Data is Back: MongoDB, Databricks, Snowflake

**CJ Desai** (0:00)
What is happening right now, Molly, is that you see these hyperscalers, some of them are running out of capacity. So this large customer in Texas, speaking to them, they have really good partnership with one of the hyperscalers. They wanted to move more workloads in public cloud, and also some AI workload. And the hyperscalers said, sorry, we don't have a capacity. And they are one of the top 50 customers for that hyperscaler. So now they are saying, we were decommissioning this data center, CJ. We can't do that. So we are going to now run workloads on-prem, and we are going to run some AI workloads, whether it's data privacy issues or other issues. We are going to run those workloads. Frontier Labs are using us for a multitude of use cases. We cannot disclose which, what use cases.

**Molly O'Shea** (0:42)
There's only a handful. I wonder who they could be.

**CJ Desai** (0:44)
Because a lot of AI-native startups, whether it's Emergent, Base 44, Metal.AI, specifically ElevenLabs. When we look at the ElevenLabs story, they have north of 50 million agents, depending on when you look at it, all running on MongoDB. Data is the unsung hero and data is bad.

**Molly O'Shea** (1:13)
CJ, welcome to Sourcery.

**CJ Desai** (1:15)
It is fantastic to be here with you, Molly.

**Molly O'Shea** (1:18)
All the way in Paris.

**CJ Desai** (1:19)
All the way in Paris.

**Molly O'Shea** (1:20)
It's really funny, I was telling people about everyone that we're interviewing this week, and it just like, okay, where can you interview all the top Silicon Valley CEOs? It's in Paris, it doesn't make sense.

**CJ Desai** (1:32)
That does not make sense. At Scott at Cognizant, we were talking, and we said, next week should we meet in California? He said, yeah, that would be a good idea, rather than always meeting in Paris or other places. So I am with you, yes.

**Molly O'Shea** (1:46)
Scott was one of the first interviews that we did. And it was funny because we were talking about Devin and the comeback of Devin.
And the first task that Devin did was spin up MongoDB.

**CJ Desai** (1:59)
I was so proud. Scott said he couldn't sleep at night, that Devin could set up MongoDB, and he felt that was a great task by Devin.

**Molly O'Shea** (2:09)
Okay, so we, again, we're here at Raze. You were on the stage earlier with Laura from OpenAI. So what were you guys talking about?

**CJ Desai** (2:17)
Just, you know, Laura is very focused on, from the startup ecosystem, founders, what OpenAI does, how do they work with the founders, and specifically, what is the approach MongoDB has taken, because a lot of AI-native startups, whether it's Emergent, Base 44, both are wipe coding platforms built on MongoDB, but then you have also Metal.AI, specifically ElevenLabs, that is currently running all agentic workloads on MongoDB. So we talked about how do you truly partner with founders?
How do you stay close to them as they are scaling their enterprise or they are scaling just the hyper growth era? And what are some best practices in working with them when they need you the most? So that was basically the focus and the data layer is typically the unsung hero, but we feel that models and data both are needed to create a great agentic application. And we talked about that.

**Molly O'Shea** (3:24)
Everett Randall had just tweeted out something on the token economy and how much tokens and agents are creating more data. And then I tweeted underneath it. I don't know why I'm talking in tweets right now, but I tweeted beneath it, data is back and he said big data.

**CJ Desai** (3:39)
Big data.

**Molly O'Shea** (3:40)
So you are a winner, a downstream winner of everything that's happening in AI. And I think it was like a little unexpected too because people were just so focused on the models. But guess what? All these models and all these agents are creating so much data. So where does MongoDB fit in with the AI super cycle and all the agentic economy?

**CJ Desai** (4:02)
Yes. I would say the way I see the world is pretty simple. So many people say it, but they are truly not behind it. And here's what I say. Like people like to say companies, they like to say, oh, we are truly customer-obsessed culture, or we care about customers, customer-focused, but I'm really, really customer-obsessed. And in a typical week, Molly, I feel it's not a good week unless I have spoken individually to 10 to 12 customers, sometimes even more, even if it's a short week. So I'm constantly learning from customers on what they are trying to do with AI specifically. And when you look at MongoDB today, so MongoDB, Mongo stands for humongous, which most people don't know. So humongous database that as you scale, you should feel comfortable as an AI company that you can scale with MongoDB, right?