Scaling Europe
00:21:56 · Sebastian Johnson, Dimitris Samouris
[00:21:56] S0: Mhmm. [00:21:57] S1: What is your edge when everyone has access to the same underlying models and the same secondary, like, data or research sources? Your edge is in the primary research. So people are doing more expert calls, more surveys in order to get to a differentiated view. So the the volume of work has stayed the same. The starting point has really moved up. Yeah. That's really interesting that they they are now looking for new, yeah, edges or source of information to help them form their viewpoint or their strategy. Correct. [00:22:30] S0: Yeah. You you obviously found a real market in voice. Right? It's like voice being the first use case of Junior Yes. And that being a lot of where you kind of captured value. Is is the plan to stay on voice so you've got a vision to do a lot more across different kind of verticals or technologies?
00:22:48 · Dimitris Samouris
[00:22:48] S1: Yeah. So the way we think about this, Seb, is these particular firms, these professional services firms, they all run on conversations. Mhmm. So let's take your typical engagement from the moment a partner picks up a phone call from a client saying, hey, like, what do you know about this? We're considering commissioning some work on it. Like, can you come pitch to us? All the way to the final like readout or deliverable when you when you like when you go and present your findings to the client. There's probably in the range of a 100 conversations that happen in between beginning and end that move the dial on the investment thesis or the answer. So you have the BD call or the pitch call. You have a team kickoff internal team sessions partner reviewing work, check ins, checkouts with individual, like, work streams. You've got your interim readout with the client. You... Maybe you're meeting the management team of the target you're, you're investigating. Then you have all your expert calls, which is where we started on the workflow side. All of those calls individually represent the next step in the answer of going from blank page to final deliverable. And so we think it's critical to capture that information and help professional services firms clean it, structure it, and then build automation off the back of it. I think a lot of our our peers in the market, and there's a lot... Many ways to skin a cat, they're very focused on the workflow layer, which we agree is like a necessary component of the big picture at the end of the day. We kind of feel that that's gonna fade away. Like, if you really believe in this thesis that software becomes headless, agents will do everything, The workflows will get eaten up and it doesn't really matter what interface they run on whether it's an internal platform that your customers built one of the major model vendors or an applied AI vendor that sits on top of it. What matters is the data input and being the voice intelligence layer, we think is like really really critical to that journey.
00:25:07 · Sebastian Johnson, Dimitris Samouris
[00:25:07] S0: And that data layer, is that is that what you're calling the knowledge graph? I've I've seen some talk around knowledge graph. Yeah. Is that what you mean? It's like capturing all the information from a project to a client and not being the thing that you kind of pull the analysis from? [00:25:18] S1: Yes. So the knowledge graph, one way of thinking about it is... Think of a good analogy. Traditional diligence was someone gives you a filing cabinet [00:25:30] S0: Mhmm. [00:25:31] S1: With thousands of documents in it, and you're supposed to go through and pull out the relevant bits of information from that as pertaining to the investment thesis. A knowledge graph is almost think about it as like the detective's evidence board with like the cork and the strings that are being drawn between different suspects or events. It is a way of visualizing relationships between entities in a particular market. And this is a much richer way of parsing information and as part of what we are doing under the hood when we are capturing voice data and other types of data as well. There... In many ways a diligence report can be think of... Thought of as like a knowledge graph flattened into a PowerPoint PowerPoint report. And so we spent a lot of time thinking about how we can enrich the data that is being produced by our customers to help them get to the final answer. [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.
00:26:31 · 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?