00:21:45 · Guillaume Moubeche, David Steinberg
[00:21:45] S1: Yeah, it's insane. What I love about Athena and everything you've built is like, obviously you're delivering huge amount of value to your customers, but at the same time, I feel like this is a product that people will keep on using more and more, because the reality is like, you're getting a lot of context also on the company and everything that they are doing, which means that you can reinforce Athena and everything you do to basically like suit them better. And any switch to a competitor will actually make the context basically go away and disappear. And eventually the results will be always worse than whatever they were getting with you. So they will always come back. So I think it's pretty magical. You should. [00:22:30] S0: You're tired of running your SaaS based startup, please come work with me, because you just said that better than anybody I've heard say it. Here's the deal. We take our clients' data, we take our data, we match it into a consumer data platform. The algorithms live exclusively in there. No data exhaust to the foundation or frontier models, but 100% of the knowledge base and the context lives in the consumer data platform. It does not go back to the enterprise. Now, we don't extract any of that to our data cloud. It lives in this ecosystem. If you fire us, it all goes away. So I think there's a reason that our net retention rate in 2025 was greater than 120% as a company. So if you think about a Jeep, 100% is good, 110% is like gold. We're [00:23:22] S1: both I wish at you these numbers.
00:23:22 · Guillaume Moubeche, David Steinberg
[00:23:22] S1: both I wish at you these numbers. [00:23:24] S0: No. And I'm not trying to show up, but my point is that it's just something that I think a lot of people don't understand about our business. If you fire us, you lose 100% of the context and inference model knowledge base. So if you think about it, and Chris Greiner, our CFO, does an incredible job on this. The longer a client stays with us, the more money they spend, because the greater the knowledge base, the greater the return on marketing and technology spend, the more of their dollars they move from other software and marketing partners or vendors to us. I mean, I'll tell you, I cannot remember the last time a client actually fired us. I mean, we have some clients that go in out of super scaled or scaled. I now have a new category that I lovingly call super duper scaled. It's been incredible. But because of the way the ecosystem works, their data plus our data, you then remove the personally identifiable information to protect the consumers. [00:24:38] S1: I was curious to get your view on models because, know, like, I mean, if we look at a year ago, I think the frontier models were way ahead. Now we're seeing like open weight and lightweight models, open source models to a stage where, you know, they're either at the same capacity or at least on specific tasks, they can either sometimes outperform like frontier models. So what's your view around this and how do you leverage it as a competitive advantage?
00:25:06 · David Steinberg
[00:25:06] S0: Yeah. I mean, so if you look at the Athena inference model, which we announced in partnership with Fireworks dot ai and NVIDIA, And you look at the product roadmap video or demo, they said something that I think is incredible. Our AIM models operate at a 65% more efficient level and 12% greater accuracy than using frontier models on our own data where we've tested it. They're just getting started. So you're going to have two types of models, right? You're going to have a foundation or frontier model, which is going to require billions and billions and billions of dollars of CapEx to train it. Then you're going to have inference and contextual models that are going to have to be changing every moment of every day. Because inference and context changes every moment of every day in most businesses. They're going to be hyper accurate, hyper scalable, and super small. They're going to be very targeted. And that's what we believe is the future of knowledge base, which is by the way, not to say that Claude and OpenAI are not worth trillions of dollars. I'm not the right guy on that. Work with everybody. And I believe as it relates to auto cogeneration, as it relates to operating business models, and I believe writing poems, they're going to be the guys for many, many, many years. As it relates to business tasks, we believe the future is inference models. And by the way, it appears as if NVIDIA agrees, right? Because they bought Hugging Face. They're buying these platforms that really, I think, are going to be less frontier based and more inference based. Sort of at Zeta, we're already seeing the efficiency and the efficacy of our proprietary inference models as substantially higher. Now, to be clear, I think that 6512% is like baby sticks. It's not even table stakes. I think ultimately we're going to be hundreds of percentages better using our inference models than the frontier models to create the tasks that are mission critical for enterprises to operate their businesses. So it's going to be very interesting to see how I think the world bifurcates into the frontier models, into the inference models, into contextual models, and then how the internet bifurcates into the HTTP layer, and then the agentic layer that lives below it.
00:27:45 · David Steinberg, Guillaume Moubeche
I think you're going to have a lot of moving parts going into the next five to ten years, which I think are going be incredible. By the way, it's why we bought Senso AI. It's why we believe the future of a big component of e commerce is going to be a genetic base. It's why we've built out our generative engine optimization platform as an entirely new channel, and we're helping enterprises with it. And it's why we believe that those frontier models are going to inform the agents, which are going to then go off and do the commerce on behalf of individuals. So if you look at what instinct's doing, you look at what meta's doing with... I'm using it, the name escapes me. Could look right on my That's [00:28:34] S1: on OpenAI or like Grok. [00:28:37] S0: No, Muse. I was looking for Meta. Yeah, yeah. But you could look at my phone and you could see, I love them all. It's great. I would tell you that Dots is incredible. I think people are sleeping on it. And I think the big difference with Dots is if you get the enterprise version, you can integrate it into your enterprise grade software versus inference. So I find Muse is really good on e commerce. I think Instinct is incredible from a conversational perspective, because I'm an iMessage guy anyway, and it's fully integrated into their API. I don't know how they got permission to do that, but it's incredible. And Dots has been really great. I'm getting up to speed on it because it's a little newer. But I think the automation of a lot of the stuff that we spend a lot of time on is coming.
00:28:37 · David Steinberg, Guillaume Moubeche
[00:28:37] S0: No, Muse. I was looking for Meta. Yeah, yeah. But you could look at my phone and you could see, I love them all. It's great. I would tell you that Dots is incredible. I think people are sleeping on it. And I think the big difference with Dots is if you get the enterprise version, you can integrate it into your enterprise grade software versus inference. So I find Muse is really good on e commerce. I think Instinct is incredible from a conversational perspective, because I'm an iMessage guy anyway, and it's fully integrated into their API. I don't know how they got permission to do that, but it's incredible. And Dots has been really great. I'm getting up to speed on it because it's a little newer. But I think the automation of a lot of the stuff that we spend a lot of time on is coming. [00:29:31] S1: And you talked about the acquisition of Senso recently. I know you've done about 19 acquisition in nineteen years. [00:29:38] S0: It's probably more, but yeah, I joke we've done 19 acquisitions in nineteen years. It's highly probable there'll be a twentieth. But we do acqui hires. We're doing little deals all the time. But to your question, I'm sorry.
00:29:38 · David Steinberg, Guillaume Moubeche
[00:29:38] S0: It's probably more, but yeah, I joke we've done 19 acquisitions in nineteen years. It's highly probable there'll be a twentieth. But we do acqui hires. We're doing little deals all the time. But to your question, I'm sorry. [00:29:52] S1: What would be like the top three lessons you've learned from integrating companies successfully? Like I've acquired like a couple, and I think it's always like hard, you know, like to define, like how does you make it a success? How do you, like, make sure that the the the best people in the team also stay? Like... Or if it's entrepreneurs to incentivize them enough for the long run? Like, I'm curious to see, like, what's your method and strategy about it?