Rillet has raised a $100 million Series C at a $1 billion valuation, bringing total funding to more than $200 million. The AI-native enterprise resource planning company says the round will accelerate development of what it calls "Accounting Superintelligence," where AI agents perform increasingly complex finance work directly inside a real-time general ledger.
ICONIQ led the round, with participation from Sequoia, Andreessen Horowitz, Sequoia Global Equities, Bain Capital Ventures, Oak HC/FT, Battery Ventures, FirstMark, Scale Venture Partners and Creandum. The financing is Rillet's third fundraising round in approximately 14 months. ICONIQ General Partner Seth Pierrepont is joining Rillet's board.
The company plans to use the capital to expand its agentic finance platform, which is designed to let finance professionals and AI agents work together using the same accounting data, policies, controls and audit infrastructure.
Growth and customer traction
The financing follows a period of rapid commercial growth. Rillet said new annual recurring revenue doubled during the last three months, and its customer base has grown to more than 600 companies. The platform is used by publicly traded companies and fast-growing technology businesses, including Mercor, Function Health and Temporal.
After initially gaining traction among technology and AI companies, Rillet is expanding into additional industries including biotechnology, healthcare, fintech, logistics and professional services. Customers are using Rillet to replace legacy ERP systems including Oracle Fusion, SAP, Workday, Microsoft Great Plains and NetSuite.
From system of record to operating environment
Rillet's broader strategy is to reposition the ERP from a passive system of record into an operating environment where both humans and autonomous agents can perform financial work. Traditional ERP systems largely store completed transactions, while finance teams frequently perform analysis, reconciliation and operational workflows across spreadsheets and separate software products.
Rillet is attempting to vertically integrate those functions. Structured financial data flows through native integrations into the company's real-time general ledger, where AI agents can operate directly against the underlying accounting records. Those agents can perform finance tasks with access to accounting context while maintaining audit trails and requiring human approval where appropriate.
The company believes this structure provides an advantage over AI products that operate as separate software layers on top of legacy accounting systems. Rather than giving AI agents limited access to records stored elsewhere, Rillet is building its general ledger and AI functionality as a unified platform. The company describes that platform as a "harness" for modern finance organizations, allowing employees and AI agents to work from a continuously updated financial view of the business.
Finance teams retain visibility and approval authority while agents handle a growing share of operational accounting work. Rillet believes this model could allow corporate finance functions to operate continuously rather than relying primarily on periodic accounting closes. One example cited by the company is Mercor, where Rillet said its AI agents are helping a three-person finance team support a business scaling beyond $2 billion in annual recurring revenue.
Rillet is also working closely with accounting and auditing firms as it builds the platform. The company entered into an alliance with Ernst & Young earlier in 2026 focused on finance transformation, and said it is an official partner of more than half of the Accounting Today top 20 CPA firms. The partnerships are intended to help Rillet develop an AI-native accounting system capable of operating within the controls, compliance requirements and audit processes used by large enterprises.
"For the last two decades, the ERP has been treated as a system of record, a place to store what already happened. In the AI era, it has to become the operating layer for what happens next. Finance agents need more than access to data; they need to work inside the general ledger," said Nicolas Kopp, CEO and Co-Founder of Rillet. "Rillet is building that harness: one environment where humans and agents share the same financial truth, divide the work and keep every action auditable. The result is a finance function that can operate 24/7 and in real time."
Kopp also predicted that within two to three years, every company will run finance this way, agentic and in real time. He said Rillet is building the system of context and harness that will take them there.
Pierrepont said the firm's investment reflects how customers actually run on the platform. "In our view, Rillet is the clear market leader in AI-native accounting infrastructure. What stands out to us is how customers actually run on it, multi-billion-dollar businesses operating with finance teams a tenth the traditional size, closing their books continuously. We believe Rillet is the foundational infrastructure for the next generation of enterprises in the AI era, and we are proud to deepen our partnership."
The company ultimately sees agentic finance becoming a standard operating model in which AI systems work continuously alongside finance professionals while every action remains governed, reviewable and auditable. For finance teams evaluating where AI fits into their workflow, Rillet's model points to a shift from periodic closes toward continuous operations - and a growing expectation that finance staff will supervise agents rather than perform every transaction manually. Professionals tracking this space may want to review AI for Finance resources and consider an AI Learning Path for Accountants to understand how these tools change daily work.
Why this matters for finance professionals
The practical takeaway for finance teams is that ERP replacement is no longer just about migrating data - it's about deciding which accounting tasks can be delegated to agents and which require human judgment. Rillet's growth suggests that companies are already making that call at scale, with multi-billion-dollar businesses running lean finance teams on AI-native systems. Finance professionals who understand how to supervise and audit agent work will be better positioned as this model spreads beyond early adopters in tech.
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