Scaling Europe
00:26:31 · Sebastian Johnson, Dimitris Samouris
[00:26:31] S0: Yeah. Okay. Got it. And as an industry, these are not... I don't... Certainly, in my time as consultant, we weren't well known for being the most or the fastest to adopt new technologies. [00:26:42] S1: Yes. [00:26:42] S0: It feels like that has somewhat changed in AI. Yes. Has that been your experience? And if so, why do you think that is?
00:26:47 · Dimitris Samouris
[00:26:47] S1: Absolutely. And and going back to when I told you the first... When we tried to raise our seed round in May 23, one of the key pieces of feedback from venture capital was consulting firms are terrible buyers. They're the worst possible technology buyers. I did not understand what that meant at the time. And I think part of the problem is that no one had built for them. Yeah. Like, think about what the last piece of software someone built for the consulting industry was. think-cell? Yeah. And before that, the Office Suite. Like that was it. That's... It hadn't changed. Before the Office Suite, I I remember I have some funny stories of like senior partners at Parthenon telling me when I first joined that they would... They'd sketch slides out on... What's it called now? It's not not acrylic. It was like this acetate. Right? Like the old university lectures that you'd have where they'd draw a slide out and they'd project it. That's how they used to deliver work back then. And now you have this new technology, the steerable printing press that can actually produce cogent analysis, and it's perfect for this industry. And that changed a lot for them. I think they realized that, okay, like we need to make it easy for our teams to test and to buy this stuff. Now, enterprise sales is hard. Some of the customers that we're working with now, like quite literally took us three years to sell into. And a lot of that is because we've been displacing internal tools that they had to go through this cycle of trying to figure out if they wanted to build versus buy. But they're getting much better at being buyers and they're doing cool things now. Have some customers who build like sandbox environments that simulate a couple of engagements and then whenever a startup comes to them, because they've realized now that innovation is gonna come from the startup community. Yeah. It's a quick plug and play into an existing... Like, they can actually run a dry run of that engagement. So they're changing.
00:28:46 · Sebastian Johnson
[00:28:46] S0: Yeah. You mentioned that that it was deciding whether to build or buy. Yeah. Are they really... Are they thinking about building their own internal solutions or what does that look like?
00:28:54 · Dimitris Samouris
[00:28:54] S1: Oh, for sure. Wow. Yeah. Yeah. They... So it's gone through two waves. The first wave was when we started going to market. Mhmm. So this is like May June of twenty three, when... It's so easy to build on top of a third party API nowadays and you have... Remember like consulting firms are full of like very smart people that are really into tech. Not not all of them, but there's a portion of them that are like quite ambitious in what they want to do as early adopters. And so they'd say, like, we should absolutely build this. It's so and they built they built first versions of them. They built POCs that were successful, and they proved out the use case. There's a big difference between building out a POC or something that can be helpful on a single engagement or a pilot and then scaling that to a reliable enterprise solution that thousands of your staff can use every day. And by the way, the tech is not the hard part, not even close. The hard part is the change management. Do I have someone who is going to train these people? Do I have 20 fourseven global customer support? Is the product getting better over time? Those are the things that they found it difficult to continue to progress on past the POC. So there's been a huge wave of experimentation. That was phase one where they they tried and then a few of them continued to invest, but most kind of gave up after they went through that that cycle. Phase two has been Claude Claude code specifically. Yeah. And here you had a bunch of senior partners that got stuck in and were like, wow, like I can build tools by myself. I don't even need to go to the internal build team now and have them prioritize me versus other stuff that they're working on. Like, I myself can build stuff. And that fueled a second wave of like, well, why do we want to work with external vendors? Like, we can just vibe code everything now. And I think the market is now again coming out of that phase because there's a huge difference between a vibe coded app and again production level software that crucially answers one question and there are very few customers that have gotten to this stage yet, which is how do I turn my firm into a machine that gets better over time? So this is a fundamental machine learning system question. Right? Like Yeah.
00:31:17 · Dimitris Samouris
Every subsequent interaction, every ride that Waymo goes on or Tesla goes on feeds data that makes the next version of the So next model even how does my firm get better with every subsequent diligence that I do? Those are like system level questions at a vibe coded app that two partners use are never going to be able to to address. So it's a constant, you know, up and down. And I think to be successful is... In our shoes is to work with them. Like, I think a lot of startups get very frustrated when customers tell them, oh, we're gonna build this on our own. One of the things that we've done with a number of them, by the way, is I had my cofounder write a memo. All of the things that we solved when building expert call workflow software. It's two pages of every technical problem. We give them the answer Seb. It's not like I'm not trying to hire this. Like, this is what you need to solve. Yeah. Take it. Good luck. And that actually has shifted the conversation a lot of times where people realize, okay, like, these guys have been working on this for a long time and there's a lot that we would have to deal with that we frankly don't really want to deal with. And so that that changes the frame of the conversation. So my advice to other startups in this space is like, help help your customers. They're working through some very existential questions and just because the answer is no now does not mean that it's no no later. And if you stay with them along that journey, you you earn a lot of goodwill.
00:32:51 · Sebastian Johnson, Dimitris Samouris
[00:32:51] S0: Is is that the biggest pushback you get from customers that we'll try and build our own, or what are the other reasons they might [00:32:56] S1: say no? Overwhelmingly, when we get pushback is is why can't I build this on on my own? That is no longer the case so much with senior AI stakeholders who have after two cycles realized that there's lot more to this, but individual partners or individual like consultants who are like, I can vibe code this, like, why am I paying you guys extra? But it... It's gotten much easier over time. Now I think people realize the role that startups can play in this space. [00:33:23] S0: Do you see a lot of similarities between yourself and the industry that you're working or selling to to the legal industry that we've seen with Harvey and Legora? [00:33:33] S1: Absolutely. With the caveat that legal tech has been the category for fifteen plus years. I diligence legal tech [00:33:43] S0: Mhmm. [00:33:44] S1: Businesses. By the way, one of the the most interesting components of that was we'd always come back to the same question, which is you're trying to sell efficiency to a market that doesn't want it. I'm a partner that makes money off of a billable hour. Yeah. What good does it do me if you make me 20% better? And so law is furthest along this journey of like, okay. We need to transition to output based pricing, and you see some of these, like, AI native law firms like Crosby out there [00:34:13] S0: Mhmm.