Datarails, a financial planning and analysis software company, is making a bold bet that AI will make the traditional FP&A tools it helped develop obsolete, and that it needs to disrupt itself before someone else does.
In response, Datarails is launching FinanceOS, an AI-native platform that the company calls a “financial operating system.” It’s a platform that allows finance teams to perform financial analysis using any AI tool, such as Anthropic’s Claude, OpenAI’s ChatGPT, or Microsoft Copilot, while maintaining the data management and audit trails they need.
“AI can build models, perform analysis, and generate reports much faster and much better than humans,” said Didi Garfinkel, the company’s co-founder and CEO. luck In an interview. “So all these tools that are focused on creating tools by and for humans are no longer relevant. Quite the opposite. They limit AI.”
That’s a provocative claim from a 10-year-old company that made a name for itself by solving what Garfinkel calls “Excel Hell,” the chaotic management of spreadsheets that finance departments rely on for budgeting, forecasting, and reporting. Datarails has built a platform that unifies data from accounting systems, HR platforms, CRMs, and other operational software into a single source of truth and connects that data to the Excel models finance teams already use. Datarails, based in Tel Aviv, Israel, has raised $175 million in venture capital funding to date, including a $70 million Series C funding round in January.
But Garfinkel said the advent of generative AI has changed what is possible and what is needed. AI models can generate sophisticated financial analysis in seconds, but CFOs can’t simply throw data into ChatGPT or Claude and trust the output.
“One of the challenges and issues that CFOs have with AI right now is trust,” Garfinkel said. He divides this into two aspects. It’s about trusting the data the AI works with, and trusting that the AI’s output is reproducible. The latter is particularly difficult because major AI models are probabilistic in nature and will not give the exact same answer to the same prompt every time.
Datarails hopes to address both of these issues with its new FinanceOS product. The system connects data from over 400 different sources (the “systems of record” that finance teams rely on, such as NetSuite, SAP, and Salesforce) and performs real-time financial integration of this data, including complex eliminations, allocations, and foreign exchange adjustments. The platform enables AI models to analyze this data using Model Context Protocol (MCP), a new open standard for connecting AI systems to external data sources.
Once a financial model is built using AI, FinanceOS allows customers to lock it in place, ensuring that the underlying data is updated from period to period while keeping the financial model consistent.
The timing may be right for Datarails. According to a Gartner study cited by the company, AI adoption in corporate finance remains essentially flat, increasing by just one percentage point from 58% in 2024 to 59% in 2025, while 91% of finance teams report a low impact from AI tools. Data quality and availability were cited as the most common barriers.
With investors hyper-focused on how AI challenges the traditional pay-per-user license business model of Software-as-a-Service vendors, Datarails is leaning in a disruptive direction. Garfinkel said this makes sense because we are moving to a usage-based pricing model and software is increasingly being used by AI agents rather than humans.
“Total spending on software is going to be even higher and will increase,” he says. “But there will probably be fewer people. AI can do more. So if you take this equation, you get one very clear conclusion: CFOs pay for value.” Garfinkel said pay-as-you-go pricing represents the value a company gets from using a product.
Datarails positions itself not only as a product company, but also as a partner to help CFOs navigate their AI journey. The company plans to offer professional services, training, and custom agent development alongside FinanceOS. This is a recognition that, as Gurfinkel puts it, “the CFO’s office is the last to adapt to new technology.”
This hands-on approach is the same strategy pursued by other companies selling AI agent-based products to enterprises, including Salesforce, Anthropic, and OpenAI. These companies employ teams of “forward-deployment engineers” who help customers design agent workflows and configure AI systems, as opposed to the older model of SaaS companies that were primarily centered around customer self-service.
Gurfinkel was candid about the competitive environment, arguing that many of the industry’s oldest FP&A software vendors are struggling. “They’re already gone. They’re slow. They don’t have enough money or energy to rewrite the technology,” he said. New entrants like Abacum and Runway, which have invested heavily in sophisticated web interfaces and algorithmic workflows, face a different challenge. There has been a lack of investment in the data integration layer, which Gurfinkel believes is the new strategic high ground, forcing them to reinvent themselves.
The good news for these companies is that most have recently raised significant capital, giving them time to adapt, he said. “But it will be interesting to see how they react to this change,” he added.
He draws parallels between what he predicts will happen to financial professionals and what is already happening in software engineering, where AI coding assistants have transformed the way developers work. “No programmer is actually typing on a keyboard,” he said. “Nearly 100% of their code is written by AI, and I’m sure it’s exactly the same for the financial community.”
Datarails says FinanceOS is available immediately and will be fully operational within a few business days. Datarails’ existing FP&A, cash management, month-end close, and expense management products will continue to be available as managed solutions built on the same underlying platform.
