00:39:19 · John Collison, Mati Staniszewski
[00:39:19] S0: seems like for certain types of model architectures, there's, like, an upper limit on, like, the natural size. Have we found that upper limit for voice models? [00:39:26] S1: It's it's... It feels like for specific use cases, like, say, audiobook narration, you probably found that size. Probably don't need to stretch it too much bigger to to make the quality as much higher. But for certain use cases, that will probably grow. The the thing that's that's, you know, like, I hesitated on the question is, in a cascaded approach, you probably will not see, like, dramatic size changes. Mhmm. You inherently want the models to be quick Yeah. And they're reliable. You want to orchestrate them in a smart way. In a fused approach, probably that will get into, like, tens, hundreds billion parameter models because you kind of combine, of course, the Intel... The LLM side and the voice side. Yeah. So that will get bigger. But on the Adjust Voice, I think it will keep keep being small. [00:40:07] S0: Okay. But there are certain domains where, yeah, we'll see bigger models. [00:40:10] S1: That's still interesting. [00:40:11] S0: Yeah. Yeah. It it is amazing how... It does seem fun from a research point of view how there are still these various unsolved aspects and how you guys are just making technical breakthroughs and then releasing them down the product pipeline, that's like a really fun stage of a company's life cycle.
00:40:11 · John Collison, Mati Staniszewski
[00:40:11] S0: Yeah. Yeah. It it is amazing how... It does seem fun from a research point of view how there are still these various unsolved aspects and how you guys are just making technical breakthroughs and then releasing them down the product pipeline, that's like a really fun stage of a company's life cycle. [00:40:27] S1: For sure. It's like fun because we... It feels like we can do innovation on both sides. There's like so much on research side, so much on product side, and then like the kind of, ultimately, the biggest parts is how we deploy it to the customers, where Light and Intent, like SMB will have very different dynamic than the enterprise. It's not vendor SaaS relationship where you just give the product out there for the biggest companies out there, but you are more of a partner in their AI transformation part, so you want the resources to work alongside them to work on the frequently very new use cases that were impossible to help create and bring those voice agents to production. Yes. So that's, a big big big shift. Yes. But the biggest focus is is is how we how we bring the conversational agents out there to to the businesses around the world. [00:41:14] S0: So when you say con... Bringing conversational agents is the biggest priority, is this for customer service type use cases? Like, what are the most popular use cases for conversational agents?
00:41:14 · John Collison, Mati Staniszewski
[00:41:14] S0: So when you say con... Bringing conversational agents is the biggest priority, is this for customer service type use cases? Like, what are the most popular use cases for conversational agents? [00:41:25] S1: Yeah. Like, we want to be a partner for, like, full interactions between business and... Businesses and their customers or their audience. I'm saying their their audience because that will apply in support. Support is the easiest one because that's where it's most ready. Yeah. But, like... And that's maybe the big difference to how we see ourselves to some of the other companies in the space is this can also apply to sales. You can you can have the proactive side of reaching back. You can have AISDR versions of that. Yes. And then you can have all the way to the marketing use cases where we are your partner for for working on on on... Even outside of, like, the the conversational agent space of how you create a great marketing campaign. Yes.
00:41:25 · Mati Staniszewski, John Collison
[00:41:25] S1: Yeah. Like, we want to be a partner for, like, full interactions between business and... Businesses and their customers or their audience. I'm saying their their audience because that will apply in support. Support is the easiest one because that's where it's most ready. Yeah. But, like... And that's maybe the big difference to how we see ourselves to some of the other companies in the space is this can also apply to sales. You can you can have the proactive side of reaching back. You can have AISDR versions of that. Yes. And then you can have all the way to the marketing use cases where we are your partner for for working on on on... Even outside of, like, the the conversational agent space of how you create a great marketing campaign. Yes. [00:42:01] S0: And, sir, how does it break down between... You know, we had Des Traynor from Intercom on here, and they have Finn, their agent, and it's a thing in the website that you can go talk to. And he described a very similar phenomenon that you described, which is you start maybe thinking, oh, this will help me answer customer support queries, but it becomes like a generic UI for the, you know, for the website where it's a box you can type in to go do things and understand things. And so why wouldn't you read the docs and design your integration by, you know, whatever? And so will I have, like, one for text and then one for voice? Will you guys do text too? Will... Just how does that... Because it seems like this is also succeeding at the text level with [00:42:46] S1: Yeah.
00:42:46 · Mati Staniszewski, John Collison
[00:42:46] S1: Yeah. [00:42:47] S0: Finn and Sierra and all these things. [00:42:48] S1: The places where we know we will we will be able to provide the biggest value is, like, where, ultimately, today, you will have more... Either a big portion or most of the interactions coming from voice. Mhmm. So if that kind of intersection is there Yeah. That's where we can provide higher value. And, of course, like, if you if you need a text chatbot there, that's that's like if you fix the voice agent, you'll have fixed text piece, like, inherently as well. But the place where we we do optimize today is going to be, like, how do you select the right voice for the right customer interaction, how you pull that in the in the pretty complex case of what you mentioned earlier of, like, how you orchestrate that to pause or look for something deeper into the docs, how it can be extension of entirety of the business, so not only in support but across entire of the user journey. But the bottom line is, like, we want to be able to provide you across entirety of the interactions. Yep. Voice is usually a big part of those interactions. [00:43:43] S0: Yes. [00:43:44] S1: And, yes, we need to we need to solve the integrations. We need to solve the knowledge. [00:43:47] S0: We need [00:43:47] S1: to solve text as part of that. But, like, we wouldn't, for example, go into... What I think will happen in a lot of those cases, like, very deeply into reasoning version of those use cases where you maybe need to, like, the multi touch... Yeah. Yeah. And a [00:44:02] S0: lot of complex actions.
00:44:02 · John Collison, Mati Staniszewski
[00:44:02] S0: lot of complex actions. [00:44:03] S1: A lot of, like, financial analysis of, like, is... Like, that would be not not something we optimize for. Can we talk [00:44:08] S0: about your revenue ramp? Or you're just one of the fastest growing startups, period, of the past few years. What's your most recently announced revenue figure? [00:44:16] S1: Most recently announced was end of twenty Or... 20 [00:44:19] S0: whatever number you wanna give us. [00:44:20] S1: Most So recently announced was 350 at the end of twenty twenty five. Yeah. But the the best proof of the technology working... So recently, are... Announced our work with Deutsche Telekom and T Mobile, with Revolut, with Klarna, with Meta, with IBM, a wide set of use cases. And this quarter was kind of one of the the best for enterprise growth where we had the first quarter hit 100,000,000 in a... In an an additional ARR growth, which is crazy. [00:44:46] S0: In net new ARR? [00:44:47] S1: In net new ARR.