Rillet, a two-year-old startup building what it calls the first truly AI-native accounting platform, has raised a $100 million Series C at a $1 billion valuation, the company told Fortune exclusively—joining the ranks of AI-era unicorns racing to unseat decades-old enterprise software giants.
The round, led by ICONIQ with participation from returning backers Sequoia Capital, Andreessen Horowitz and Oak HC/FT, plus new investors including Bain Capital Ventures, Sequoia Global Equities, Battery Ventures, FirstMark, Scale Venture Partners and Creandum, marks Rillet’s third fundraise in the past year and pushes its total funding past $200 million. ICONIQ general partner Seth Pierrepont is joining Rillet’s board as well.
For Rillet co-founder and CEO Nicolas Kopp, the milestone is as much personal as financial. In an interview with Fortune, Kopp described the company’s mission as freeing CFOs from the drudgery that keeps them chained to spreadsheets long after everyone else has logged off.
“CFOs really struggle day to day. They can’t see their families on weekends,” Kopp said, because they have to spend so much time reviewing data and creating slideshows. Noting that he has a finance and accounting background himself and that his company is full of people with accounting backgrounds, he said he wants AI to change that—not by replacing finance professionals, but by acting as their tireless back office. “Our message is not that we’re coming after jobs. That’s just not correct,” he said, stressing that “domain expertise” is core the company’s mission: “We’re positioning AI as a helper to that individual and what they can achieve.”
From launch to unicorn in two years
Rillet’s rise has been fast even by startup standards. Kopp said the company launched publicly roughly two years ago, raised a Series A led by Sequoia last summer, then closed a Series B just weeks later—a round that saw new annual recurring revenue double quarter over quarter. The company says it doubled its new ARR again in the three months leading into this latest raise, and now serves more than 600 customers.
Those customers include some of the fastest-growing AI companies in the world—Neuralink, Skild AI and Mercor among them—alongside a growing share of decidedly non-tech businesses. Roughly 40% of Rillet’s customer base now sits outside the tech and AI sectors, Kopp said, spanning industries as varied as waste recycling and movie studios, describing the shift as evidence that AI-native finance tools are crossing into the broader U.S. economy. “That’s been really cool to see,” he said.
Mercor, in particular, has become a marquee reference customer: According to the company, its finance team is using Rillet’s AI agents to manage a business scaling past $2 billion in annual recurring revenue with a headcount of just three.
“Rillet is the clear leader in AI-native accounting infrastructure,” Pierrepont said in a press release announcing the fundraise. “What stands out is how customers actually run on it—multibillion-dollar businesses operating with finance teams a tenth the traditional size, closing their books continuously.”
Taking on the legacy giants
Rillet’s pitch to the market is direct: Legacy enterprise resource planning systems—Oracle Fusion, SAP, Workday, Microsoft’s Great Plains and NetSuite among them—were built for a pre-AI era, and are increasingly vulnerable to a challenger built from scratch around artificial intelligence.
“Some of these giants that seemed untouchable” are now facing serious disruption, Kopp said, describing a wave of enterprise customers ripping out legacy systems in favor of Rillet’s platform. The core distinction Kopp draws is architectural. Traditional ERP systems, he said, were designed for humans to input and review data—a workflow that leaves finance chiefs “dragged down into the day-to-day minutiae of numbers” instead of focusing on strategy. Rillet, by contrast, is built “agent-first,” with AI systems capable of running hundreds of operations in parallel, executing much of the manual accounting work that traditionally consumed finance teams’ time.
That shift, Kopp argues, doesn’t just save time: it produces cleaner, more consistent financial data than human-run processes typically allow, while creating what he calls a complete audit trail. “Proving out the work layer is mission-critical for enterprise readiness,” Kopp said, arguing that Rillet is the only system that can combine deterministic accounting data with AI agents completing complex, end-to-end work in the market today.
Rillet has paired that pitch with credibility-building moves in the accounting establishment. Earlier this year, the company launched an alliance with EY for AI-native finance transformation, and it says it now partners with more than half of the Accounting Today top 20 CPA firms.
The AI acceleration
Kopp traces much of Rillet’s recent momentum to rapid improvements in underlying AI models. Accounting, he noted, is “traditionally a very old, stodgy category”—one where AI has emerged as an unexpected catalyst. “Especially in the last six months, things started lighting on fire in a good way,” he said, describing tasks that once took a human a full day now taking a couple of minutes. This frees up time not for job loss, but for higher-level strategic work, he added.
That acceleration comes as the accounting profession faces a separate, slower-moving crisis: fewer graduates entering finance and accounting careers. Kopp sees that talent gap as part of the opportunity. He argued that AI agents can help make up for a shrinking pipeline of human accountants even as business complexity—from pricing changes to competitive pressure—continues to increase.
Rillet’s own product development has sped up in step with its AI capabilities, according to Kopp. He pointed to instances where the company’s customer support team (many of them with accounting training) has shipped feature requests within two to three hours of a customer raising them, as engineers increasingly build tools in direct collaboration with the company’s in-house accountants. “That wasn’t possible six to 12 months ago.”
For this story, Fortune journalists used generative AI as a research tool. An editor verified the accuracy of the information before publishing.
