Datarails Raises $70M Series C as AI Becomes Core Infrastructure for Finance Teams

Datarails has raised $70 million in Series C funding, bringing its total capital raised to $175 million. The round was led by One Peak, with participation from Vertex Growth, Vintage Investment Partners, Zeev Ventures, Innovation Endeavors, Qumra Capital, ClalTech, and several returning investors.

The financing comes amid strong operational momentum. In 2025, Datarails reported 70% year-over-year revenue growth and expanded its global workforce to more than 400 employees. The company now expects to reach $100 million in annual recurring revenue next year, positioning it among a growing cohort of finance software providers moving from functional tools into broader operating platforms.

An Excel-Native Bet on How Finance Actually Works

A defining element of Datarails’ strategy is its decision not to replace Excel, but to build around it. Despite years of attempts by software vendors to move finance teams away from spreadsheets, Excel remains the default interface for planning, forecasting, and reporting. Internal research cited by the company shows that nearly all finance professionals spend several hours a day inside Excel, and younger generations expect it to remain central to their workflows.

Rather than forcing a behavioral shift, Datarails treats Excel as the front end while consolidating data, controls, and intelligence behind the scenes. Its platform connects Excel models to structured financial and operational data, reducing manual reconciliation and version-control issues without changing how teams work day to day. This approach has helped Datarails gain traction with finance organizations that want modernization without disruption.

From FP&A Tool to Finance Operating System

Originally known for its focus on financial planning and analysis (FP&A), Datarails has expanded into what it now describes as a finance operating system. The platform spans FP&A, month-end close, cash management, and spend control, bringing together data that traditionally lives across disconnected systems.

More than half of the company’s growth in 2025 came from products launched within the past year. These include a month-end close solution designed to provide visibility into close status and dependencies, and a cash management product that connects directly to bank data to support liquidity forecasting and real-time cash visibility. The expansion reflects a broader shift in the market toward unified finance platforms rather than single-purpose tools.

AI Agents Built on Internal Data, Not Generic Prompts

Alongside the funding announcement, Datarails introduced new strategy, planning, and reporting AI agents. Unlike general-purpose AI tools, these agents are purpose-built around each customer’s internal data, spanning ERP, CRM, HRIS, and Excel models. The goal is to make AI outputs directly usable for finance workflows rather than experimental.

The agents are designed to answer questions that finance teams routinely face, such as identifying drivers of profitability changes, testing forecast scenarios, or explaining budget variances. Outputs can be generated as board-ready PowerPoint slides, PDFs, or Excel files, aligning with how finance teams communicate results internally.

This focus on data grounding and security reflects ongoing concerns among CFOs about accuracy, confidentiality, and auditability when using AI in financial contexts. By constraining AI agents to curated internal datasets, Datarails is attempting to balance automation with trust.

Why Investors Are Leaning Into Finance Infrastructure

From an investor perspective, the appeal lies less in flashy AI features and more in infrastructure leverage. Finance teams operate at the intersection of compliance, strategy, and execution, making reliability and data integrity non-negotiable. Platforms that can consolidate data and embed intelligence directly into existing workflows are increasingly viewed as foundational.

The Series C round also gives Datarails flexibility to expand geographically across North America and EMEA, increase R&D investment, and potentially pursue acquisitions. As finance software markets fragment across niche vendors, consolidation has become a recurring theme, with larger platforms seeking to absorb adjacent capabilities rather than integrate them piecemeal.

What This Signals for the Future of the CFO’s Office

Datarails’ raise highlights a broader shift in how AI is being adopted inside finance organizations. Rather than treating AI as an add-on feature, vendors are embedding it into the core data layer that powers planning, reporting, and control. In this model, AI becomes less about automation for its own sake and more about compressing decision cycles and reducing friction between insight and action.

The continued dominance of Excel suggests that transformation in finance will be evolutionary rather than revolutionary. Platforms that respect entrenched tools while quietly modernizing the underlying infrastructure are likely to see faster adoption than those demanding wholesale change.

Looking ahead, the CFO’s office is increasingly positioned as a strategic hub rather than a reporting function. As AI-driven insights become standard, the differentiator will be how well platforms unify data, preserve trust, and integrate into real-world workflows. Datarails’ latest funding round suggests that investors see this layer of finance infrastructure as both durable and central to the next phase of enterprise AI adoption.