Rillet, a two-year-old startup building the first truly AI-native accounting platform, has raised $100 million in Series C funding at a valuation of $1 billion, the company said Assets exclusive – join the ranks of AI-era unicorns fighting to displace decades-old enterprise software giants.
The round led by ICONIQ, with participation from returning backers Sequoia Capital, Andreessen Horowitz and Oak HC/FT, as well as new investors including Bain Capital Ventures, Sequoia Global Equities, Battery Ventures, FirstMark, Scale Venture Partners and Creandum, marks Rillet’s third fundraising in the past year and brings total funding to over $200 million. ICONIQ general partner Seth Pierrepont also joins Rillet’s board.
For Rillet co-founder and CEO Nicolas Kopp, the milestone is both personal and financial. In an interview with AssetsKopp described the company’s mission as freeing CFOs from the drudgery that keeps them glued to spreadsheets long after everyone else has logged off.
“CFOs are really struggling day in and day out. They can’t see their families on weekends,” Kopp said, because they have to spend so much time reviewing data and creating slideshows. He pointed out that he himself has a background in finance and accounting and that there are many people with accounting backgrounds in his company. 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 after jobs. That’s just not right,” he said, emphasizing that “expertise” is core to the company’s mission: “We’re positioning AI as a helper for that person and what they can achieve.”
From market launch to unicorn in two years
Rillet’s rise was quick, even by startup standards. Kopp said the company went public about two years ago and then raised a Series A led by Sequoia last summer closed a Series B just weeks later – a round in which new annual recurring revenue doubled compared to the previous quarter. The company says it doubled its new ARR again in the three months prior to this latest increase and now serves more than 600 customers.
These customers include some of the fastest-growing AI companies in the world – including Neuralink, Skild AI and Mercor – as well as a growing share of decidedly non-tech companies. About 40% of Rillet’s customer base now sits outside the technology and AI industries, Kopp said, spanning industries as diverse as waste recycling and film studios. He described the shift as evidence that AI-native financial tools are making their way into the broader U.S. economy. “That was really cool to see,” he said.
Mercor, in particular, has become a key reference customer: according to the company, its finance team uses Rillet’s AI agents to manage a business with over $2 billion in annual recurring revenue and a headcount of just three employees.
“Rillet is the clear leader in AI-native accounting infrastructure,” Pierrepont said in a press release announcing the fundraising. “What stands out is how customers are actually benefiting from this – multibillion-dollar companies operating with finance teams one-tenth the traditional size and continually closing their books.”
Take on the old giants
Rillet addresses the market directly: Outdated enterprise resource planning systems –oracle Fusion, JUICEWorkday, Microsoft’s Great Plains and NetSuite – among them – were built for a time before AI and are increasingly vulnerable to a challenger built on artificial intelligence from the ground up.
“Some of these giants that seemed untouchable” are now facing serious disruption, Kopp said, describing a wave of enterprise customers ditching legacy systems in favor of the Rillet platform. The main difference Kopp draws is architectural. Traditional ERP systems, he said, are designed for humans to enter and review data – a workflow that results in finance chiefs getting “dragged into the day-to-day details of the numbers” rather than focusing on strategy. In contrast, Rillet is agent-first, with AI systems capable of running hundreds of operations in parallel and handling much of the manual accounting work that traditionally took up finance teams’ time.
Kopp argues that this shift doesn’t just save time: It results in cleaner, more consistent financial data than human-led processes typically achieve, while creating what he calls a complete audit trail. “Proof of work shift is critical to business readiness,” Kopp said, arguing that Rillet is the only system on the market today that can combine deterministic accounting data with AI agents that handle complex end-to-end work.
Rillet paired this pitch with credibility-building efforts in the accounting industry. The company launched one earlier this year Alliance with EY for AI-native financial transformation, and it says it now works with more than half of them Accounting today Top 20 CPA Firms.
AI acceleration
Kopp attributes much of Rillet’s recent momentum to rapid improvements in the underlying AI models. He noted that accounting has “traditionally been a very old, cumbersome category” — one in which AI has emerged as an unexpected catalyst. “Especially in the last six months, things have started off in a good way,” he said, describing tasks that once took a person a full day to complete but now only take a few minutes. This creates more time not for job losses, but for strategic work at a higher level, he added.
This acceleration comes as the accounting profession faces a separate, slower-moving crisis: fewer graduates are embarking on careers in finance and accounting. Kopp sees this talent gap as an opportunity. He argued that AI agents can help offset the shrinking number of human accountants, even as business complexity – from price changes to competitive pressures – continues to increase.
According to Kopp, Rillet’s own product development has accelerated in step with its AI capabilities. He pointed to cases in which the company’s customer support team (many of them with accounting training) has dispatched feature requests within two to three hours of a customer raising them, as engineers increasingly develop tools in direct collaboration with the company’s in-house accountants. “That wasn’t possible six to twelve months ago.”
For this story, Assets Journalists used generative AI as a research tool. An editor checked the accuracy of the information before publication.