Barr Moses, Monte Carlo CEO on Agent Trust, AI Infrastructure and Data

Grace Gong (0:02)

We're live. Hi, Barr. Welcome to Venture with Grace.

Barr Moses (0:05)

Hey, it's great to be live. This is awesome. How are you, Grace?

Grace Gong (0:09)

I am good. Yeah, I was just streaming with, I was telling you about, I was just streaming with Alex five years ago. So yeah, I'm excited about our data master class today with USO.

Yeah.

Barr Moses (0:23)

It's a big day in the world for AI, for everything. There's a lot of stuff happening. It's a very interesting time. I know you got a lot going on Grace, so thanks for having me. I'm excited to be here.

Grace Gong (0:32)

Thank you. Thank you so much for taking the time.

I traveled to Jordan a while ago, as well as he spoke at our April summit. I was always curious about the progress of Monte Carlo, and obviously you guys did phenomenal jobs in the data space. I want to have you guys on. Before we dive into the conversation, I want to give a quick shout out to our amazing sponsor. This episode is brought to you by Nebius, the ultimate cloth for AI innovators. Nebius provides AI infrastructure. It can come down to combining reliability and speed with flexibility and engineering support unmatched by hyper-spellers. AI leaders like Meta, Shopify, and Higgsfield already partnered with Nebius to brand their AI workloads. Plus, Venture Back Startup can save up to $150K on compute costs when they apply for access. Visit nebius.com or nebius.com/startup to learn more. Okay, so I want to start with, Monte Carlo is like a agent trust platform that unifies data and agent observability to monitor, troubleshoot, improve production AI system, which is such a relevant conversation as when we were having the conversation with in our last episode, I was talking about, I feel like nowadays, because agents are performing longer tasks, so there is a lot of issue that may happen. And maybe we could start from, since you guys work with all the enterprise, and I want to start with, how do enterprise process these data as well as in the current climate, everyone's agent maxing.

We can start from how does the current platform works for Monte Carlo, and then we can dive into everything else.

Barr Moses (2:10)

Yeah, so much to talk about. Oh my God. Where do we get started? So I think you might know, and I know we interviewed here a few years ago, you might know Monte Carlo from our roots. We sort of are credited with creating a category called data observability. And this was about five, 10 years ago when enterprises just started something that they usually called modernization. That was really the word back then, modernization, the digital revolution. And on the backdrop of that, everyone started modernizing themselves, and as part of that, data become really important, and Monte Carlo created this category. Fast forward to today, there was a new revolution, of agentifying, and so enterprises are really looking to not just modernize, but adopt AI, and as part of that, you're right, they're agent maxing. And so, you know, Monte Carlo has sort of adapted with our customers and with the market to focus on what we call agent trust. And so our mission is to enable enterprises to adopt trusted AI, and I'll double click into a couple of those words. The first is double clicking to the word AI. Of course, data is a part of AI, but it's not enough, right? So we're definitely focusing on making sure that data can be trusted. But the AI itself is very important. Like if the model gets updated, if there is agent drift, there's a lot of things that can go wrong on the agent side of things. So we want to make sure that we have monitoring and observability and logging by design, right, from day one.

And, you know, double click on the word trust. That's probably the number one thing that's top of mind for CIOs and CTOs these days. It's probably two things. The first is, how do I ship AI to production? And the second is, how do I make sure it's secure? Obviously, with mythos and the recent hugging face attack, that has become very, very top of mind. So there's a lot happening, but just to bring a little bit of order to the chaos, Monte Carlo, by way of background, works with enterprises like financial industry companies like Morningstar.

We work with the Jets, we work with retail companies, we really work with sort of global 2000 companies to help them make sure that they can trust their agents and the data that feeds them. Now, maybe I'll give... Oh, sorry, go ahead.