The Exchanges

Q your business. They've been pretty clear about it. Um, and I think you have used the frontier models in your product, but you must be thinking, my Lord, am I enabling my own demise by partnering with them? And there's all these open source models. So, um, how do you think about your partnerships with those type of frontier models and the fact that they want to kill your company?

A So on, on the, on the first part, the, Given we create a platform, we try to provide all our lamps out there so our customers can pick. Entropic, OpenAI, Open Source, Google Models, um, and that agnostic, being agnostic to a specific model is actually helpful because customers, can they make sure that they build a harness, build their agent orchestration, create a voice element of how that agent interacts with the world, how the marketing way interacts with the world, but they are not dependent on any model. So for us, that part is, is, is, um, It's a, it's actually good because we can provide that to the customers. On the, on the kind of the second big part of like, of course, the, the space is overlapping increasingly. Models, our platform, platform, our application, everything is becoming a little bit more, more fuzzy. For us, there's still the defining piece was focusing on that one layer of, like, how does interaction look like? How does communication look like? And we've been able to help compete them on voice models, um, both on text-to-speech, speech-to-text, on the turn-taking, on music, and, um, and we've, you know, here, our research team is, uh, is, is, is, is a set of magicians that are able to continuously do it time and time again, um, And I think part of the reason is, it's on the research side. It's the architecture that matters, not the scale. You really need …

AI assessment note: “being agnostic to a specific model is actually helpful because customers”

Q How so? Yeah, what, what, how should you speak to the LLM? We saw Sergey Brin say, threaten it with bodily harm. It's a very effective technique if you haven't tried it, but what are the, Things that are different when you're talking to the LLM.

A The, the, the specific emotional example, we, we work with a lot of, um, financial services companies, uh, uh, Revolut, Klarna, PacBank, and some of the frequent case, not in all of them, is of course how you remind people about payment, or that you collect that, that, um, from the people that aren't answering, and frequently people would naturally feel ashamed of Telling the real situation. With AI, people are much more open to share what actually happened, give the information, and suddenly this emotional block of, like, in front of other human, I don't want to be able to say all of that, is, is, is very different. So that's different. Um, usually people are more snappy with AI voice agent. It's like, you know, like, quick responses.

AI assessment note: “With AI, people are much more open to share what actually happened”

Q Do they get to pick their price or you pick the price?

A Depends on the model. We do, we do both. So you can, you can either give it a default that lets us distribute that slightly more optimally, or you can pick yours and the use case is going to be, going to be different. And like you said, opens up a set of incredible opportunities in that dynamic context and other languages. Uh, but maybe a last one on that, like voice is such a big part of identity and probably, probably our most important work was actually working with people that lost their voice. Due to ALS, due to throat cancer, and working on bringing that voice back. So I worked with Congresswoman in the US, Jennifer, Jennifer Wexton, who lost it, and wanted to continue to inspire others that you can do incredible work despite that, and, ah, and was the first speech delivered in, in, in, in, in Congress. Or more recently, I think this was my, the, the most, ah, like heartwarming story. There was, ah, this woman that, ah, That's wanted to get married, lost her voice before she could get married.

AI assessment note: “Depends on the model. We do, we do both.”

Q then vibe coding. And now we actually have people building production code who are not developers. You have developers going 10 X and token maxing. How has building software changed internally? And how do you deal with making sure that the code is Really high quality because people are paying you this money, but they're going to demand really high quality product since they're spending so much money with you.

A Yeah, that's, it's also true. The 2022 was still the year where topics of the day were crypto and, um, and metaverse. So the building there was also the best time to start because we could actually take a, take a bit of time to focus on what we thought is the future. Uh, but then the way we are structured is A lot of small teams, especially across the product engineering, but also in how we think about go-to-market optimized for specific industries, telco, financial services, healthcare, so every unit is very tightly knit together, um, and we do that across the company, uh, so it's usually five to 10 people teams that, that, that, that run ahead, and inside of each of those teams, the decision we took, which is slightly different than how it's usually structured, we embedded engineers in In, in every place. And even in the places which aren't engineering. So our talent team will have an engineer. Our legal team will have an engineer. Our revenue engineering or go-to-market engineering have engineers embedded all across. And those people have two roles. One is, of course, creating automations and bringing the software inside of that team. But second is actually helping everybody else do what you said, which is make sure that people are adopting AI, but also There's a security check for everything they deploy, because ultimately if, if you're not using a lot of the coding softwar…

AI assessment note: “we embedded engineers in In, in every place”

Q for talent, so, so tell us about how many employees you have now, and how you maintain the culture of the company when revenue is ripping, investors are throwing money at you, showing up at your doorstep, I mean, quite literally, um, but you've got to run the company, you've got to build a culture, so how many employees now, and how are you dealing with these competing, uh, priorities?

A Yeah, that's the, that's the key element of how you all, for us, the, the element of, like, how we can maintain the culture despite the quick growth is, is, is kind of critical, and how we optimize both the interview cycle, how we are bringing people on board, how we onboard them. We have 600 people today, um, so also very quick growth on that people side, and as a company, we combine research and product, so we, we, we are building a communication platform for AI, On the research side, this includes everything across audio. Generating speech, transcribing speech, orchestrating speech for interactions. On the product, this is how we can complete the entirety of the customer journey. From marketing, and creating assets, and localizing them internationally, through customer support with voice agents, to proactive enablement of how voice agents can help in operations, training, and sales. So this requires a lot of different talent, um, and, and, and, and, and a part of that revenue growth is actually reflection of the functions we've grown over time. So, From the original team, very research, very engineering heavy. From the first 10 people, we had zero attrition. Everybody is, ah, ah, still at the company from those core research and engineering talent building together with us. So, so far, being able to outcompete, and I think the common thread, and, and credit to my co-founder,…

AI assessment note: “We have 600 people today, um, so also very quick growth on that people side”

Q left with, well, how do we actually do this? Do we get a voice impersonator, but instead they went to you. Talk a little bit about that deal and how it went down. And is that what they used recently, you know, in, in, uh, some of the new films with Darth Vader? There's a new Darth Maul series, um, where they have Darth Vader, and did you power that?

A I don't know what I can say about the new things, but definitely the big use case that did, that big, big, completely new experience, uh, was in the gaming space where, ah, yes, uh, Fortnite, so Epic Games, uh, not, not game, Fortnite launched, um, Darth Vader, which people and players could interact with live, in partnership with the estate, in partnership with Disney, so every player, after reaching a certain stage, could have a Darth Vader interact and help you solve the missions. And we are seeing that kind of mode coming up more and more often of how you can effectively extend, extend your likeness, your, like you said, like publicity into interactive use cases, bring it across the world, ah, up together, ah, So that was exactly that model, and now we are working on, on, on, ah, one of the public ones is Headspace, so Headspace has a great meditation.

AI assessment note: “I don't know what I can say about the new things, but definitely”

Q ability to make your own Language model today, especially with all these great models out there that are now open sourced. It's going to be a pretty easy for a company with your level of resources. So why wouldn't you at least offering it as an option? And then I guess there's cost. I mean, you must be shipping tens of millions of dollars to the frontier models every year.

A Ship a good amount. Um, we are good partners, good partners with them, uh, um, but, but it's, um, it's ultimately, you know, showing up in the value we can create, too. So, like, a lot of what we spoke at the beginning of how we can elevate ourselves as an organization, too, is definitely helpful. So, I think they've done tremendous work on, on building. Uh, it's, it's almost crazy that each of us has, like, a, a, Turing, uh, like, you know, if you, if you were to chat with an agent now, it feels like, um, the Turing test will be complete. It's as smart as another human, uh, and we hope this year we'll do that same thing for voice, uh, where any conversation feels like you're speaking with another human.

AI assessment note: “Ship a good amount. Um, we are good partners, good partners with them”