AI Agents Talking to AI Agents: Reinventing Commerce with Decagon CEO Jesse Zhang

**Elad Gil** (0:05)
Today, we're lucky to have with us at No Priors, Jessie Zhang. Jessie is the co-founder and CEO of Decagon, which provides customer service and other related AI for all sorts of different enterprises, including banks, telecom providers, airlines, and of course, many of the biggest and most important tech companies. Jessie Prior started Lowkey, which was acquired by Niantic, and we're very excited to have him join us today on No Priors. Jessie, thanks for joining us today on No Priors.

**Jesse Zhang** (0:29)
Thanks for having me.

**Elad Gil** (0:30)
Can you tell us a little bit about Decagon and why you started the company, how you started it, how you all got going?

**Jesse Zhang** (0:34)
Yeah, of course. So Decagon, for those who are not really familiar with us, we're an AI customer service agent. And so you can kind of think of us if we're working with a large bank or airline or just people that have large contact volume, the AI's job is to have a very engaging and personalized conversation with the user and resolve it, and save the company a bunch of money, and ideally drive more revenue in the future because folks are more engaged. And as we've grown, it's kind of becoming more and more of a, you got to think of a conversational UI for the brand, where it's how every user can interact with it. And we often use the term concierge to describe this, but that's what we do.

**Elad Gil** (1:11)
And you're working right now with some big banks, or some of the world's biggest banks, you're working with airlines, telcos, like you've actually gotten to very big customers very quickly. How did you go about doing that or how did it happen?

**Jesse Zhang** (1:21)
Yes. As you know, we started out mostly with the digital native companies, a lot of startups do that, and digital natives, of course, are much more willing to try out startups, they can move faster.

**Elad Gil** (1:30)
So that'd be like late stage tech companies and things like that?

**Jesse Zhang** (1:32)
Yeah, like Ripley, Innosha, and folks like them, they were great partners and they also just helped us iterate on the product a lot. So that's where we started. As we've gone on, I think just naturally, we're pulled up market just because of the demand.
As you might imagine, that's where most of the large contact volumes are. So we just have it a lot faster than we thought. And I would say a lot of these enterprise also moved a lot faster than we would have expected. So that's why we ended up there.

**Elad Gil** (2:01)
I think that's one of the underappreciated things about AI traction is a lot of companies are willing to try things in a way they weren't willing to before because it's such a big technology shift. And so all these markets are kind of open now that weren't before that would be much harder to do.

**Jesse Zhang** (2:13)
Yeah, I mean, another specific dynamic is that at the enterprise, it's becoming a lot more of a top down motion. So in the past, any of these technologies could have been just like one team trying to vet it or decide it. But now it's like an AI transformation. And the C-suite, the board, are all very big on how do we adopt AI. And customer service is often one of the biggest areas, or probably the most low hanging fruit. So that's how these conversations have progressed.

**Elad Gil** (2:41)
And how much of an impact are you having in terms of some of these teams? So I know that you're giving a lot of leverage to these customer service orgs. Are you making people two times more productive? Or I'm just sort of curious, is there a way to measure the outcome here?

**Jesse Zhang** (2:52)
Yeah, in most of the large enterprises, the first thing they'll measure is just what is the efficiency that you're gaining them. So whatever they're spending on their contact center or their operation, how much can you cut that down by? And we've done case studies now where folks have been able to cut that down by 60, 70%. That's like a great success case, right? Because it's like a very clear business case. You can show it to everyone. And then the sort of secondary thing, oftentimes folks will even put this at the same level, if not higher, is just the customer satisfaction. So you need to measure that and make sure that your customers are having a good time and more engaged, if not just like more also just happy than previously.