Hyphenate Raises $45 Million Series A to Automate Finance with AI Agents

Hyphenate, a New York-based AI startup developing autonomous agents for corporate finance teams, has raised $45 million in Series A funding led by Nexus Venture Partners, with B Capital also participating. Existing investors Foundation Capital, BoldCap and Gaia Ventures joined the round, bringing the company's total funding to $54 million.

Founded in 2024 by former Microsoft finance transformation leaders Ramnandan Krishnamurthy and Ajay Krishna Amudan, Hyphenate is building AI agents that automate finance operations across accounting, treasury, billing, collections and reporting. The company plans to use the new capital to expand its agents into more finance workflows and strategic functions, with the longer-term ambition of helping CFOs make forecasting and capital decisions using transaction data.

The funding comes as companies explore ways to deploy AI beyond basic assistance and into business-critical operations. Finance is a particularly demanding area because automation must work within strict requirements for accuracy, internal controls and auditability.

Hyphenate's AI Agents Target Repetitive Finance Work

Corporate finance teams manage a wide range of interconnected processes, including revenue recognition, invoicing, collections, bank reconciliation, accruals, accounts payable, month-end closing and board reporting. These workflows often require employees to move information between systems, investigate exceptions and maintain records for audits.

Hyphenate develops agents across five main areas: order-to-cash, treasury, general ledger accounting, procure-to-pay, and reporting and insights.

Rather than requiring businesses to replace their existing enterprise resource planning systems, banks or other financial software, the platform integrates with the systems already in use. Its approach is designed to fit into existing finance operations instead of forcing companies to rebuild their technology stack.

The company also says its agents learn from each customer's historical spreadsheets, emails and system logs. By examining past workflows and cases that required manual intervention, the platform identifies recurring exceptions and uses resolved cases to inform future actions.

The resulting processes are recorded to support auditability. This is important for finance teams, where a task is not complete simply because an AI system has produced an answer. Companies also need to understand what happened, why a decision was made and how the outcome can be reviewed.

Revenue Grows 86-Fold in 12 Months

Hyphenate reports that its revenue grew 86-fold over the previous 12 months, while its customer base expanded 11-fold. Its customers include six publicly listed companies, among them HiBid, Groupon and Synthesia.

The company says its platform supports operations involving hundreds of legal entities, thousands of bank accounts and millions of transactions each day. It also reports a 90% reduction in repetitive finance work and a 75% reduction in audit exceptions among customers.

According to Hyphenate, customers use an average of six platform modules, and approximately 40% increase their usage during the first year. Some reportedly expand usage by two or three times.

These figures are company-reported metrics, not independently verified results in the supplied source. The announcement does not disclose absolute revenue, customer counts, profitability or the methodology used to calculate every performance improvement.

Even with those limitations, the reported growth suggests that the company is expanding beyond isolated AI experiments towards broader deployment within finance teams. The extent to which these results persist as the platform scales will be important in evaluating its long-term performance.

Why CFOs Remain Cautious About Autonomous AI

Finance is a high-stakes environment for AI adoption. Errors can affect financial statements, regulatory reporting, cash management and investor confidence. As a result, CFOs must balance the potential efficiency gains from automation against the need for oversight and control.

A study commissioned by Hyphenate in early 2026 found that 96% of surveyed CFOs viewed freeing their teams to focus on strategic work as a key benefit of AI. However, only 14% said they would completely trust AI to generate accurate accounting data independently, while 97% believed human oversight remained necessary.

These survey findings are reported by the company and should be understood in that context.

Hyphenate's approach is to provide agents with defined responsibilities while retaining evidence of their actions and involving people when judgement is required. This reflects a central challenge for enterprise AI: businesses need systems that can do more than recommend an action, but they also need boundaries and mechanisms for review.

For finance leaders, the practical question is not simply whether AI can perform an individual task. It is whether the system can execute a workflow reliably, handle exceptions, preserve audit trails and operate within existing controls.

Experienced Founders Bring Finance Transformation Expertise

Hyphenate was founded by Ramnandan Krishnamurthy and Ajay Krishna Amudan, both former Microsoft finance transformation leaders.

Amudan spent five years at Microsoft leading finance transformation, including a rebuild of the company's internal finance platform for metering, pricing, billing, collections and revenue reporting.

That experience is relevant to Hyphenate's focus on complex finance workflows. Large organisations often have multiple systems, interconnected processes and exceptions that do not fit neatly into standard automation rules.

The company previously raised a $9 million seed round in September 2025, led by Foundation Capital. Angel investors included Aravind Srinivas, CEO of Perplexity, and Tien Tzuo, CEO of Zuora.

The latest round gives Hyphenate additional capital to expand its technology and customer deployments as businesses evaluate more autonomous ways to manage finance operations.

Competition and the Race to Automate Finance

Hyphenate operates in an increasingly competitive market for AI-powered accounting and finance software. Several companies have raised substantial funding to automate financial workflows and bring AI agents into business operations.

The supplied report highlights Rillet, which raised $100 million in a Series C at a reported $1 billion valuation in August 2026; Basis, which raised $100 million at a reported $1.15 billion valuation; and Campfire, which raised $65 million in a Series B in October 2025. Other competitors include Stacks and French fintech unicorn Pennylane.

The competitive landscape suggests that investors see an opportunity to apply AI to finance workflows that have traditionally relied on human review and established enterprise software.

Hyphenate's focus on learning from a company's existing data and workflows, rather than requiring a wholesale software replacement, is central to its positioning. But it must demonstrate that its agents can maintain accuracy and auditability as they take on more complex responsibilities.

The challenge is particularly significant for public-company customers, whose financial operations must withstand audits and regulatory scrutiny. Speed alone is insufficient if errors require extensive manual correction.

Funding to Expand AI Across the CFO's Office

Hyphenate plans to use the $45 million Series A funding to extend its agents across more finance workflows and move into increasingly strategic areas of the CFO's responsibilities.

The longer-term ambition is to use transaction records as a foundation for forecasting and capital allocation decisions. If the company succeeds, its platform could move beyond automating repetitive tasks towards supporting the financial decisions that shape how businesses operate.

The opportunity is substantial, but execution will matter. Hyphenate must prove that its technology can handle more workflows without compromising financial controls, and that customers will continue expanding their use of autonomous agents as their responsibilities grow.

For enterprise leaders, the development illustrates a broader shift in AI adoption: from tools that assist employees to systems entrusted with completing operational work.

The next test is whether those systems can earn enough trust to operate reliably in one of the most sensitive functions of a business.