Maximor AI Delivers Audit-Ready Agentic Finance Automation

Two former Microsoft executives, Ramnandan Krishnamurthy and Ajay Krishna Amudan, have launched Maximor, a startup emerging from stealth with $9 million in seed funding to challenge the persistent reliance on spreadsheets in mid-market finance. The new company introduces a platform powered by a network of AI agents designed to automate complex financial workflows like revenue recognition and month-end close. This development directly targets what the founders call “Excel-led finance”—a widespread practice of manual data reconciliation that creates inefficiencies and operational risk. The core of the Maximor platform, which it describes as providing “Audit-Ready Agentic Automation,” is a system that embeds compliance and real-time data visibility into a company’s financial backbone, aiming to shift teams from manual data entry to strategic oversight.
The news that former Microsoft execs launch AI finance company represents a significant new entry in the financial technology sector.
Key Points
- Maximor has launched with $9 million in seed funding to automate mid-market finance using a network of AI agents.
- The platform’s human-in-the-loop design assigns AI to data preparation and humans to final review for audit-ready compliance.
- Early client Rently documented a reduction in its month-end close process from eight days to four after implementation.
- The system integrates with existing ERPs, CRMs, and accounting software to create a unified, real-time financial data source.
Breaking Excel’s Financial Chokehold
For many mid-sized companies, sophisticated ERP and CRM systems still feed into a final, vulnerable bottleneck: the manual spreadsheet. As highlighted by TechCrunch, finance teams frequently export transactional data into Excel, using functions like VLOOKUP to reconcile figures across disparate systems. This approach perpetuates data silos and introduces a high risk of human error.
Maximor’s architecture directly confronts this by employing a network of specialized AI agents. These agents connect to a company’s existing software stack, including ERPs like NetSuite and Intacct, accounting tools such as QuickBooks and Zoho Books, CRMs, and payroll systems. Instead of periodic data dumps, the agentic AI for mid-market finance continuously pulls transactions, unifying operational and financial data into a single source of truth in real-time. This continuous reconciliation process is designed to automatically generate workpapers and auditable trails, effectively creating what the company calls an “AI-Native” finance function .
The company’s goal is for Maximor AI to replace Excel as the default tool for complex reconciliation.

Humans at the Helm, AI at the Wheel
Maximor’s approach acknowledges the high stakes of financial accuracy by building its system around a human-in-the-loop model. The platform is designed so that human accountants act as reviewers and validators for the work performed by the AI agents. CEO Ramnandan Krishnamurthy described this to TechCrunch as a digital parallel to traditional accounting teams, where junior staff—the AI agents—handle preparation, and senior managers—the human reviewers—focus on oversight. This design is central to the news about human-in-the-loop AI for finance, balancing automation with accountability.
Early results substantiate the platform’s claims. For example, proptech firm Rently reported cutting its month-end closing process from eight days to four and avoided hiring two additional accountants. The implementation also redirected nearly half of the team’s time toward more strategic initiatives. On its website, Maximor quantifies its platform’s impact , stating it can unlock 40% of a finance team’s capacity for strategic work, reduce staff hours on repetitive tasks by 90%, and decrease exceptions found during audits by 75%.
The ability to export fully reconciled data into Excel serves as a practical bridge for teams and auditors accustomed to spreadsheet-based workflows.
Microsoft DNA Meets Financial Complexity
The credibility of Maximor’s vision is significantly bolstered by its founders’ backgrounds at Microsoft. CEO Ramnandan Krishnamurthy was involved in driving customer adoption for Azure Open AI and worked on data integration products like ‘Azure Synapse Link’, a background detailed on his profile at The Org. This experience with large-scale AI and data unification provides a strong technical foundation for the company. CTO Ajay Krishna Amudan’s work on revamping Microsoft’s own internal revenue systems adds deep domain expertise in corporate finance challenges.

Investor confidence is demonstrated by the $9 million seed round led by Foundation Capital. The round also includes angel investors who are CFOs and finance leaders from companies like Ramp, Gusto, and MongoDB, providing strong industry validation. Maximor is targeting mid-market companies with revenues of $50 million or more, a segment often underserved by existing solutions. By already serving customers in the U.S., China, and India and supporting both GAAP and IFRS accounting standards, the company is positioning itself as a global solution from its inception, according to its launch announcement.
Rewriting the Financial Playbook
Maximor’s launch marks a notable development in applying agentic AI to corporate finance. By combining a sophisticated AI framework with a pragmatic human-in-the-loop design, the company addresses the critical barriers of trust and accuracy that have historically slowed AI adoption in this risk-averse field. The emphasis on creating “audit-ready” outputs directly tackles a primary concern for any finance department. If the platform continues to deliver on its initial results, it demonstrates a clear path for transforming the role of finance professionals from data reconcilers to strategic business partners.
The key question now is how quickly this model of supervised automation will become the standard for the modern finance team.
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