]
Andrew Warner: All right. And the problem you had there, and I know you’ve launched a few companies after that too. The problem though that you had there was what?
Pavel Dolezal: Well, it was always, you know, uh, I launched a [00:07:48] couple of companies and they were all using data and machine learning to actually automate processes. And the problem with
Atlas was like 15 million people are doing [00:07:57] some searches like, like in Google today. And I needed to understand what do they search for, you know, like, and it took me like half a year, you know, to, to get [00:08:06] engineers to build this view for me and to get all the data together.
So I would not. You know, like bring down the systems, right? And so when I saw this [00:08:15] the same problem, exactly the same problem in three different companies I built, I was like, it’s time to change it. And when the cloud started [00:08:24] and the whole SaaS industry started the proliferation of, you know, SaaS, you know, data sources, it was just bigger and bigger problem.
So I was like, this needs to get [00:08:33] changed. Yeah.
Andrew Warner: I am surprised. I get it. You’re talking about with Atlas 1998 is when the company was running. You were there till [00:08:42] 2002. Okay. So back then, getting any kind of data was hard. Right. But you’d had other companies since then we’re talking about, what was the company that you [00:08:51] had just before this one? You were, uh, at Net Mail to 2019.
Pavel Dolezal: Yeah,
yeah,
yeah. But
Andrew Warner: data was still too hard for you to get?
Pavel Dolezal: [00:09:00] Oh yeah, it started to be even harder. Or like, I thought that when the cloud started, you know, it would be like, okay, but remember [00:09:09] 2020 to 2012, you know, uh, it was, um, the nobody knew Snowflake. It didn’t exist. Uh, [00:09:18] and so the defacto standard of data was Hadoop technology.
It was built by engineers for engineers. It was originally started, uh, [00:09:27] off of the white paper from Google. Then, you know, like Yahoo and Facebook started that. And, uh, it was Apache uh, project. It was like so [00:09:36] freakishly hard to do anything, so it started to be even harder. And so when I got together with my co-founders, we are like, they, they saw the same problem from the [00:09:45] consultancy, you know? They had a small consultant say, you know, doing it
projects, and then more and more people wanted this data, you know, and so they started to [00:09:54] build it together and they saw it. And so we started to actually get together. We were like, Hey, what’s gonna change in next years? We were like, well, there’s gonna be, [00:10:03] you know, somebody’s gonna figure out the, the database problem. It’s not gonna be Hadoop, it’s, we are gonna go back to CCO and of, and it’s not gonna be one [00:10:12] backend, it’s gonna be multiple backends. So yes, now we have Redshifts S flag, uh, BigQuery, Doug DB Iceberg, you name it. You know, [00:10:21] there is, there is like end endless T for of backends, right? And then we were like, well there’s gonna be, we see this SaaS businesses, you know, [00:10:30] taking off and there’s gonna be, you know, like proliferation of SaaS businesses within the enterprise. Guess what Gartner says that there is up to [00:10:39] 300 different SaaS tools in the enterprise business 300. You know how hard it’s to get data from two [00:10:48] sources, just like 303rd one.
What?
Andrew Warner: look, the problem you’re saying, just to catch up on what you’re saying right now, you’re saying, look, [00:10:57] the problem is that there’s that. First of all, the people who are stor, the software that’s holding onto data is not meant to be user accessible. So most people don’t have [00:11:06] access to it, and that’s something that’s always bothered you.
Everybody should have access to data, number one. And the second, the second issue that you said is there’s also now, in [00:11:15] addition to these data warehousing, uh, tools, there’s also hundreds of other SaaS, uh, apps that people are using and the data is stored within there. So [00:11:24] yes, it’s getting, uh, it should be getting easier, but it’s actually harder because of all those, and then you had a third reason.
What’s the third one?
Pavel Dolezal: Yeah. And it, it, and the third reason was exactly, it should not be a magic, [00:11:33] you know, it, you, you, you should not be a part of Voodoo clan that knows how to sequel or Python. You know, like this is a business problem. [00:11:42] So, uh, you as a person, tech savvy, tech savvy person in the business should be able to handle all of your questions, you know, and automations [00:11:51] yourself. Right. So that was our North Star. So that’s why we built Keboola as an API first, you know, so we can abstract from the [00:12:00] technologies and change them on, on, you know, under the hood as they evolve. And B, we were hoping for something like LLMs to come, you know, to come out, you [00:12:09] know, like very early on. It took us seven plus years, you know?
So we were ready, you know, for LMS back in 2016. And we’re like, there’s gonna be [00:12:18] something that’s gonna help us to write these SQL Python queries. You know? So the user can just work in natural language. Yes. That happened seven years
[00:12:27] later.
Andrew Warner: By the way, you said not just get data accessible, but also do something. One of the discoveries that I’ve had over the last week when I’ve talked to different AI companies is [00:12:36] they’re much less excited about the agent thing than they are about the make data more accessible. So every time I talk to them, I want [00:12:45] them to tell me about how AI will, will magically do a thing for me.
And they say, no, no, Andrew, uh, like this company, hi. He goes. Real [00:12:54] estate, uh, brokers have data in all these different places. They can’t access it. So what they do is they text someone on the team and they go, can you tell me? And [00:13:03] that’s a waste of time, and it takes forever to get the answer. So he goes, what we created was a text that you can, that you, you know, like a, a almost like a person on text.
You text this number, [00:13:12] you ask your question, you get an answer instantly, and we pull the data faster than anyone else. And he goes, that’s the exciting part. It’s not what we could do with the data. It’s can we actually make it accessible? And you’re smiling the [00:13:21] same way.
Pavel Dolezal: Well, because that’s the first problem. If you can, like, uh, you know, for us, this has been known problem for years. So, uh, it’s a [00:13:30] hurdle. You know, like you see all these nice demos with agents and everybody. You know, but like, if you look under the hood, what they’re actually doing, they’re, you know, using [00:13:39] Excel or Google spreadsheet and maybe Google Calendar, right?
It’s easy. But you know, in the reality is, is these guys, you know, we’re telling you most of the [00:13:48] interesting data is slot in the proprietary systems or, you know, specific SA systems, or they might have Salesforce with a [00:13:57] different implementation, right? So that’s hard and that’s not sexy. You know, it’s kind of like plumbing, but like once you actually [00:14:06] unlock it and like what we do, you know, automate the data pipelines, they would run for eight years, 10 years.
Like, you know, there is a company, uh uh, [00:14:15] uh, uh, DXC, right? Like, like $16 billion a year company, you know, the original IT company. And they use [00:14:24] us, you know, to run all their sales and marketing data pipelines around the globe for last eight years. It just runs. [00:14:33] Right, so you automatically get the data accessible.
Once you have that, you can start building those interesting use cases and you can then start automated processes with [00:14:42] it. But unless you have, you know, data accessible, no magic ai.
Andrew Warner: The other thing that’s interesting is, first of all that you’re saying, first we make data [00:14:51] accessible. Then we act on that data. There’s like an earlier step that I’m noticing come up O over and over, which is. Consulting that as a [00:15:00] consultant, not a software vendor, not a SaaS maker. Those things are sexier, but as a consultant, you get to go in, you have deep understanding of what the customer needs.
You do [00:15:09] it a lot by hand, and then eventually you create software that systemize it. You’re smiling. Take me through the early part of the business when Kabbah did that.
Pavel Dolezal: [00:15:18] Well this is how we started. Uh uh, so my co-founders. Actually, uh, had the consulting business right. Uh, they would be deploying [00:15:27] their engineers. You know, before we all knew forward deploy engineering was a thing. Uh, uh, and just like consulting with clients, I building the [00:15:36] data, accessibility automations, insights for them. And so I came from the second angle. I was the, the owner of the business, you know, I had the issue. [00:15:45] And so together, uh, we started to go around different clients and we did implementations ourself. And by that we actually [00:15:54] learned what are the hard problems, right? And that’s how we started to build people. And that’s the principle we keep, you know, up to today [00:16:03] we have, you know, a couple of clients where we actually do implementations ourselves and we actually learn and we co-design with them. One of the [00:16:12] examples is one of the fastest growing unicorns in Europe, which is called uh, raw group. You know, they do grocery deliveries within one [00:16:21] hour. You know, like, kind of like imagine Amazon Fresh actually working that’s raw in Europe, you know, like everybody’s so used to it, you know? And so [00:16:30] we are designing things together, you know, to, because like, it makes sense
honestly, if I
Andrew Warner: of the early days when you were just consulting or your partners were just [00:16:39] consulting. Gimme an example of a project that was done that then led to a software understanding that that led to something that’s usable by other clients.[00:16:48]
Pavel Dolezal: Yeah, so, so actually I, I will use the group because like the guy who started that is, this is his third company and the first one was the [00:16:57] Groupon clone for, you know, six countries in Europe, which was actually very successful and profitable, by the way. Interesting side note, [00:17:06] Groupon as a original Groupon is now run by checks as well. You know, some of our friends and client is our client actually.
Have bought in as a [00:17:15] private equity. Yeah. Yeah. I have redesigned the whole Groupon and data using ula. It’s, it’s a great story, you know, and they are, they are awesome team, how they are actually [00:17:24] executing. But going back to Thomas Tuper is his name.
When he started his first company, it was called slo. And, uh, he, he, like, we found [00:17:33] him on Twitter, honestly, one late night, you know, um, he was tweeting was like again, 2:00 AM it’s a magical number, you know, like between midnight and 2:00 AM [00:17:42] things happen with founders. And he was like, I’m starting this company.
Uh, I have my database. I have a real problem. It’s a MySQL database, and what I need, you know, I [00:17:51] need to connect my sales reports. I need to connect this and this. I don’t know how to do it. It’s like so hard. So we immediately, my co-founder reach out to him. Um, next [00:18:00] morning we were on site and we start to discuss, and he helped us to co-design, you know, because he’s very tech savvy. He’s very business kinda [00:18:09] magician. This guy’s incredible. And uh, you know, he’s forward technologically, you know, he likes technologies. So together we [00:18:18] designed that, you know, needs to be API first. Right? So that abstraction layer I was talking about that started with to
Andrew Warner: Meaning he told you just do API, [00:18:27] meaning just suck data in from, from other API
Pavel Dolezal: he, he didn’t tell us, just do
API, but he, he started like, how do you want to use it? Well have these, you know, [00:18:36] sources that always change. And then we took it back to our team, right? And we’re like, Hey, we need to have an abstraction there. That’s, that’s obvious, right? And so, uh, and then [00:18:45] he was like, well, I can’t, I know how to run the database. I don’t want to do it because like, you know, like it’s just.
Too much effort. I want just insights. [00:18:54] So we start to run database underneath Keboola. Right? And so like these design principles, we literally started with him as a, as [00:19:03] a client. And then he used us in three other companies. ’cause we designed together, right?[00:19:12]
Andrew Warner: All right. I get that. I see it. Now let’s talk about some of the challenges. So you built the business, then Corona hits, right? [00:19:21] COVID-19. What happens to the business as you’re building it?
Pavel Dolezal: Uh, yeah. So before, before Corona, we were, this is my, [00:19:30] I think, third or fourth company, and we wanted to be bootstrapped, you know, in the beginning so we could do what we wanted to do. We had this vision, we knew it’s gonna take a couple of years. [00:19:39] And we wanted to that. So, uh, we start a business, uh, we start to grow business pretty successful. Uh, I moved to us in [00:19:48] 2019 and then, you know, we start growing in Chicago and Corona hits. So I need to stay in Europe. Uh, honestly, we, [00:19:57] we need to, you know, like nobody knew what’s kind of going, going on. We need to lay off people in, in US because like we didn’t have money, you know, to pay them. We need to [00:20:06] refocus and, uh. I dunno if you remember, but like in the beginning of Corona, the, the original or the first, you know, like death in [00:20:15] Italy there was a, there was a mortality rate around 5%. That essentially means like that. That’s why there was such a panic in the beginning. [00:20:24] Um, that means that it would wipe out the population within a year or whatever, right?
And so we’re like, well. Okay, business is good, [00:20:33] but we should help now. Now it’s kinda like time. How to help techno use technology to, to, to actually, to actually help the governments and people. And [00:20:42] so we put out on Twitter again, Hey, check government, do you want help? And before you know it, you know, six hours later we are actually, [00:20:51] you know, with the Prime Minister and the whole cabinet and they’re like, we don’t know what to do.
You know, this is kind of like a. Technology could play and you know, contact [00:21:00] tracing and everything, how to connect the data. And so we are like, yeah, we can, I help you. We can integrate the data. And so we did. But then it was like more and more the [00:21:09] governments were like totally not ready for anything. So we actually built a group of enthusiast, you know, technological enthusiasts, 5,000 people, [00:21:18] 5,000 software engineers, and they started to help. Well that sounds great. The only two issues was that, uh. Uh, we [00:21:27] started to help with one thing, but then we started to see that they need more and more. And then we started to run, you know, with couple of friends, part of that [00:21:36] government program for the government. And it, we couldn’t get off because if we would get out, it would just collapse. And [00:21:45] so we almost lost the business, uh, because like in the times where every, you know, like tech company was selling and selling and selling. We were focusing [00:21:54] on, you know, like pro bono work and the, it was great. If you, if you, if you look at the stats in the first wave of Corona, Czech Republic was best in the world. [00:22:03] But then, uh, the government people, you know, they are not really, yeah, it’s a strange, uh, I would [00:22:12] not want to work with government ever more, you know, just like it sucked us in so much we’re trying to change that system. And [00:22:21] after almost half year, we had to say, stop, you know, like, our company’s like almost going down
and we are helping someone who doesn’t want to [00:22:30] help.
So we went back. We actually, it was, it was, it helped us in a way that we actually started the PLG motion, which we didn’t have [00:22:39] before. Uh, and since then, over 21,000 companies actually sign up for us PLG Motion. We grew it. We started to grow [00:22:48] it, you know, and now like last 12 months we grew it three times. So like there’s, you can always get something from crisis, I think. [00:22:57] But yeah, there’s so many crisis building the company that you need to make sure that they don’t kill you, right? And you need to have at least plan B [00:23:06] and C and everybody says go in, you know, for all. I think that’s a great advice if it works out.
Andrew Warner: Was the government [00:23:15] grateful for all those that you’d given up for them?
Pavel Dolezal: No,
Andrew Warner: No.
Pavel Dolezal: like it was like, um, uh, and we knew it. Um, like half [00:23:24] year later we would, there would be great articles, how we fucked up everything and you know, like,
yeah,
Andrew Warner: Uh, and did you get those articles about how you screwed everything [00:23:33] up?
Pavel Dolezal: Yeah. There are online somewhere you can, it’s just
like, you know, like there was 5,000 people involved in engineers.
Um,
so, [00:23:42] uh,
Andrew Warner: You said that it helped you get to PLG product led LED growth. What do you mean? I, it seems like you’re completely in, in [00:23:51] software, but I mean you’re, it seems like you were completely in the other direction then.
Pavel Dolezal: Is that we have, we have two legs, you know, like, like, like a human being, two legs. They need [00:24:00] to walk in the same rhythm, the same direction. So, uh. One. Uh, originally we started just like, like, [00:24:09] uh, we, we didn’t have sales originally. Uh, so we started just word of mouth and people recommending us. And you couldn’t actually start keah [00:24:18] online.
You had to talk to someone. We had to start for you. Uh, uh, and then, uh, when when after Corona we’re [00:24:27] like, well, it’s great that we are getting these bigger clients. How are we gonna work with us? You know, like. We don’t have money now to invest, to go [00:24:36] back to us physically. So how are we gonna work with that? So we’re like, well there is this PLG motion that people seem to do well. And so [00:24:45] like, like we were like lowered our, our principle was lowering down the barriers for people to actually start using ki, right?
So, Uh [00:24:54] we started like free account. We now have very, very, very generous free and where people can actually run their businesses on that. [00:25:03] Um, we’re like, well, this is our way to, to go back to us because like, I don’t need to be there for, to target people who are there.
Right. So, [00:25:12] and, and then it started to take off and it’s a, it’s actually, I, I think it’s a, the world has changed, you know, after Corona, you know, I don’t think that people are [00:25:21] buying now just, you know, like by phone only or introductions or reference. Always, especially in our industry, there will be some one technical [00:25:30] who will want to try the software. Right. So that’s kinda like even when we sell, you know, our, and our, our tickets are, are, you [00:25:39] know, like mid, mid, mid tickets are 75 to 150 k, you know, as a starting ticket. Uh, we still have, we still have, you know, like hundreds and [00:25:48] hundreds of companies that pay us, that pay us by credit card. Just like $20, $50 and they grow, right? Or that there is, uh, [00:25:57] thousands of people every, every, you know, quarter joining who want to try it, and then you can trace them to the companies that we actually do outreach to.[00:26:06]
Andrew Warner: I see. Let’s talk about an a bigger customer that you got you. You had this shocking story about how you got a bank to buy from [00:26:15] you because you couldn’t get them to work with you. Why couldn’t you get the bank to work with you?
Pavel Dolezal: Well, uh, imagine, right? Uh, banks are one [00:26:24] of the most regulated industries, especially in Europe, right? All the GDPR and things we invented that as Europeans. You know, bureaucracies are thing, right? [00:26:33] And so, uh, I don’t think there is a harder customer to work with than a bank. But as well, you know, [00:26:42] banks are great customers because everybody knows them. Right. And they have great use cases, you know, re especially retail banks, you know, so right now we are working [00:26:51] with the Erta bank and, and, and we are in over 85 departments. There’s, there’s hundreds of people that use us in 85 departments, [00:27:00] but that took us almost 10 years to get there. So when we first started, I was like, I want to have this bank as a customer, right?
It’s a very [00:27:09] well known brand in Europe and et cetera. But. Like you, you don’t get them as a customer like this, right?
So we’re like, what [00:27:18] can, they don’t typically buy from startups. Um, they’re very risk aware. You know, they’re, uh, they have so much regulation, so [00:27:27] much to lose that their first principle is not to innovate as much as
possible. Their first principle is kinda like, Hey, like do it securely. We are a bank. [00:27:36] We, we actually work with people money, so we need to be secure and, uh, yeah. So, but there was a trend of cloud [00:27:45] cloudification. So I, I knew this bank from the company I invested in net mail and I was like, this is a great customer, but they will not buy from us [00:27:54] for a couple of years. So what we did, we actually approached them. We, we started to do community hackathons because like we wanted to get people excited about [00:28:03] data. We wanted to show our platform, um, and we wanted, we were hoping to get, you know, customers out of them. So we approached the bank with, you know, like the, [00:28:12] the prospect of doing a hackathon. And so we used their data, we anonymized the data, and together we did the hackathon for over 500 [00:28:21] people. AWS was sponsoring, IBM was there, Google was there. Everybody took like four days, three new companies were started out of the hackathon [00:28:30] and it was, it was just amazing. So we established the relationship and then, you know, we worked with them for a couple of more years, two, three years [00:28:39] to actually, you know, really work with them, do proof of value to show them, you know, then we did a lot of, lot of security and finally in. [00:28:48] 2019, they signed the first deal. So ex, exactly When Corona hit, you know, we were starting the first implementation there.[00:28:57]
Andrew Warner: When you got those, that many people to participate in a hackathon, how did you get them?
Pavel Dolezal: Well just [00:29:06] really being active in the community, so, well, first being active in the community. So we did a lot of blog posts, Twitter, [00:29:15] uh, back in the day. And then we start actually. Uh, to, to work with other people. Like before Corona, the meetup.com was actually a [00:29:24] very active website. Now it’s not as
much, right? So there would be people with different groups, and we found out that they would have one thing, they would have some [00:29:33] audience, but they would not have enough content. Right. So what we started to do, like, and before Corona, we, we actually ran a, a, a [00:29:42] London data enthusiast, uh, uh, group as well in London with several thousand people there.
And like every two weeks I think we would have, we would have, we would’ve [00:29:51] an event, you know, there would be like 150 people like looker.com when they launched in, in, in uk the guys actually came. To launch at our, you know, [00:30:00] like at our meetup. It was awesome, but, so that’s, we would, we would collaborate, uh, cooperate with people who would have their small groups, [00:30:09] but they would not have content. And we found out that, uh, it’s very hard for people to get content and to organize. So we’re like, okay, [00:30:18] everybody has small audience. Let’s combine together. We will organize, we will do the content, we will prepare the data, we will do use cases, we’ll moderate. It [00:30:27] turned out pretty well. We’ve done this several times, the huge hackathons, and then we were like, well, this takes half a year to prepare.
Right? Great data hackathon takes a lot of [00:30:36] time. So we were looking for a small concept. And, uh, uh, which would be repeatable. Uh uh, we got together with the, back in the [00:30:45] day, 2015, 16, there was a big, uh, uh, it was a big women in tech movement.
And so, uh, we got together with one of the groups, check [00:30:54] it girls, and, uh, and we started, Hey, you don’t do data.
They’re like, yeah, we would love to do data content. So we, we design, you know, a specific [00:31:03] workshop with them. And since then, you know, like. It’s been, it’s been taught to over 30,000 ladies and it actually evolved into, into an [00:31:12] academy, which, which tried to be sponsored by Google three months program Yeah.
And stuff
Andrew Warner: heard in your bootstrapping
Pavel Dolezal: great to work with community.
Andrew Warner: I heard in [00:31:21] your bootstrapping days these types of community things and hackathons ended up being your Salesforce.
Pavel Dolezal: Yeah,
definitely. Uh, [00:31:30] honestly, they would
Andrew Warner: I.
Pavel Dolezal: like, people would invite other people. So, um, like the participants [00:31:39] are our, our North Star for Good Hackathon was not a number of new clients. I remember our CFO back in the day. She was [00:31:48] like, I need to understand what is the ROI ON on these activities. I’m like, we don’t know. Like, how can you do Then like, uh, we, [00:31:57] we, we have a theory or hypothesis
and we are ready to, you know, put all of our effort in it. And just like either prove it or [00:32:06] disprove it. And, but we will, it’ll, it will take us half a year to understand. Right. And it’s okay with us. And so, uh, the guiding principle [00:32:15] was to provide the value for people to provide the value for community.
People would be inviting people, other people to actually build their use cases [00:32:24] at the hackathons. Right. So it was kinda like proof of value done on site. And that’s just how people start to invite other people, you know,
because, and then we
Andrew Warner: [00:32:33] was, I, I’m gonna make a useful event when the people want to come. If they come, they might bring their, their friends, and then all those people will get to know we’re [00:32:42] doing a Keboola, but not necessarily sign up right away.
Pavel Dolezal: Yes.
And, uh, yeah, I, uh, our, also, our guiding principle was, [00:32:51] uh, we are not gonna do prizes because what happens with hackathons, when you do prizes, you have a professional hackathon, hunter. [00:33:00] And they go and just swoop in. You know, they take the price there and they go off. That’s no fun.
Right
So like, no [00:33:09] prices, well actually we would’ve a price like ham, right?
Like Spanish ham, you know,
like big, big chunk of ham, uh, or, or something like that. And, [00:33:18] uh, that, that, that was that, that still working pretty well, you know?
Andrew Warner: What’s the revenue for the business now?
Pavel Dolezal: We are [00:33:27] approaching 50 million a RR. Yeah.
Andrew Warner: 1 5 15.
Pavel Dolezal: Yeah. One five.
Andrew Warner: Wow. You went bootstrapping for so long with all these different ideas. [00:33:36] Why did you decide to take some money a few years ago?
Pavel Dolezal: Uh,
for scale. Uh, it’s like we saw with Corona, uh, that [00:33:45] one big, you know, black swan event, what it can do to us, right. And, uh. When [00:33:54] we saw in 2022, uh, that what, what Transformers did with the GPT, right? And how it’s kinda [00:34:03] like our vision that finally there will be something that can help us with the data and, um, that these two things, we unlock the [00:34:12] data potential, make it accessible and there is the second part, which can actually make it easy to talk to that data, right. [00:34:21] We were like, wow, this is, this is now. Right? And so like, well, we had a huge discussion, honestly. Um, it took [00:34:30] almost a year internally. So are we gonna lose our freedom? You know, like, uh, you know, or are, are we, do we want to, [00:34:39] you know, like that as many, like our mission is actually to automate every single business process with data and AI that’s [00:34:48] been for almost
over
Andrew Warner: even to make it accessible, it’s to get to that automation point.
Pavel Dolezal: Yes.
The accessibility is the [00:34:57] prerequisite for it.
That’s what we identified as the hardest, you know, like thing. And, and that’s where people fail. But only [00:35:06] coupled with that ai it can actually, it can make it accessible. People can get insights, right? And by getting insights, they can run their [00:35:15] businesses better. And, but then what they want to do, they want to use the same data. The same data, right? The same systems. To [00:35:24] actually automate their businesses. And so that’s what we saw with, you know, ai, that it can actually have that potential and we [00:35:33] analyze that. We need more capital for that. Right? And so, uh, and you know, a year and a half later, that vision is actually, you know, [00:35:42] coming together because like right now, uh, with our systems, you can start with the question. You know, like, then, you know, the systems, the [00:35:51] LM systems actually help you with actually defining what data you need. Like, oh, I have a, I have my, you know, like, let’s say we will be Mac Pen running on Shopify, [00:36:00] right? I have my stationary business. I want to see which customers have not bought from me in not last 90 days,
right?
You input it [00:36:09] in, it says, well, you need the data, uh, from your POS system. Oh, I’m using Shopify. And Keboola helps you in one click to integrate the data and it says, where do [00:36:18] you have your store? You know, like Warehouse, you know, in this system like Ship Mon or IT Help Keah helps you in one click to integrate it, but then LMS [00:36:27] help you to join it together.
You know, the auto magic, right? And then you can get the answer, but that doesn’t end there. Then people are, [00:36:36] okay, interesting. Now I want to send it, you know, to to, to something like Brace for Audience, you know, like, uh, like, um, automation. And then [00:36:45] people are like, okay, now I want to run this every day. So that’s when you build the agent, right?
That’s when you build the [00:36:54] agent, not, not before. That’s kind like putting the horse. In front of the cart, in front of the horse because first you need to understand what are you [00:37:03] solving, what is the process, and only then you can build the agent and you need to have data. You need to have quality data, you need to do, do QA on the data, and you need to [00:37:12] run the automations.
So that’s
why most
Andrew Warner: before you run, before you run the automations, you need human beings to do it, to teach you what needs to get done, or [00:37:21] is that not necessary?
Pavel Dolezal: Yeah, before you run the automations, you know, like, like with systems like us, you actually [00:37:30] like the human beings. Like Yeah. Like think about it. How do you get to describing the process? Either, uh, you have the, you have some advisor [00:37:39] or McKensey guy coming in, analyzing the system and analyzing the process. Uh, and then saying, this is it, this is this, you know, goes with [00:37:48] huge project. The hard thing is business people don’t usually understand how their processes work, right? So what we are trying to do, [00:37:57] or what we are doing, we’re trying to do, we are flipping that. People are very good in asking questions. So like, who doesn’t buy from me?
Why? Right. [00:38:06] And then, okay, I want to reactivate them. This is the tool I’m using. Right. And by the time you’ve done this, [00:38:15] you know, you actually describe the whole process,
right? You, you’ve done the work of McKenzie guy. Without actually knowing that. And if you [00:38:24] have the system, you know, like Keah, which actually, you know, keep trail of everything you’ve done, kinda like in that conversation, all the metadata, it’s [00:38:33] so easy for us to recreate that system back, that process back. And we tell you, this is the data you need to hear and, and here it’ll go here. This is how it’s gonna [00:38:42] transform. Boom. Run.
Andrew Warner: And the boom run is, I, I now understand who has bought for me before, but hasn’t bought for [00:38:51] me in six months. I know why they didn’t buy. I know what I should do. And then instead of me doing it, I tell the, the agent to do it and the agent might write an email that [00:39:00] says, we’ve got this 15% discount on this thing that’s very related to what you bought a few months ago.
That’s, that’s where you’re going.
Pavel Dolezal: I would just say like we, we pair it [00:39:09] with different systems. It’s not all, we are the underlying automation for the data. Right? But then you need, but you know, at the end [00:39:18] sometimes, you know, like, you might even know that you need those systems or you don’t even lock, you don’t lock into the brace, right?
You just send the audience there and other agent, you know, like [00:39:27] actually activates that. But I’m just saying agents are not, not the last thing. I, I love agents. I think it’s a huge, huge feature. But I mean, like [00:39:36] the big problem is to get a data accessible and b, describe the process. Right? So we turn it [00:39:45] around.
Andrew Warner: But you raised your money in June of 2022. How much did you build by then? You had profits by [00:39:54] then. You had a clear product by then, right?
Pavel Dolezal: So we, we, we raised a seed round in, in June 22. And [00:40:03] by then we had a company, we, we had, uh, if I’m correct, something three, 3.54 million, uh, dollars. [00:40:12] Uh, you know, like, like until then we were running the company to be profitable because like, you know, like we were bootstrapping
or cashflow positive, you know, depending on the year. [00:40:21] Um, um, yeah, and that, that’s what we had kinda like, and we had the basic platform, right. And it was, it was, it was very well, it was very well, uh, it was very well, you know, [00:40:30] like tried by, by dozens of, uh, by, by dozens of customers. And we’re like, okay, time to scale.
Andrew Warner: And it also had LLM in it, like it was, you were already there.
Pavel Dolezal: [00:40:39] Not yet.
Yeah, yeah. We were, no, back then in June 22, no. We were using, uh, back in that summer, we actually wrote the first [00:40:48] integrations for GPTs, GPT was acting one something
and you could run a query, you know, to GPT through our [00:40:57] orchestration. So, but you know what, you know what? Nobody wanted to use it. Nobody. It was
like, I, I like.
Andrew Warner: this was months before [00:41:06] chat, GPT came out and like literally months before chat, GPT came out, you guys raised June, 2022. November, 2022. OpenAI [00:41:15] came out with chat, GPT. People started to understand what this could do. They got to play with it and suddenly, I’m imagining things took off for you there.
Pavel Dolezal: [00:41:24] Yeah, that’s pretty much, that’s pretty much the story. Yeah. That’s, that’s kind of like, uh, it, it actually, it didn’t, it didn’t go that fast, you know? Uh, it took [00:41:33] people one more year, uh. To start actually running the AI powered automations. So we have clients like Jim Beam, you [00:41:42] know, like not gym like Jim Beam, like drink, but Jim as a gymnasium, you know, fit company.
They are in 16, 16 countries, 16
1 6. [00:41:51] And uh, they went from zero to over 300 million. Uh, you know, like, uh, uh, a revenue bootstrapped. Um, [00:42:00] um, awesome guys. Um, everything is run on data. They use Sula as their operating system to get all of the data, everything. And so last [00:42:09] year, uh, they were one of the first adopters of LMS in the process automation. What they did, they had a 50 50, a 50 people [00:42:18] team. With the, the support, uh, user support, like content support, and their biggest problem, like, like people give them reviews in 16 languages [00:42:27] everywhere, right? Uh, one of their biggest issues was that, uh, people would, you know, actually spam them. So the competitors would span their reviews. [00:42:36] So they use Keboola, they use, you know, chatGPT within their, you know, workflow. Kula automated that. And so we get the data from reviews. [00:42:45] You know, we, you know, like normalize in Keah, they, you know, ran JGPT from Keah it, you know, analyzed the data and then actually wrote [00:42:54] the responses and then again, run it through Keboola.
And at the end, you know, they would have, they would have a human in the loop interface where people would say yes, [00:43:03] no, yes, no, or rewrite. They would go from 50 people down to three people.
Andrew Warner: Wow.
Pavel Dolezal: that’s, that’s magic.[00:43:12]
But it’s not magic. Like you need to be part of a secret cult. You know? This is accessibility to everyone.
That’s, that’s my goal.
Andrew Warner: Okay. Let me ask you this to close [00:43:21] it out. If someone were looking to start an AI company today and didn’t have your technical know-how, I wanna know what some of the opportunities are. What do you [00:43:30] see? If you’re looking out and you’re saying, here’s the opportunity, go run this. What are some of those ideas?
Pavel Dolezal: Honestly, uh, I’ve helped, [00:43:39] uh, you know, like. Hate it or love it. I think the vibe coding is like a huge, huge opportunity. I’ve helped literally dozens of [00:43:48] people this share to actually start their own companies and it always goes like this. Oh, uh, like this guy, I don’t, I’m actually working for [00:43:57] non-profits.
You know, like, we don’t get too much money, but like. We have this issue, you know, like we don’t know what grants are being done. When, you know, and the old [00:44:06] systems are too clunky. I know exactly what to do, I just dunno how to code it. Well, I teach him, you know, I show him lovable. I show him courser [00:44:15] and like, literally, you know what, over Sunday he builds an MVP and on Monday he goes and he shows it, you know, like in, in some, in some [00:44:24] convention to to to other nonprofits.
And he literally on the spot gets. 10 people to sign up that they will pay for it. [00:44:33] And, and so, you know, like I think the, if you don’t know, if you don’t have technical, uh, things, what is your, what is your actual secret? Is your [00:44:42] vertical knowledge,
you know? And that, that’s, that’s, that’s, that’s the thing, you know. Coding, uh, at, at least to MVP, not production, but MVP is [00:44:51] like now easy and anybody can go
and just like prototype what they want to build and they can sell it. You know, I have literally [00:45:00] next to me, I, I, like, I have two friends who built businesses over last year. One of them is now 10 million a RR, 10 million. One person, [00:45:09] white coding app. And the second one is, is do is doing 3 million. You know, and just like time is [00:45:18] now, honestly.
Andrew Warner: Would you introduce me to them so I could do interviews with them?
Pavel Dolezal: Yeah, of course. Very
happy. Yeah, Yeah, Yeah. I would
WhatsApp. Yeah,
Andrew Warner: Hell yeah. I would love to [00:45:27] do a series of interviews with people who were inspired by what you’ve told them and then ended up building businesses that couldn’t have been done before.
Pavel Dolezal: yeah, yeah.
Andrew Warner: Alright. [00:45:36] Thanks so much for doing this.
Um, I’m excited to get to know you better. I love that we’re now on what I, dude, I hated WhatsApp, but now the more I’m talking to [00:45:45] people outside of the US and especially in this world of AI and and agencies, the more I’m on WhatsApp living there.
Pavel Dolezal: Uh, it’s kind of like addictive, [00:45:54] right? Or like, yeah, but, and then, but go WhatsApp, telegram, you know, signal and it’s just like, but yeah, I don’t know how I would be living [00:46:03] without it actually now.
Andrew Warner: Me neither. All right. Hell yeah. keboola.com. Thank you. Bye everyone.
Pavel Dolezal: Thank you, Andrew.