How AI Is Disrupting Industrial Tech | Visionaries Club VC Insights - video Dailymotion

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How AI Is Disrupting Industrial Tech | Visionaries Club VC Insights  AI is disrupting traditional SaaS — and Europe's industrial tech giants are finally listening. In this episode of Startuprad.io, we explore how applied AI in B2B is transforming procurement, logistics, and manufacturing, and why industrial tech innovation may crown the next wave of unicorns in the DACH region.  🎙️ Guest: Marton Sarkadi Nagy, Partner at Visionaries Club, a Berlin-based VC with €600M+ AUM and a unique LP base of unicorn founders and legacy industrialists.  💡 What You’ll Learn:  Why traditional SaaS is dying and how agentic AI is redefining B2B software  How Visionaries Club blends legacy and innovation to spot top founders  What makes a “genre-defining founder” (hint: urgency, obsession, execution)  Europe's edge in the application layer of AI  Radical accountability and how top founders handle crisis  Learn more here: https://www.startuprad.io/post/how-europe-s-visionaries-are-using-ai-to-disrupt-industrial-tech   🔗 Listen to the Podcast Anywhere: Spotify: https://open.spotify.com/show/1O2dpN9cUU6F9tS5Ocvc8P Apple Podcasts: https://podcasts.apple.com/us/podcast/startuprad-io-startup-podcast-from-germany/id690941914 Castbox: https://castbox.fm/channel/id1140079 Goodpods: https://goodpods.com/podcasts/startupradio-startup-podcast-from-germany-24813  The music used in our intro is "MF-297 : First Hero" licensed from Musicfox.com: https://www.musicfox.com/detailsuche/?searchtext=297&submit=search   ⚠️DISCLAIMER: We do not accept any liability for any loss or damage incurred from you acting or not acting as a result of watching any of our publications. You acknowledge that you use the information we provide at your own risk. Do your research.   Copyright Notice: This video and our YouTube channel contain dialogue,  and images that are the property of Startuprad.io. You are authorized to share the video link and channel and embed this video in your website or others as long as a link back to our YouTube channel is provided.   © Startuprad.io - All rights reserved  Chapters: 00:00:00 The Future of Venture Capital and Applied AI in Europe 00:00:26 Introduction to Martin  00:02:12 Journey from Operator to Investor  00:07:00 Understanding Radical Accountability  00:08:57 Market Insights and Investment Thesis  00:12:22 The Unique Base of Visionaries Club  00:15:52 Identifying Bullish Sectors  00:19:18 Europe's Position in AI Application  00:22:00 Rethinking Company Structures for AI  00:28:19 Evaluating Founders: Traits of Success  00:33:24 Painkillers vs. Vitamins in Startups  00:37:46 The Influence of Competitive Sports  00:40:21 AI's Impact on SaaS Adoption  00:44:33 Connecting Startups with Industrial Partners  00:47:45 Challenges for European Founders  00:50:57 Adapting European VCs for Global Competition

Transcript

00:00Welcome to StartupRad.io, your podcast and YouTube blog covering the German startup scene with news, interviews, and live events.

00:19Hello and welcome, everybody.

00:22This is Joe from StartupRad.io, your startup podcast and YouTube blog from Germany, Austria, and Switzerland.

00:27And today I do have Martin here with me. Hey, how are you doing?

00:31Hi, great to be here.

00:33Totally my pleasure.

00:35I usually give a little introduction about the guests that I do have here.

00:40And we may tell our audience up front, you are not per se an entrepreneur, but you're working on the investment side.

00:48You are with Visionaries VCs.

00:51You're based in Berlin, and you have been the former growth lead at tier during a hyper growth phase.

01:00I think you have one or two stories to tell from this time.

01:04You also have been a competitive athlete.

01:09I'm sure we'll also talk about that.

01:11Plus, you specialize in BASAS, AI, cybersecurity, and deep tech, where you're exactly at the right place here at StartupRad.io.

01:19You have a strong belief in operational experience and radical accountability in VC.

01:26We'll talk about that, I think.

01:28And you lead investments that solve real-world industrial problems via applied AI.

01:33I also got some names here of investments, not you personally did, but visionaries, including Lovable, the unicorn Personio, Miro, Pigment, Tacto, Apron, Choco, Pivot, and Central.

01:57And, of course, we link down here in the show notes, the interview with Central.

02:04That was already a lot.

02:06Take a deep breath.

02:08So, let's talk a little bit about your journey and your vision.

02:13How did your time at tier for everybody?

02:16That's one of the e-scooter companies, the hyper growth e-scooter companies, during its hyper growth phase influence your approach as an investor.

02:25Yeah, that's a great question, Jörn.

02:30Just for background, I was with tier pretty much from its pre-seed stage until Series B, which meant that within a very short period of time, within one year, we went from zero to 400 people, reached 100 million annual revenues and similar number on the funding side,

02:48which I always refer to as a little bit of a positively chaotic scaling journey, because there was a lot of positive elements and there was also a lot of chaos.

02:57And one thing that was definitely very, very clear in that short period of very intense time is that the people you work with really, really define what you can achieve.

03:15And exceptional talent will find a way to own the outcome and really build something that will move the needle in some context.

03:25And this is one really interesting conversation we always have with founders that are building very early stage teams, especially investing in pre-seed and seed,

03:33is that who you should hire and how do you know that person actually performs well?

03:38Did you hire the right person for the right role? Yes or not?

03:41And if somebody is underperforming, is it because they are not doing the right responsibilities or not in charge of the right responsibilities or whether ultimately it's just not a fit for the company?

03:54And one key learning that really, really shapes the way that we are trying to work together with founders is this perspective of how we look at talent and ultimately how you can hire the type of people who you can use as Swiss Army Knives in very different situations.

04:09And just to be clear, those people, Swiss Army Knives, they don't necessarily need to come from just a handful of really big Berlin-based startups or a handful of consultancies, right?

04:22Absolutely not.

04:24These type of people can come from pretty much any types of backgrounds.

04:29Very often, in the majority of the cases, they have at least some level of unconventionality in their life story, which doesn't mean that they went to some Ivy League schools,

04:42but very often they might end up coding in their parents' basement at the age of 12 and just cannot stop reading books about building things.

04:51And I think that's something that just comes up again and again.

04:54With these people.

04:56I assume you had quite a lot of fun at here, but what motivated you to become really from an operator turned into a VC?

05:11Did you think at the beginning it was a more relaxed job?

05:17And how did you end up at Visionaries Club?

05:21Yeah, it was not a very conscious decision at all.

05:25When I was with Tia, I had a friend who was running Entrepreneur First batch in Berlin and we went into a couple of conversations and we were talking about when I personally thrive the most.

05:42And I also realized in that conversation, which I didn't know about myself, is that I thrive the most, the more I look outside of my regular day-to-day environment, so to say.

05:55And I think there are different types of people here.

05:58I definitely fall into the camp of really thriving in the environments where I get new impulses, not just from a topic perspective, but also individuals' perspective.

06:09And then this friend of mine told me, hey, I actually have two friends who are actually founders, former founders, and they are launching a fund.

06:17And it sounds like that since they are building this venture fund from scratch and you get to spend your entire day speaking to people who are thinking how the future should look like in a different way, changed by technology, sounds like a very good intersection of your operator DNA, building something actually as in a venture fund.

06:39So being kind of like an entrepreneur in VC and also being able to have this very outward looking way of working and I pretty much just took that introduction, not expecting too much and I think a lot of things resonated with me and the things that came together, the different DNAs of Visionaries Club made me very excited and that's where I have been in the last six years.

07:03You often speak about radical accountability.

07:12What does this mean when you work with founders?

07:17For example, let's think I'm one of your investments and currently it's not going well.

07:24What would you expect in terms of radical accountability?

07:27Radical accountability is a pretty broad term, I would say, and definitely don't only use it in the relationship of VC to founder, but also the other way around.

07:43And this is something that we also most importantly encourage founders that we back use within their own environment, so to say.

07:52Radical accountability is a little bit of a stolen term, I would say, from radical transparency from Ray Dalio, switching the word out transparency into accountability, but it's very simply put, radical accountability means that especially in environments where there is a lot of change and just as I told you at TIER, there is a lot of chaos.

08:16The one thing that you can only go back to and always can go back to is owning output and that's really what radical accountability means because everybody has ideas, everybody has comments about how things should be done, but what really differentiates the top 0.01% of startups from the rest is that this sense of radical accountability is pretty much soaked into the culture of how people think and get stuff done.

08:45And this is something that pretty much accountable, both on a positive and rather consequential negative side when things are either executed very properly or not executed properly.

08:57So, we're now going a little bit into market insights and your investment thesis.

09:05And we may tell our audience because I do believe most of our audience are founders and they somehow have an idea.

09:15They had heard Visionish Club before, but we should tell them that you're around the data that I found around 600 million euros assets under management.

09:24Your last fund was, I believe, I believe in 2022, 400 million.

09:28That's correct.

09:29Yes.

09:30And so, you're one of the bigger VCs and therefore, it is of interest to me.

09:37But some of the things that first stood out is that you guys have a very unique base with limited partners.

09:45For everybody who's not familiar with the term, it's basically the institutions, the people who give you the money to invest them as VC, legacy industrialists, and modern digital entrepreneurs.

10:00How does that shape your portfolio strategy?

10:03Because it sounds like you have two magnetic poles and they always pull you in different directions.

10:10Yes, I'm happy to give you a little bit of background because I do think that this will help also scope the conversation a little bit.

10:19And I just want to tell you and the listeners a little bit about the origin of Visionaries Club.

10:24So, we have been around for some six years.

10:26And one very important theme that we have all across the investment team is that everybody is a former operator or founder.

10:34Pretty much really everybody in the investment team.

10:36And this is something that we really wanted to incorporate into the very DNA of how we set up the fund ultimately.

10:44And back then when we set up the first fund generation, one very important decision we made was, as you said, that we only raise capital from entrepreneurs that we know well.

10:54And if you look at who these entrepreneurs are, as you mentioned, it's two very different group of individuals, but it's always the private people behind these companies.

11:03But on the one hand, we have a collection of some 30 unicorn founders.

11:08If you look at, for example, Andre from Miro or Daniel from UiPath from Eastern Europe, Ilka from Supercell or Miki from World from the Nordics.

11:15If you look at Fintech, for example, Peter from ADM, Guillaume from Checkout.com, but also a lot of dark entrepreneurs such as Get Your Guide, Flixbus, HelloFresh, AutoEyes, who build these very successful hyperscaling tech companies.

11:27And as you mentioned, on the completely other side, we have this collection of family business entrepreneurs who are a little bit less conventional entrepreneurs because they didn't start these companies themselves, right?

11:36They inherited these multi-decade old family businesses from the what we call old economy or industrial economy that have been operating pretty much offline for a couple of decades, very often in manufacturing, logistics, distribution, wholesale.

11:50And what's really interesting about them and about Europe specifically is that 80% of the European economy is owned by family businesses.

11:58So when we were thinking about bringing this entrepreneurial DNA into how we build the fund, we found that if we look into the next decade and we look at the intersection of what we work with in the European economy and what technology can bring and unlock, this is really the intersection that we are looking into.

12:15So this is very digital first entrepreneurs and this is very non-digital entrepreneurs who are incredibly important of how we think about the economy.

12:23So this is how we really bring this group of people together.

12:26And over the last couple of years, we scaled this fund to some 600 million.

12:30And ultimately, if I really want to sum it up in one sentence, the single biggest leverage that we bring into the relationship we have with our founders that we back is that we bring in these people and really connect the founders that we back with the right people at the right time across all this network.

12:49This can be about potential customer introductions, this can be about integration partners, hiring, go-to-market, but based on our experience, instead of coming in with a high-level VC advice, we just take a step back and really execute on those introductions that are strategically important.

13:02I also do have a theory, maybe you also have an opinion on that because I'm now doing startup interviews with the project in Germany that I did before since, let's say, 13 years.

13:20And over time, I've seen a lot of entrepreneurs maturing, getting bigger businesses and so on and so forth.

13:26And when they're running the company for long enough, there is barely a difference between those people and the more traditional entrepreneurs, how they view their life, how they view the company and their outlook on the company.

13:39Would you agree to that?

13:41I would say it's really interesting, especially if you contrast industrial entrepreneurs with really, really large corporates.

13:50One thing that we made a very conscious decision on taking on these industrial entrepreneurs and how I would say they think about actually digital entrepreneurs is that since they own a very significant portion of the company and they are also in a very active strategic role, they can take decisions much faster and they can take risk with a much higher level.

14:14Again, this is not a guarantee that they will suddenly all adopt highest, you know, the most advanced software and end-to-end agenting AI automation tomorrow.

14:24But at least you can get an answer from them very, very fast, whether this is the right timing for them to speak to a certain software company or not.

14:32I see.

14:34We're now talking to VC and I would be interested, maybe except for AI, what sectors are you most bullish on right now?

14:43Especially in early state investing?

14:48Yes, this is a really good question.

14:50I would say that given our very DNA and kind of history, over the last couple of years, we built a relatively lean team.

14:59So in total, we are six people in the investment team.

15:02And that means that for us specifically, it doesn't make sense to split up the team by sector, right?

15:09So even though we have certain interest areas, for example, I personally look into a lot of topics on the, let's say, more technical side when it comes to data, infrastructure, architecture, AI, cybersecurity.

15:21These are all areas to love to look into.

15:24We are incredibly focused on founders and pretty much picture them within the bigger realm of what we find exciting, right?

15:34So if you look at the way that we work usually and work together with founders, we spend, I would say, 80 to 90% of our time on the ground in ecosystems because Europe is incredibly fragmented and you have absolutely no idea which ecosystem will produce the next really exceptional entrepreneur.

15:50You pretty much have to be there, really try to find these founders, sit down with them and really understand why the timing of what they want to build fits into the broader market.

16:04And this can be in very different industries.

16:07For example, I personally have been looking into and working with a lot of founders in procurement, but also back teams in cybersecurity.

16:13It can be about, you know, engineering, it can be about pretty much pure data, it can be about really, really, we are, I would say we are very sector agnostic from that perspective.

16:26And which ones are the most interesting right now?

16:34Sectors?

16:34Yeah.

16:35You can also speak from personal perspective because I do understand from such broad company, it's always difficult to speak like about this or that, but your personal experience in your area of responsibility is totally fine.

16:52It's a really interesting question because we are now at a very interesting shift between cloud software 1.0 versus the next type of, let's say, software.

17:08You can still call it software.

17:09And I know you didn't necessarily want to get an AI answer, but I would say one very clear shift that we are seeing at the moment is that traditional software as a service

17:20will very likely cease to exist in its current form in a very short period of time, and almost these models around services as a software is emerging.

17:31Because if you look at especially, for example, the industrial economy, one very interesting theme that we have been looking into, and maybe one thing to pinpoint very concretely, is how we are thinking about the automation of back office work, right?

17:47And this traditionally, for example, in software has been very much tied to sectors.

17:52So, for example, you had to think about a very specific procurement software as a service that had, I don't know, an underlying database, some type of a user interface, maybe integration with legacy systems, and then you try to pretty much take these companies and then target these companies and roll them out.

18:09Now, what we are seeing is that if you look at some of the back office work, let it be, let's say, insurance, procurement, sales, quoting, construction, you have these massive back offices where people are just sitting in front of their computer and have been doing the same repetitive tasks they have been trained to do for pretty much 10, 20 years.

18:31And in my view, this is going to be exactly the absolute first type of use case where full level of automation will be achieved within a very, very short period of time.

18:42So, we absolutely don't see any scenario where these tasks won't be 100% automated within a couple of years of time.

18:49And this is especially relevant because this is exactly the type of talent also in our economy that is retiring fast and there is no supply of it.

18:58Because you have to be somewhat educated in order to execute on these tasks, but it's actually not something that needs incredibly sophisticated, you know, qualification that cannot be taught in certain areas.

19:12Why do you believe Europe is positioned to lead in the application layer of AI globally?

19:18The reason for that is that Europe is a very special, Europe is in a very special position.

19:26If you look at the talent in Europe, it's very clear, speaking to entrepreneurs from a global scale, speaking to investors from a global level, that Europe has absolutely zero talent problem.

19:38This is something that is sometimes a massive misconception.

19:42Europe has incredible engineers, incredible entrepreneurs.

19:45It's a very fragmented ecosystem, but from a very fundamental perspective, I think this is just one thing that is, I think, very important to get right.

19:56When it comes to the application layer of AI, and especially if you look at the European economy and getting back to, for example, how many of these industrial companies,

20:06but for what it's worth, you know, non-industrial companies necessarily, have been working with traditional software like SAP and others, you know, some of these existing software stacks have been around for 30 years, right?

20:19And there is an absolute clear reason for that.

20:23And the clear reason for that is that their lock-in is so incredibly high that challengers over the course of the last couple of decades absolutely fail to remove them

20:34because they are so ingrained and so customized to the local environment that it was just pretty much impossible to create a strong enough incentive for these customers to put effort into removing them and adopt a new solution.

20:47Now, the opportunity for Europe right now, where pretty much this ingrainedness is the highest, I would say, is that with the shift in technology, when it comes to mapping, let's say, integration endpoints,

21:02when it comes to using new technologies around AI to facilitate data migration, data schema mapping, mapping out workflows, and pretty much ultimately automating these workflows,

21:14is something that was not unlocked before, and from an application layer perspective, this is what we have contacts on.

21:24And I think the key word here is contextuality, and this is something that Europe has.

21:29The technology is there.

21:30We can use it, pretty much, from a foundation model perspective, which, you know, we don't have to be a winner in.

21:36And ultimately, this is exactly where the opportunity is, because you can match this level of contextuality

21:41and generate a new generation of challenges that can ultimately remove this absolute high-locking of incumbents

21:50that have been dominating the industry for many, many years.

21:54As personally, I've been working in more SAP projects, then I would like to admit here, I can totally see that.

22:03But when I now think about the logic that we used there back in the days, and the teams you've been talking about doing their administrative stuff,

22:14which would be quite a picture book example of being replaced by AI agents,

22:21I get to think that you would not only need to re-envision the software,

22:29but you'll also need to re-envision, at least in part, the companies,

22:36because there'll be a lot more of automation, especially in administrative duties.

22:41Yes, 100%.

22:45And I do not think that this is going to be a zero-to-one shift, right?

22:52If you look at, for example, a very clear example of the migration push of SAP on-prem to SAP HANA,

23:02that, you know, SAP is pushing massively,

23:04some of these companies actually spend a very, very significant amount of euros

23:09and a very significant amount of time, meaning years,

23:13to go from the concept of understanding what the existing on-prem setup looks like

23:20from the perspective of what's standard SAP code, what's custom SAP code,

23:24how, for example, the business logics look like,

23:27all of these things, hire a bunch of consultants,

23:31kind of try to map out exactly how this should look like in the cloud.

23:35It doesn't just work in a way that you buy a virtual machine

23:38and you just push it there within a week,

23:40but you actually have to go through this entire process.

23:42And then pretty much you try to move the application.

23:46Now, from my perspective,

23:49technologies that can, on the one hand,

23:52speed up this type of process,

23:56as well as think about how these workflows can be fully automated

24:01from, let's say, an agentic perspective,

24:04will need to emerge in parallel

24:07because you cannot just throw an agent pretty much at an on-prem SAP instance, right?

24:11I think it's very, very clear.

24:14So you will need very different approaches.

24:17And ultimately, what will unlock the most value

24:20will have the most grip on the market,

24:22as we have seen also in the past.

24:23There is no absolute clear-cut answer what type of approaches we'll win.

24:30But ultimately, I think it needs to be a game of parallel approaches, to be honest.

24:36And what you've been talking about is on-premise,

24:39basically more or less very simplified.

24:42You had a very big data center.

24:45You're running SAP there just for your company.

24:48And now it's moved on HANA into the cloud.

24:51Very, very much simplified.

24:52And that was already a big project.

24:55But the more I think about using AI agents in such a tool,

25:01I always get the idea that the most successful companies

25:05or the most successful software in the future

25:08may not be the fastest AI agent,

25:11but I do get the one who makes it the easiest

25:15to administrate those agents,

25:18control them,

25:19give them duty,

25:20and keep them in check.

25:22Because if you do,

25:23what I have in mind are those huge Excel sheets

25:27where you track stuff.

25:28And then at one point,

25:29you don't realize that this agent is doing A,

25:33this agent is doing P,

25:34and they're basically just giving each other a work.

25:37So there is a new way

25:40how you need to think about a company,

25:42getting back to the idea

25:44of rethinking the company.

25:47But we've been a little bit interwined already into AI.

25:52So I was wondering,

25:53we're talking to VC,

25:54what is your framework to identify AI startups

25:58with like a real differentiation,

26:01and they don't necessarily have just buzz?

26:04Yes, that's a really good question.

26:08So I'm especially speaking from the perspective

26:12of a preceded investor,

26:14which is a little bit of a cheat card sometimes,

26:16because you can always give the answer

26:18that the founder has to be exceptional,

26:20which in itself,

26:21on the one hand,

26:22can be a really good answer.

26:23On the other hand,

26:24I completely agree that

26:25if you look at many of the verticals

26:28you see right now in agentic AI,

26:30you do see an absolute red ocean

26:33of parallel approaches,

26:34let's say when it comes to

26:35the number of AI legal tech companies

26:38or the number of companies

26:39that are trying to build your AI SDR

26:41and so many of these different approaches.

26:44From our perspective,

26:46the two things we precede ultimately

26:49and early stage investing

26:51in a really simple,

26:53simply put way

26:54is a really truly excellent founder

26:57building in an incredibly exciting market.

27:00And the incredibly exciting market

27:02is pretty much a given in many cases

27:05when you are looking at

27:05the opportunity of the technology

27:07and what you can see

27:08in many of these use cases.

27:10Now, ultimately,

27:11the exceptionality of the founder

27:12is something that we pay exceptional,

27:15like really, really big attention to,

27:18because that's where

27:19you can identify somebody

27:22who will be able to navigate

27:24the, let's say,

27:25the level of uncertainty

27:26that you will need to navigate

27:28in this space.

27:29And if you look at just

27:30the simple acceleration

27:31of the last two to three years

27:33when it comes to what capabilities,

27:36for example, AI can do,

27:37this is one topic

27:39we have been discussing

27:40with the founder,

27:41is that, for example,

27:42if you look at

27:44some of the, let's say,

27:48features that, I don't know,

27:50some of these foundation models

27:51could do, for example,

27:53writing a poem

27:54or something like this

27:54that are absolutely not spectacular today,

27:56almost to anyone

27:57who has been natively using

27:59these AI tools,

28:00back then,

28:01the amount of value effect

28:02that you got from them

28:03was, you know,

28:05a hundred times higher

28:06than what you get from now,

28:08right?

28:09So, from our perspective

28:10and from a human perspective,

28:12human experience perspective,

28:14what we see is that

28:15we get used to the power

28:18of the technology

28:18incredibly fast.

28:19and we just forget

28:21how much progress

28:22has been made

28:23in the last two to three years.

28:25And I think personally

28:27that we completely underestimate

28:28how much this technology

28:29will develop

28:31in the coming years.

28:32And because of that,

28:34there is a very high level

28:37of uncertainty

28:37that a certain founder

28:38needs to navigate.

28:39So, ultimately,

28:40as a pre-seed or seed investor,

28:41trying to identify

28:42if you have a level

28:43of tech defensibility

28:44as a startup

28:46that just developed an MVP

28:47is not a very valid question,

28:51right?

28:51So, for us,

28:52the focus really,

28:53really shifts

28:55very much

28:55to the exceptionality

28:56of the founder,

28:57which in itself

28:58can lie into,

28:59for example,

28:59unique insights

29:00to a certain industry.

29:01Because, as discussed already,

29:03for example,

29:03in Europe,

29:04when you still

29:06have the challenge

29:07of, for example,

29:07needing to sell

29:08to some customers

29:10in person

29:11or do field sales,

29:12for example,

29:13let's say in construction tech

29:14or industrial tech,

29:15a founder that is able

29:17to understand,

29:17on the one hand,

29:18the capabilities of AI

29:19but also understands

29:20the particularities

29:21of the industry

29:22is the combination

29:23that makes them exceptional,

29:25right?

29:25And this is something

29:26that we always try

29:27to look at

29:28from a perspective

29:29point of view.

29:32I see.

29:33We'll be back

29:34after a short ad break

29:36and then talk about

29:36how you do your investments,

29:38how, for example,

29:39you evaluate a founder

29:41and so on and so forth.

29:47Hey, guys.

29:49Thank you for being back

29:50with us

29:51after the short ad break.

29:52I'm still talking

29:53to Martin Partner

29:54at Visionaries VC

29:56and we are talking

29:58right now

29:59about how

30:00they evaluate

30:01the founders.

30:05What traits

30:06do you think

30:07define

30:08a genre-defining

30:10founder

30:11in your eyes?

30:13Yes,

30:14this has been

30:14an exercise

30:15we have been

30:16constantly thinking

30:17about

30:17and re-challenging

30:18ourselves on,

30:20especially

30:22if you look

30:23at the really

30:24exceptional founders

30:25in Europe

30:25and how

30:26serendipitously

30:27they came out

30:28of absolutely

30:29unexpected hubs,

30:31times,

30:31and setups.

30:32We definitely

30:34don't think

30:35that you have

30:35a very strong

30:36ability to put

30:38together a checklist

30:39and just tick boxes

30:40and give an average

30:42score

30:42and if somebody

30:43hits that average

30:44score about

30:44a certain level

30:45then you invest

30:46if not,

30:46then not.

30:48So for us,

30:50exceptionality

30:51can come

30:52in very different

30:52forms

30:53and we have

30:55certain traits

30:55that we usually

30:56look into

30:57that can feed

30:59into certain

31:00exceptionalities

31:01in founders

31:01in very different ways.

31:03To give you

31:03an example,

31:04one trade

31:06that we are also

31:07looking into

31:09is a combination

31:11of a founder

31:11having

31:12pretty much

31:14very much like

31:14for example

31:15if you would

31:15look into

31:16let's say

31:18soccer

31:19to come up

31:22with a very

31:22concrete example.

31:24What makes

31:26a good player

31:27shoot

31:27for example

31:28a ball

31:29in a good way?

31:31it's a combination

31:32of timing

31:33it's a combination

31:34of power

31:35and accuracy

31:36and these are

31:38the three characteristics

31:39and the combination

31:39that really

31:40exceptional founders

31:41do have.

31:43When it comes

31:43to timing

31:44also interchangeably

31:46use it together

31:47with urgency

31:48or kind of like

31:48proneness to action

31:49is the ability

31:51for the founder

31:52to very clearly

31:53articulate

31:53when to do what

31:55and how to

31:56prioritize

31:56what.

31:58It can be about hiring

31:59it can be about

32:00execution

32:00it can be about

32:01when they

32:02start building

32:03a certain product

32:04in a certain market

32:04power

32:05is pure grit

32:07it's about

32:07how hard you work

32:08and pretty much

32:10how much you

32:10commit to the company

32:11and accuracy

32:12is ultimately

32:13the ability

32:15to identify

32:17the most important

32:18problems

32:18and really

32:19shortlist those

32:20on a daily basis

32:21and this is something

32:22that we always

32:24try to evaluate

32:25on a recurring

32:27basis

32:28together with

32:28founders

32:29this is one

32:30very important

32:31aspect obviously

32:32that just comes up

32:34again and again

32:35in certain founders

32:37and I want to

32:39highlight this

32:39sense of urgency

32:40that with

32:41some of the most

32:42successful founders

32:43when as an investor

32:45you are in a meeting

32:46with them

32:46you almost feel

32:48uncomfortable

32:48about wasting

32:50their time

32:50and this is something

32:52that you know

32:53I definitely felt

32:54at tier

32:55with Lawrence

32:56who is just

32:56a fantastic founder

32:57as well

32:57is that

32:58their sense

33:00of urgency

33:01when it comes

33:01to coming to action

33:03and their sense

33:04to not waste time

33:05in instances

33:06where they

33:07absolutely don't need to

33:08is very very high

33:10and this is something

33:10that you can

33:11I think really sense

33:12as an investor

33:13to give you

33:14another example

33:15product

33:17and personal

33:17obsession

33:18is something

33:19that you definitely

33:21can identify

33:22relatively

33:23accurately

33:24and it comes

33:25out in very

33:26different formats

33:27in very different

33:28founder journeys

33:29because if you

33:30have a fresh

33:31university team

33:32coming out of uni

33:33maybe a couple

33:34of months of

33:34internship experience

33:35who have been

33:36constantly thinking

33:37about a certain

33:38problem

33:38and you know

33:39they were

33:40absolutely sleepless

33:41about it

33:41and now try

33:42to attack it

33:43which was the

33:44case in some

33:45of our investments

33:46like Tactile

33:46for the listeners

33:47it's a Munich

33:48based procurement

33:49software company

33:50from some of

33:52the small

33:53and medium

33:53sized businesses

33:54in the European

33:55economy

33:56they have been

33:57obsessing over

33:58and over

33:59about how

34:00incredibly broken

34:01procurement

34:01is

34:02it's really

34:03was their DNA

34:04if you look

34:05at the seasoned

34:06industrial

34:07sorry

34:08a seasoned

34:08entrepreneur

34:09for a seasoned

34:10operator

34:10entrepreneur

34:11who have been

34:12in the industry

34:12for more than

34:1310 years

34:13it's going to

34:14be a very

34:15different type

34:15of personal

34:16or product

34:17obsession

34:17if for example

34:18somebody decides

34:19after 6 years

34:20of being

34:21one of the

34:22most successful

34:22let's say

34:24companies

34:25or scale-ups

34:26for example

34:27companies like

34:28Klarna

34:28or Conto

34:29or Swile

34:30to give you

34:31just some

34:31examples

34:32from our

34:32portfolio

34:33to

34:35start from

34:37zero

34:37and start

34:38with a

34:38blank sheet

34:39of paper

34:39to start

34:40building

34:40something new

34:41they

34:42often felt

34:43something

34:44from a market

34:45timing perspective

34:46and in a

34:47once-in-a-lifetime

34:47perspective

34:48from an

34:48obsession

34:50perspective

34:50that they

34:51just have

34:51to make

34:51that step

34:52and this

34:52is something

34:53that clearly

34:54comes out

34:54when you

34:55have a very

34:55open and

34:56transparent

34:56personal

34:57conversation

34:57with them

34:58I was

35:00wondering

35:00can you

35:01give examples

35:02of painkiller

35:03versus

35:04vitamin

35:05startups

35:05and why

35:07that distinction

35:08matters

35:08yes

35:10it's

35:13it's

35:14something

35:14that we

35:15really like

35:17using in

35:17the context

35:17of B2B

35:18software

35:18and that's

35:19the reason

35:19why I

35:20would

35:20personally

35:21be an

35:21absolutely

35:22horrible

35:22consumer

35:24investor

35:25because

35:25for me

35:26comprehending

35:27painkiller

35:27versus

35:28vitamin

35:28in that

35:29context

35:30is just

35:30very

35:31difficult

35:31in B2B

35:32software

35:33it's

35:34from at

35:35least a

35:35theoretical

35:35perspective

35:36it's

35:39something

35:39relatively

35:40simple

35:40to identify

35:41from a

35:42conceptual

35:43perspective

35:43a painkiller

35:44is something

35:45that can

35:46help your

35:47customer

35:47either

35:48increase

35:49your revenues

35:49or decrease

35:50costs

35:50or will be

35:51absolutely

35:52mission critical

35:53for you to

35:53operate

35:54if you look

35:55at

35:56for example

35:57some of the

35:59agentic AI

36:00companies that

36:00try to

36:01automate

36:02your sales

36:04team

36:04that's a

36:05very clear

36:05you know

36:06impact on

36:07you being able

36:08to for example

36:09serve more

36:10customers or

36:11open your

36:11funnel up more

36:12so really try

36:12to for example

36:13drive your

36:14supply

36:14if you look

36:15at for example

36:16some of the

36:16agentic AI

36:17companies that

36:18are trying to

36:18automate your

36:19back office

36:19end to end

36:20you pretty much

36:21can replace

36:22very concretely

36:23headcounts in

36:24your back

36:24office at

36:25fraction of the

36:25cost

36:26so that's

36:26really doing

36:27that

36:27if you look

36:28at companies

36:28like Stripe

36:29for example

36:30that's a very

36:32clear example

36:32of a company

36:33that is just

36:34mission critical

36:35for you to

36:35operate

36:36because otherwise

36:36you don't get

36:37paid

36:37right

36:37so this is

36:39pretty much

36:40how we try

36:40to think about

36:41it one

36:42very interesting

36:43thing when we

36:46are thinking

36:46about pecular

36:47versus vitamin

36:47is that in

36:48reality things

36:50work sometimes

36:51in a different

36:52way if you

36:54look at the

36:54very concrete

36:55example of

36:56process automation

36:56and I'm

36:58talking a little

36:59bit pre-AI

37:00era there have

37:01been a huge

37:02wave of some

37:03of these RPA

37:04companies that

37:05were trying to

37:06pretty much

37:06automate anything

37:07that Zapier and

37:08UiPath

37:08couldn't but yet

37:10they were

37:11not successful

37:12why is that

37:13it's very

37:15obvious from

37:15a conceptual

37:16point of view

37:17that if you

37:17automate something

37:18then you also

37:19save money

37:20yes that is

37:21absolutely true

37:22but if your

37:23customers don't

37:23want to automate

37:24those things

37:25and they are

37:25not in the

37:26business of

37:26automating

37:27things it

37:27becomes often

37:28very difficult

37:29for them to

37:30convince that

37:31they need to

37:31give the extra

37:32upfront investment

37:33for those cost

37:34savings and

37:35that's where

37:35we always

37:36try to match

37:38the conceptual

37:39understanding of

37:40what is a

37:41painkiller with

37:41reality of

37:42what actually

37:43is a

37:43painkiller

37:44we've been

37:47talking in the

37:48introduction that

37:49you do have a

37:50background in

37:51competitive sports

37:52how does this

37:54influence your

37:55judgment in

37:56high stakes

37:57investment decisions

37:58competitive sports

38:00is a really

38:01interesting environment

38:03and there are

38:04a lot of

38:05parallels when

38:07you're thinking

38:07about company

38:09building because

38:10in competitive

38:11sports in many

38:13cases you have

38:14to prepare for

38:16one single event

38:17that might happen

38:18once a year

38:18once every two

38:20years or in the

38:21case of the

38:21Olympics once

38:22every four years

38:23and you have to

38:26show up every

38:27day sometimes

38:27every day twice

38:28training up to

38:3014 times a week

38:31give your absolute

38:33best and think

38:34about how you

38:35can be your

38:35better self

38:36every single

38:36day for that

38:38one single

38:38event and

38:39sometimes you

38:40have an injury

38:41that comes in

38:42that takes you

38:44back let's say

38:45four to five

38:45months in your

38:46preparation and

38:48you cannot do

38:49anything with it

38:49but there are a

38:50lot of crisis

38:50situations and

38:53if you look at

38:54the most

38:54successful people

38:56in sports and

38:57competitive sports

38:58they are able to

39:00deal with

39:00setbacks

39:01incredibly well

39:02keeping their

39:04cool in those

39:05events is

39:06something that

39:07is really

39:08exceptional and

39:08if you look at

39:09some of the

39:09top athletes

39:09there's just

39:10something that

39:10comes out again

39:11and again

39:12when it comes

39:14to investing

39:15and having an

39:18honest conversation

39:18with a founder

39:19this type of

39:21pressure test

39:21also I would

39:23say can be

39:23very much

39:23applied and

39:25if you're having

39:26an honest

39:27conversation

39:27about the

39:29highest heated

39:31crisis situations

39:32that they ever

39:33had in their

39:33life and

39:34listen to how

39:36they dealt

39:36with it

39:36is something

39:38that really

39:38shows how

39:39they deal with

39:40the situations

39:40because these

39:41situations happen

39:42and as a

39:44founder you

39:45just have to

39:45solve them

39:46and this is

39:48something that

39:48we always

39:50have as a

39:51bit of an

39:52exercise and

39:53what some of

39:54our best

39:54founders absolutely

39:55managed to do

39:56incredibly well

39:57is to assess

39:58the situation

39:59understand what

40:00you can do

40:00about it

40:01what you

40:01can't do

40:01about it

40:02and act

40:03like that

40:03let's talk a

40:08little bit

40:08about applied

40:09AI and

40:10SaaS adoption

40:12you said

40:13AI will be

40:14the biggest

40:15driver of

40:15SaaS adoption

40:16particularly

40:17in industrial

40:18sectors

40:19can you a

40:20little bit

40:20expand on

40:21that because

40:22you also said

40:23the classical

40:24SaaS how

40:24does this

40:25fit together

40:27here

40:27you mean

40:30the classical

40:31SaaS will

40:32will

40:32resist to

40:34exist in the

40:35form that it

40:36has been

40:36existing

40:37yes in the

40:38form right

40:39now and

40:40where will

40:40it go

40:41what will

40:41be like the

40:42next iteration

40:43the next form

40:44of classical

40:44SaaS

40:45this is a

40:48really interesting

40:49topic and

40:49and I think

40:50everybody is to

40:51some extent

40:52still very

40:52speculative about

40:53it but what

40:56we have seen

40:57already in the

40:58last couple of

40:58months or you

40:59know one or

41:00two years is

41:01that the

41:02ultimate

41:03application

41:04interface that

41:05that people in

41:08these environments

41:09are using to

41:11execute on

41:11certain workflows

41:12is completely

41:13changing if you

41:14for example look

41:15at very

41:16traditional

41:16software as a

41:18service as

41:19mentioned you

41:20might have

41:21some backend

41:21database some

41:23features that

41:24people you know

41:25input data in

41:26maybe the

41:28software application

41:29is processing

41:30this data and

41:30then you have

41:31an output

41:31that's something

41:33that given the

41:35capabilities of

41:35what's changing

41:36right now

41:37in my view

41:39will really

41:40really change

41:41just from the

41:43perspective that

41:44if you look at

41:45how traditionally

41:46workflow has been

41:47executed

41:47especially in the

41:50case of

41:51knowledge work

41:5180% of

41:53knowledge work

41:53is just

41:53finding some

41:55processing and

41:56summarizing

41:56information and

41:57maybe passing

41:58it on to the

41:59next person

42:00this is something

42:02that can be

42:03done incredibly

42:04well using

42:05AI and

42:06some of

42:07not only it's

42:09possible right

42:10now to remove

42:11some of the

42:11intermediary steps

42:12but you can also

42:13completely rethink

42:14how the whole

42:16workflow is

42:16executed

42:17because if you

42:18look at this

42:19whole concept

42:20from a data

42:20perspective and

42:21data processing

42:22perspective an

42:24agent or AI

42:25does not

42:27necessarily have

42:29to process the

42:29data the exact

42:30same way as a

42:31human being

42:32would right

42:33ultimately and

42:35this is something

42:35where I do

42:36think that AI

42:38as an application

42:39layer will

42:40completely change

42:41the way that

42:42that industrial

42:43companies work

42:44just let's take a

42:45very I would say

42:46concrete look at

42:47procurement

42:47ultimately if you

42:49are head of

42:49procurement at

42:50some of these

42:50industrial companies

42:51your number one

42:53job as

42:54procurement leaders

42:55usually say is

42:57to keep your job

42:58because procurement

42:59is a bit of a

43:00loser game right

43:01you ultimately make

43:02sure that everything

43:03is procured on time

43:04at the best price

43:05and it arrives

43:06if it does that

43:08then great you're

43:09doing a great job

43:10if it doesn't

43:10then it's not

43:11so ultimately

43:13if you look at

43:14how procurement

43:15leaders have

43:16been using

43:16software for

43:17example in the

43:18past is that

43:19they had to

43:21enter for

43:21example their

43:22system or ERP

43:23system to look

43:24up inventory

43:25talk to product

43:27talk to product

43:27engineering sales

43:28what do you need

43:30to procure

43:30ultimately go up

43:31to your supplier

43:32open some type

43:34of supplier

43:34database

43:35look at some

43:37catalogs

43:37submit some

43:38purchase orders

43:39and it was all

43:40a little bit of

43:41a chaotic workflow

43:42from the perspective

43:43of what you

43:43needed to do

43:44but if you look

43:45at ultimately

43:46what for example

43:47some of the

43:48AI capabilities

43:49can unlock

43:51when it comes

43:52to understanding

43:53need budget

43:54analysis

43:55and what you

43:56ultimately need

43:57to execute on

43:58at a given

43:59point in time

43:59and what you

44:00need to optimize

44:01for is something

44:02that is very

44:04different from

44:05how you would

44:06work as an

44:07individual human

44:08and how you

44:09would process

44:09this information

44:10and pass it

44:10on if that

44:11makes sense

44:11that definitely

44:16makes sense

44:18but it

44:19it takes a

44:20while until

44:21it sinks in

44:22what this

44:23really means

44:23and how

44:24it actually

44:25applies to

44:26different

44:26industries

44:27I don't

44:30claim I'm

44:30through with

44:31this thinking

44:32by getting

44:32closer and

44:33closer

44:33you are

44:35also

44:36connecting

44:36AI startups

44:37with

44:38LPs

44:38to solve

44:39real problems

44:40and how

44:41does a

44:42successful

44:43case for

44:43such a

44:44corporation

44:44look like

44:45yes

44:47so this

44:48is something

44:49that we

44:49talked about

44:49and when

44:50we built

44:51the fund

44:51or started

44:52building

44:52the fund

44:52we wanted

44:53to make

44:54sure that

44:54we have

44:54this

44:55unique

44:55ingredient

44:56of having

44:58the connection

44:59to these

45:00limited partners

45:01of industrial

45:02family businesses

45:03represent a

45:04very significant

45:05portion of

45:06the economy

45:06because very

45:09often if you

45:09look at

45:10B2B software

45:11you know AI

45:13or call it

45:14pretty much any

45:14type of

45:15technology at

45:16the moment

45:16in Europe

45:17if you want

45:18to build a

45:18multi-billion

45:19dollar outcome

45:20as an

45:21entrepreneur

45:21it's very

45:23difficult

45:23to ignore

45:24this group

45:25of family

45:26business

45:26entrepreneurs

45:27and industrials

45:27in the long

45:28term

45:28if you are

45:30selling to

45:30European

45:30companies

45:31so our

45:33idea was

45:35that you

45:36know when

45:36we build

45:37the fund

45:37is that we

45:38can connect

45:38these

45:39entrepreneurs

45:39that we

45:40back with

45:40these industrials

45:41and you

45:43know as

45:43mentioned the

45:44most important

45:45thing that we

45:46bring in as

45:46Visionaries

45:47Club is that

45:47whenever we

45:48invest with

45:49founders and

45:49this often

45:50already starts

45:50before investment

45:51can be you

45:52know sometimes

45:53in the stage

45:54of ideation

45:54is that we

45:55sit down

45:56together and

45:57figure out who

45:59from our

45:59industrial network

46:00is actually most

46:01helpful to talk

46:02to from the

46:04perspective of the

46:05product that the

46:06founder is

46:07building and

46:08ultimately get

46:09them in front of

46:10the most important

46:11stakeholder let it

46:12be a champion or

46:13an actual user of

46:15the product as

46:16soon as possible

46:17and really shorten

46:19this response time

46:20that they get

46:21from these

46:22industrial companies

46:23and this is

46:24something we do

46:26think has a very

46:26fundamental unlock

46:27and in many

46:28cases some of

46:29these industrial

46:30companies might

46:31get back hey

46:32this is incredibly

46:33relevant now we

46:34are in the

46:35middle of this

46:35massive I don't

46:36know ERP

46:37migration so let's

46:38talk in six

46:38months sometimes

46:39they say this is

46:40exactly what we

46:41have been looking

46:42for for a long

46:42time let's set up

46:44a paid DOC

46:45next week and

46:46sometimes it's

46:47no we will you

46:49know build this

46:49internally and

46:50this is not

46:51relevant but

46:52getting this

46:52response time

46:53versus trying to

46:55call it inbound

46:55some of these

46:56industrial businesses

46:57that are not

46:58even on LinkedIn

46:59is something that

47:00is very

47:01contrasting and

47:02in an ideal

47:03scenario whenever

47:05we can connect

47:06these industrial

47:06businesses with

47:07the founders that

47:08we are working

47:09with we can

47:10really shorten

47:11this cycle and

47:12in the most

47:12exceptional cases

47:13founders can

47:14pretty much

47:15champion these

47:16companies as

47:17well as if

47:18they were let's

47:19say technology

47:19companies and

47:21this is where the

47:21magic of 3D

47:22exceptional founders

47:22lie so you

47:24know we don't

47:24guarantee any

47:25pay contracts

47:27this is not the

47:28business we are

47:28in but this

47:29kind of door

47:30opening function

47:31is what we've

47:32past success

47:34is no indication

47:35for future

47:36performance the

47:37usual disclaimer

47:38in financial

47:38services yes

47:39let us go a

47:41little bit

47:41shortly into

47:43Europe's

47:44venture capital

47:45landscape if you

47:46still have a

47:47little bit time

47:47yes what are

47:51the biggest

47:51challenges European

47:52founders face

47:54today and how

47:55can they overcome

47:56them the biggest

47:58challenge European

47:59founders face

48:01today is

48:03ultimately what

48:04everybody says

48:05which is

48:06fragmentation of

48:07the European

48:07ecosystem and

48:09why we think

48:10fragmentation is the

48:12biggest challenge

48:12at the moment

48:13is because

48:16various different

48:18ecosystems are in

48:20very different

48:21maturity stages

48:22if you look at

48:23London if you look

48:24at Paris if you

48:25look at some of

48:26these ecosystems

48:26they have a

48:29history of producing

48:30some really

48:31exceptional you

48:32know venture

48:32outcomes and some

48:34of these venture

48:34outcomes started

48:35producing some

48:36really exceptional

48:37operators who might

48:38end up you know

48:39starting new

48:40companies and for

48:41example if you have

48:42proximity of a

48:43university you

48:44might even have

48:45the chance to

48:45bring some of

48:46these entrepreneurs

48:47or operators into

48:48some of these

48:49hubs that can

48:50really enable

48:50entrepreneurs not

48:51only to just pull

48:52the trigger and

48:52start something new

48:53and take risk but

48:54also to be able to

48:55hire exceptional

48:56talent and start

48:58you know selling to

48:59the local ecosystem

48:59now this is not the

49:02case for all

49:03ecosystems if you

49:04look at some of

49:06you know other

49:08cities the

49:09ecosystem are in

49:09very different

49:10stages but

49:11ultimately if you

49:12look at for

49:13example the

49:14example of Miro

49:14Andre started it

49:16from a small town

49:17in Russia called

49:17Perm that many

49:19people didn't even

49:20hear about and

49:21through this big

49:22filter he managed

49:23to you know build

49:24it into a

49:26successful enough

49:26outcome that now

49:27it's a globally

49:27leading company but

49:29if you put

49:31yourselves into

49:33the shoes of

49:34something like

49:35that the amount

49:36of challenges that

49:37you need to go

49:37through and the

49:39amount of you

49:41know pushback that

49:41you will get that

49:42will set you back in

49:43terms of timeline and

49:44how fast you can

49:45market your product

49:46is exponentially

49:47higher and the

49:48more remote the

49:49ecosystem is the

49:50more difficult it

49:50is ultimately and

49:53this is something

49:53that is already

49:54changing but

49:55ultimately this is

49:56the very reason why

49:57we set up Visionaries

49:57Club in the way

49:58that we did that

49:59if we back for

50:00example a young

50:01entrepreneur out

50:02of Munich who

50:03you know Munich

50:04is already a

50:04pretty advanced

50:05ecosystem but if

50:06they want to

50:07connect to a

50:08wide range of

50:09entrepreneurs who

50:10either you know

50:11successfully navigated

50:12a certain landscape

50:13in a certain

50:13industry traditionally

50:15it has been

50:15incredibly difficult

50:16for them to get

50:17a meaningful

50:18connection with

50:19these people but

50:21via our approach

50:23we really try to

50:25work on that

50:25and facilitate that

50:26how should

50:30European VCs

50:32adapt to

50:33stay global

50:33competitive

50:34because I've

50:35I've seen in

50:36the past

50:36a few

50:38analyzers that

50:39at least from

50:40the perspective

50:41of the LPs

50:42the European

50:44VCs have

50:45outperformed

50:46over time

50:47their American

50:47counterparts

50:48so they did

50:49have a

50:50competitive

50:51advantage

50:51how can

50:53they keep

50:53pushing it

50:54in their

50:55increasingly

50:56fractured world

50:57right now

50:57venture capital

50:59traditionally has

51:00been and always

51:01will be

51:02driven by

51:03power law

51:03so there will

51:05be a lot of

51:05winners and

51:06it's very

51:06difficult to

51:07give I would

51:08say a collective

51:09formula of how

51:10European venture

51:11capital funds

51:12all of them

51:13can stay more

51:14competitive and

51:14when you say

51:15you know

51:16European venture

51:17capital funds

51:18it almost feels

51:20like that you

51:20know you would

51:21need to move

51:22the whole curve

51:23in a certain

51:23way which

51:24which is

51:25somewhat tied

51:25to to to

51:27make your

51:28environment but

51:29what I can say

51:29is that in

51:32order for

51:33Europe for

51:34some of the

51:34European venture

51:35capital funds

51:36that can be

51:37successful is

51:39completely to be

51:40on the ground

51:40because if you

51:42look at the

51:43amount of time

51:44it takes for a

51:45certain ecosystem

51:46to absolutely

51:48ignite can be

51:50very very

51:50short and if

51:52you are trying

51:52to run this

51:53from behind

51:55your desktop I

51:56think it's a

51:57very very

51:57difficult job and

51:58I think you see

51:59this story very

52:00interestingly playing

52:01out right now in

52:02the case of

52:02Stockholm where a

52:04couple of

52:04companies including

52:05Glovable just

52:07absolutely

52:07demonstrated how

52:09you can get onto

52:10the path of

52:11building a

52:11globally leading

52:12company in a

52:13very short period

52:13of time and

52:14taking that

52:15encouragement

52:15many many

52:17other really

52:18exceptional talent

52:19in the ecosystem

52:20had the courage

52:21to start new

52:21companies and

52:23pretty much within

52:24the matter of

52:25six months it

52:27became from a

52:28really interesting

52:29ecosystem into one

52:30of the leading

52:31ecosystems I would

52:31say in Europe and

52:32if you're a venture

52:33investor you just

52:34have to be there

52:35and see that for

52:36yourself speak to

52:37the founders because

52:38they will grow they

52:40will build very

52:41successful companies

52:42very fast and if

52:43you're an early

52:43stage investor and

52:44you're not there

52:45you will miss a

52:46thousand a very

52:48last high level

52:49question what

52:51needs to change in

52:53how early stage

52:54capital supports

52:56technical founders

52:57in Europe because

52:57we do have a lot

52:59of very good

52:59universities very

53:00good technical

53:01universities lots

53:02of stem talent

53:04but I do see a

53:05lot of them

53:06struggling to get

53:08out not only but

53:09also in terms of

53:11biotech and so on

53:12and so forth to

53:13really get the

53:14support they

53:15need admittedly

53:16technical

53:17university unique

53:18and Unternehmertum

53:19are getting very

53:21good at this but

53:22there needs more

53:24to change do you

53:26have a few ideas

53:27what needs to

53:28change in order to

53:29support them better

53:31get them more

53:32opportunity to find

53:33a company right out

53:34of university

53:34yes absolutely

53:37the most important

53:40challenge is

53:41bringing back

53:42exceptional execution

53:45and commercial

53:45talents and

53:47connecting them

53:48with early stem

53:49talent as soon as

53:50possible if you

53:52take the example

53:52of Hungary and

53:54Eastern Europe

53:54where I'm from

53:55ultimately and this

53:56is a conversation I

53:57just had with a

53:58founder Hungarian

53:59VC founder that

54:00just got into VC

54:01I'm now 29 he's I

54:04think also towards

54:06towards that age

54:07up until we

54:10you know

54:10finished our

54:12maybe second degree

54:13or master's or

54:14started working in

54:14the first position

54:15we didn't have a

54:17clue about what

54:17venture capital is

54:18or you know what

54:19entrepreneurship

54:20truly is

54:21we heard about the

54:22concept of starting

54:23company but the

54:24concept of what it

54:25means to take risk

54:26and take pulling the

54:29trigger to build

54:29something massive

54:30was absolutely

54:31missing and this is

54:32something for example

54:33you absolutely see in

54:34many business

54:35universities already

54:36happening in the

54:36West in they how

54:37you know you have

54:38successful e-commerce

54:39founders going back

54:40and saying you can

54:41start this company you

54:42can start this

54:42company and then you

54:43have students sitting

54:44there and having a

54:45conversation after you

54:47know the lecture

54:47about hey actually we

54:49should start doing

54:49this we are in a

54:51time of our life

54:53where pretty much we

54:54can take the most

54:55risk that we can and

54:57this mindset is

54:57something that is

54:58very very difficult to

55:00bring back very

55:01early but the more

55:02early you can bring it

55:03soon as possible

55:05pretty much start of

55:06university ideally the

55:08earlier you start the

55:10spark for this type of

55:11conversations and

55:12encouragement also

55:12across students so I

55:14would say for all

55:14those different

55:15ecosystems that you

55:16have in STEM you

55:17know all across

55:17Europe you as you

55:19mentioned you have

55:20TUM you have ETH you

55:22have Oxbridge you

55:23have so many of these

55:23universities the

55:26ability to connect

55:26students with those

55:27entrepreneurs that

55:28really really made it

55:30there is something

55:31that that is in my

55:33perspective is really

55:34missing I see

55:37Martin thank you

55:39very much it was a

55:40pleasure having you as

55:41a guest hope to have

55:42you back and for

55:43everybody who'd like to

55:44learn more we link of

55:45course your LinkedIn

55:46profile the website of

55:48Visionaries Club what's

55:49the best way to pitch

55:50just pretty much send an

55:53email martin at

55:54visionariesclub.vc

55:55I do have a game that's

55:58going on since I

55:59interviewed a few years

56:00ago Alex from

56:01back from high tech

56:03and I was I was I was

56:05wondering if you get an

56:08email that only says the

56:09headline yo we should

56:10talk would you reply

56:11the headline I would

56:16say we don't I

56:18personally don't care

56:19that much about what's

56:21in the message is is is

56:23a little bit more

56:24important okay great

56:26thank you very much

56:27pleasure thank you so

56:29much for having me

56:29that's all folks find

56:36more news streams events

56:38and interviews at

56:40www.startuprad.io

56:43remember sharing is

56:45caring

56:46you

How AI Is Disrupting Industrial Tech | Visionaries Club VC Insights

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