Datarails Launches AI-Powered Platform to Modernise the CFO Stack
The FP&A software market has attracted significant capital over the past two years.
Traditional FP&A software is dead. That is the position Datarails is staking with the launch of FinanceOS, an AI-native platform the company describes as a financial operating system for the office of the CFO. Announced on March 10, the product connects to more than 400 data sources, performs real-time financial consolidation, and provides a governed data layer that allows finance teams to use AI tools of their choice, including Anthropic’s Claude, OpenAI’s ChatGPT and Microsoft Copilot, to build models, deploy agents and automate workflows on fully auditable data.
The launch comes weeks after the company closed a $70 million Series C funding round led by One Peak, bringing total capital raised to $175 million. The company reported 70% year-over-year revenue growth in 2025 and nearly doubled its headcount to more than 400 employees. Co-founder and CEO Didi Gurfinkel was blunt in an interview with Fortune about why the company is cannibalising its own category. AI can now build financial models and run analysis faster than any human, he said, making tools designed around manual human workflows obsolete. The question is no longer whether AI will replace traditional FP&A software. It is who builds the infrastructure that makes AI-driven finance reliable.
Why the Timing Matters
Datarails is entering a market where enthusiasm for AI far outpaces execution. According to Gartner’s 2025 AI in Finance Survey, adoption in corporate finance functions rose just one percentage point, from 58% in 2024 to 59% in 2025. More striking, 91% of finance teams reported low or moderate impact from their AI initiatives. Data quality and availability were cited as the most common obstacles. CFOs can feed data into any AI tool they want, but without audit trails, governance and real-time accuracy, the outputs are unreliable. That gap between ambition and infrastructure is precisely the problem FinanceOS is designed to close.
The broader market signals reinforce the urgency. NVIDIA’s 2026 State of AI in Financial Services report found that 73% of executives consider AI crucial to their future success, with active usage climbing to 65% across financial institutions. The 2026 Financial Executives Priorities Report showed that 64% of finance leaders now rank AI and machine learning as their top technology investment priority, up from 43% a year earlier. Yet only 15% of organisations consider themselves well or fully prepared. Bloomberg’s own research has found that 75% of European finance leaders believe falling behind on AI could result in direct loss of profitability or organisational obsolescence. A Wolters Kluwer survey projects the share of finance teams using agentic AI could rise from roughly 6% to 44% in 2026 alone. The demand is clear. The infrastructure to meet it has not kept pace.
What FinanceOS Actually Does
The core proposition from Datarails is that intelligence is no longer the bottleneck in corporate finance. Infrastructure is. FinanceOS sits between an organisation’s systems of record, such as NetSuite, SAP and Salesforce, and whatever AI tools the finance team chooses to use. It consolidates data from across the business, handles complex eliminations, allocations and foreign exchange adjustments, and exposes that unified data to AI models through a secure, governed layer. Once a financial model is built with AI, FinanceOS locks the model in place so it remains consistent while the underlying data refreshes each period. Role-based permissions, SOC 2 compliance and GDPR controls provide enterprise-grade security.
The company has also built professional services alongside the product, offering training, enablement and custom agent development. Gurfinkel described this as an acknowledgement that the CFO’s office is typically the last function in an organisation to adopt new technology, and that many teams will need hands-on support during the transition. The approach mirrors the “forward-deployed engineer” model adopted by companies like Salesforce and Anthropic when selling AI agent products to enterprises.
The Competitive Landscape
Datarails is not operating in isolation. The FP&A software market has attracted significant capital over the past two years. FloQast raised $100 million, DataSnipper secured $100 million and Ageras closed an $88 million round. Larger players from Workday Adaptive Planning to Anaplan are embedding AI features into existing platforms. The difference the company is attempting to draw is architectural. Rather than adding AI capabilities to a closed product, FinanceOS positions itself as an open data and governance layer that lets any AI tool operate on trusted financial data.
Gurfinkel argued that many legacy FP&A vendors are structurally vulnerable because their products and pricing were designed around human users performing manual tasks. As AI agents take over work that people used to do, per-seat pricing breaks down. Fewer humans generate more value, and the old model does not capture that. The company has adopted usage-based pricing for FinanceOS, tying cost to value delivered rather than the number of people logging in. It is a direct bet that the economics of finance software are about to shift permanently.
The move also reflects a wider trend in enterprise software. Accounting Today reported that 2026 will see a decline in standalone AI solutions and a rise in embedded AI that functions almost invisibly, not as the product itself but as the component that makes the product work. Vendors that treated AI as a feature bolted onto legacy architecture are finding that customers increasingly want open platforms that give them the freedom to choose their own AI tools. FinanceOS is built around that premise, offering connectivity to Claude, ChatGPT, Lovable, Cursor, Replit, Gamma and other leading AI tools out of the box.
A Profession Ready for the Shift
The talent crisis in accounting adds further tailwind. More than 300,000 U.S. accountants and auditors have left the field since 2019, and 75% of current CPAs are approaching retirement age. For Datarails, finance teams that cannot hire enough analysts to consolidate data manually are exactly the customers who need a governed, AI-ready data layer. The company’s Excel-native approach, which preserves the spreadsheet workflows that 99% of financial professionals use daily according to its own research, lowers the adoption barrier. Teams do not have to abandon their existing tools. They gain a reliable foundation beneath them.
What Comes Next
Datarails says FinanceOS is available immediately and can be fully operational within a few business days. Its existing FP&A, cash management, month-end close and spend control products remain available as managed solutions on the same underlying platform. The Series C funding will go toward expansion across North America and EMEA, increased R&D investment and potential acquisitions.
The broader bet is whether the market is ready to treat financial data infrastructure as a category in its own right, distinct from the applications built on top of it. Datarails is wagering that the shift to AI-driven finance makes the governed data layer more valuable than the tools themselves. With $175 million in total funding, 70% revenue growth and a product now live, the company has the capital and the conviction to force the question. Whether legacy vendors can respond fast enough is another matter entirely. The window to own the infrastructure layer of AI-driven finance is open, but it will not stay open for long.
