Is Your AI Actually Worth What You're Spending? with Parker Conrad

**Connie Loizos** (0:01)
Hi, I'm Connie Loizos.

**Alex Gove** (0:02)
And this is Alex Gove.

**Connie Loizos** (0:03)
And this is Strictly VC Download.
Hi, and welcome back to Strictly VC Download. Today's guest is Parker Conrad, the founder and CEO of Rippling. When we last had Conrad on the show back in 2024, the company had just raised $200 million at a $13.4 billion valuation, and Rippling was leading the return to office charge in San Francisco. A lot has happened since then, of course. The company has raised another $450 million at a $16.8 billion valuation. It's crossed a billion dollars in annualized revenue. Today, Conrad joins us to talk about Rippling's latest product launch, which is called Data Cloud. It's a project that's been roughly three years in the making, as you will hear him explain. We discuss what Data Cloud means for customers and why he believes that AI becomes dramatically more useful when it is paired with an organization's people data. We also get into how Rippling is managing its own AI spending, and why the company is expanding into banking and financial services. We also talk a little bit about fundraising and the IPO market, and of course, we discuss the ongoing legal battle between Rippling and Deel. We always really enjoy talking to Conrad. We hope that you will enjoy the conversation as well, and we'll see you back here next week.
Thank you for making time for us today. Okay, so I know we're going to be talking about a bunch of things. Let's start with your news about your data cloud. Maybe let's start with the core insight behind data cloud. What problem does it solve for your customers?

**Parker Conrad** (1:48)
There's this sort of central understanding of your org that's really important. And your org both as it exists today, but also as it's been changing over time. And so we built this thing that is basically the modern data stack, but all in one system. And so Rippling for a long time has been building a lot of different systems in one, where today, if you're trying to look at data about your business, you need to make like four separate big enterprise purchases. You need to buy a system that people traditionally called ETL in order to like move data over. And that's like 5Tran and AirBite and stuff like that. And then you need to have a system like Snowflake that is where you store the data and sort of does all the compute on top of it. And then oftentimes you have something like DBT, which is how you take it. And once it's in there, you kind of munch it and change it. You transform it is the term that people call to sort of get it to a point where you can really look at it in the right ways.
And then you have like a BI tool like Tableau that sits on top of it where you can analyze the data. And what we did is we've combined like all four of those systems in one. We've been building this for about three years. It's been the biggest R&D initiative in the company. And the outcome of this is that Rippling is now, I think, the only system where you have all of this business context about your company, all of this data, and AI on top of it in one place. And that combination is really powerful. Like there's some incredible stuff that you could do. So even Anthropic, obviously hugely successful company, but one of the sort of issues with Anthropic and their product is there's no data stack underneath Anthropic. And so they're constantly sipping data through a straw via like MCP connections or sort of whatever they can get in real time out of an API.
And it's really inefficient because with AI, what we have found is that AI is useful to your company in rough proportion to the sort of volume of data that it can access. And so you give it small amounts of data through a straw and it can do some pretty cool stuff. But man, if you pipe data into an LLM through a pipe that's a mile wide and a mile high, you know, it's just, holy crap, the stuff it can do is really transformational. And that's what we've seen.

**Connie Loizos** (4:03)
I understand what you're saying about Cloud. You are built on top of the LLMs yourself, like Cloud and ChetGPT or maybe like a bunch of them.

**Parker Conrad** (4:11)
You know, underneath the hood, we're using a bunch of different models. So we've actually moved a lot of stuff from Anthropic to OpenAI recently.

**Connie Loizos** (4:19)