Rippling now wants to be the entire data stack

Parker Conrad wants you to believe that a significant portion of data analytics belongs in human capital management systems — a claim that puts Rebling, which started as an HR software company, in a niche to compete directly with custom business intelligence tools.

The idea is that the modern data set — the set of tools that companies currently jury-rig from multiple vendors — can be combined into a single tool. Simply moving data from your various business systems into a warehouse is a huge industry in itself; This is what companies like Fivetran and Airbyte do. You need somewhere to store and query it, like Snowflake; Then something to convert and clean it up, like dbt Labs; Then a Tableau-like visualization layer on top.

Conrad’s argument is that Rippling brings it all together in one system and wraps it in something others lack: a built-in understanding of your organization, a constantly evolving reporting structure, and everything that’s affected when any metric moves up or down. That’s what The data cloud rippleswhich will be officially launched Thursday morning, is designed to deliver.

To see it in action, Conrad shares his screen from his office in San Francisco, then offers a window into what Rippling found when it ran the product on its workforce.

“There were employees who would do things like: ‘Claude is very helpful to me — he analyzes my calendar and my email and comes up with a plan for me,’” he says. “This person was spending an average of $30,000 a year on this.”

No one had done anything wrong, he quickly added, but the return on investment simply wasn’t there. It’s the kind of discovery that most companies currently don’t have a way to come up with.

He then shows me a live dashboard he created by simply asking Rippling AI to analyze his company’s most recent compensation review cycle—distributions of performance ratings, promotion rates by department, and salary ratios, all drillable down to the individual level. Then he pulls out another folder, this one sized from a Salesforce reference support ticket with employee scheduling data — enough to show, at a glance, which teams are sinking and which aren’t. He notes that the registration team is severely understaffed. The travel team has more than twice as many unresolved tickets as the platform team.

But the example Conrad seems most excited about is one that’s closer to the main concern many CEOs share right now: spending AI tokens. It displays a dashboard that combines data from Anthropic usage logs, pull request data from GitHub, and Rippling’s own performance ratings to identify which engineers are actually getting value from their AI tools and who are burning money without showing much for it.

“High performers spend more, which is kind of what you’d expect,” Conrad says. But the dashboard also flags engineers who have high spending and high rejection rates from their peers in code reviews — these are the people who are most often asked by their colleagues to redo something. “If your colleagues are asking you to go back and do it all the time, maybe you’re just generating a lot of neglect,” he says.

The analysis has already prompted Rippling to lower spending limits for some employees. The product can also be configured to alert managers — or automatically stop access — when employees exceed a spending limit.

On the issue of the impact on Reibling’s own margins when customers exceed their token allocations, Conrad doesn’t elaborate — “It’s kind of early,” he says — but he dismisses the idea that Reibling is subsidizing customer usage. “We’re not losing money,” he says, adding that the goal is to keep money “as accessible to customers as possible.” The base SKU, with Rippling AI, is priced around $20 per month, with usage-based fees charged for heavier consumers. It is currently used by about 560 companies, and new revenue from the product amounts to approximately $5 million to $7 million per month.

As for the AI ​​models that actually power Rippling’s growing AI portfolio, Conrad says the company has a new favorite at the moment. “We’ve actually moved a lot of things from Anthropic to OpenAI recently,” he offers, calling the OpenAI 5.5 model “better and more cost-effective” for what Rippling does. He is also careful to note that the balance continues to shift and the company uses different models for different tasks.

Rippling Data Cloud is the most notable release this week, but it’s not the only one. Earlier this week, the company also announced Business Banking, which offers a high-yield checking account and same-day payroll processing, a feature that Conrad described as eliminating the mental burden of managing two schedules at once. Most payroll systems require processing two to four days in advance; Rippling’s banking product enables businesses to run payroll on the day employees are paid, with changes accepted as late as 1pm on payday.

It’s a facility thrown into territory occupied by fintech companies like Ramp, which just raised $750 million at a $44 billion valuation — nearly triple the $16.8 billion valuation Rippling investors assigned to the company last year — and which has positioned itself as a financial operating system for companies navigating the costs of artificial intelligence. Conrad welcomes the comparison, noting that Riebling’s banking business is currently much smaller than Ramp’s but is “growing very quickly and doing very well,” and that “there are some advantages to centralizing all of this.”

Overall, Rippling is still about two years away from positive cash flow, Conrad says, spending 45% to 50% of its revenue on R&D compared with about 8% to 9% spent by public-market HR companies like Paylocity and Paycom. In other words, the cost of building everything in-house is the point, and the payoff is a system that can easily answer questions without relying on four different vendor groups to do so.

As for the IPO, Conrad made it clear that he is in no rush, even with the window wide open at the moment. “Public markets have become a retirement community for slow-growth companies,” he says, adding that he is “not religious one way or another,” even if it seems quite the opposite. For now, he adds emphatically: “We’re not going public. Not even with a wink, wink.”