Maximor said on August 5 that its revenue had increased 35-fold as the company expanded its artificial intelligence platform from task-level automation to end-to-end finance operations. The New York-based company said it has reached multi-million-dollar annual recurring revenue and now serves more than 25 customers across software, manufacturing, construction, hospitality and consumer goods. Its platform covers revenue recognition, billing, cash application, financial close, accounts payable and receivable, and multi-entity reporting. The announcement reflects a broader shift in enterprise AI: from software that assists employees with individual tasks to systems that execute complete business workflows under human oversight.

Finance is emerging as an important test case because accounting processes require not only automation but also judgment, traceability and audit controls. From task automation to workflow execution Conventional finance software typically automates specific stages of a process while leaving employees responsible for transferring information between enterprise resource planning, billing, banking and reporting systems.

Maximor’s approach is to operate across those existing systems without requiring companies to replace their core technology infrastructure. Its Audit-Ready AgentsTM can post journal entries, reconcile bank accounts, capture bills, request approvals, issue invoices and escalate decisions through workplace communication tools. The ERP remains the official system of record, while Maximor acts as an execution layer connecting workflows across the finance organization. According to the company, approximately 98% of transactions processed through the platform are completed without human intervention. Transactions involving unfamiliar circumstances or new judgment calls are escalated to finance teams, and the system then uses the resulting decision as precedent for similar cases.

“Finance teams are not short of software. They are short of systems willing to take responsibility for the work,” said Ramnandan Krishnamurthy, co-founder and CEO of Maximor. “The ERP records what happened. Maximor learns why it happened, executes what comes next and knows when to stop and ask.” Maximor said customers have reduced repetitive finance work by approximately 90% and audit exceptions by around 75%. The company added that its agents now operate across hundreds of corporate entities, thousands of bank accounts and millions of transactions each day.

At one global cybersecurity company, Maximor said it automated cash-management processes involving 10 legal entities, seven currencies and more than 20 banking relationships. The platform was deployed in less than four weeks and reduced the number of employees required to manage the process from 20 to five, according to the company. In another deployment involving a private equity-backed group with 14 business units and more than 30 subsidiaries, Maximor said its platform assumed responsibility for consolidation and back-office operations. The company reported that audit findings fell from seven to zero while related expenditure declined by approximately 70% over six months.

Customers generally begin by applying the platform to a specific accounting bottleneck before expanding it into additional finance operations. Maximor charges customers for workflows placed into production rather than using a conventional per-seat software licensing model. Finance becomes an enterprise intelligence layer Maximor was founded in New York in 2024 by Krishnamurthy and Ajay Krishna Amudan, who previously worked on enterprise and finance transformation initiatives at Microsoft, including projects involving Coca-Cola and Walmart. The company publicly announced a $9 million seed round in September 2025 led by Foundation Capital, with participation from Gaia Ventures, BoldCap and finance and technology executives.

The funding was intended to support product development, AI research and expansion across core financial-control workflows. “Maximor is moving the category from automation to autonomy,” said Ashu Garg of Foundation Capital. “The company’s growth shows that CFOs are ready to hand over complete workflows when autonomy comes with the control and auditability finance demands.” Maximor’s longer-term goal is to use the verified financial and operational data generated through these workflows to improve forecasting, benchmarking, capital planning and strategic decision-making. As AI systems move deeper into corporate operations, the competitive question is shifting from how many tasks they can automate to how much responsibility companies are prepared to delegate—and whether those decisions remain explainable and auditable. For CFOs, this could turn finance from a function primarily responsible for recording past activity into a real-time intelligence layer capable of showing how current business decisions may affect future financial performance.