For the modern CFO, the hardest part of the job is often not the math – it’s the storytelling. After the books are closed and variances calculated, finance teams spend days, sometimes weeks, manually copy-pasting charts into PowerPoint slides to explain why the numbers went away.
Today, 11-year-old Israeli fintech company Datarails announced a set of new generative AI tools designed to automate "last mile" of financial reporting, allowing finance leaders to effectively "vibe code" Their way to a board deck.
Launching today alongside the company’s newly announced $70 million Series C funding round, the company’s new strategy, planning and reporting AI finance agents promise to answer complex financial questions with fully formatted assets, not just text.
A finance professional may now ask, "What is driving the change in our profitability this year?" Or "Why did marketing go over budget last month?" And the system will instantly generate board-ready PowerPoint slides, PDF reports, or Excel files containing the answers.
The deployment of these agents marks a fundamental shift in how "CFO’s office" Interacts with data.
beyond chatbot
The new agents promise to solve the fragmentation problem plaguing finance departments. Unlike a sales leader who lives in Salesforce or a CIO who relies on ServiceNow, the CFO doesn’t have one. "system of truth". Data is scattered across ERP, HRIS, CRM and bank portals.
A major obstacle to the adoption of AI in finance has been security. CFOs are hesitant to plug P&L data into public models.
DataRails solved this by leveraging Microsoft’s Azure OpenAI service. "We use OpenAI in Azure to ensure the privacy and security of our customers, they do not like to share data in [an] open llm," Gurfinkel noted. This allows the platform to use state-of-the-art models while keeping data within a secure enterprise perimeter.
DataRails’ new agents sit on top of the unified data layer that connects these disparate systems. Because AI is based on a company’s own integrated internal data, it avoids the hallucinations common in generic LLMs while offering the level of privacy needed for sensitive financial data.
"If a CFO wants to leverage AI at the CFO level or across organization data, they need to consolidate the data," Didi Gurfinkel, CEO and co-founder of DataRails, explained in an interview with VentureBeat.
By solving that consolidation problem first, DataRails can now offer agents that understand the context of the business.
"Now the CFO can use our agents to run analytics, gain insights, create reports… because the data is now ready," Gurfinkel said.
‘Vibe coding’ for finance
The launch leads to a broader trend in software development, where natural language prompts replace complex coding or manual configuration – a concept that tech circles call "Vibe coding." Gurfinkel believes this is the future of financial engineering.
"Very soon, CFOs and finance teams will be able to develop applications themselves," Gurfinkel predicted. "LLMs become so strong that in a single signal, they can replace entire product runs."
He described a workflow where the user could simply indicate: "That was my budget and actual statement from last year. Now make a budget for me for next year."
The new agents are designed to handle exactly these types of complex, multi-variable scenarios. For example, a user might ask, "What if revenues grow slowly in the next quarter?" And receive a scenario analysis in return.
Because the output can be delivered as an Excel file, finance teams can verify formulas and assumptions, maintaining an audit trail that typical AI tools often lack.
Ease of adoption: ‘anti-implementation’
For most engineering teams, the arrival of a new enterprise financial platform signals an impending headache: months of data migration, schema redesign, and the inevitable friction of forcing non-technical users to abandon their preferred workflows. DataRails has worked its way around this friction, which can best be described as "Anti implementation."
Instead of demanding a "rip and replace" Out of legacy systems, the platform embraces the messy reality of the modern finance stack. The architecture is designed to separate data storage from the presentation layer, effectively treating the organization’s existing Excel files as the frontend interface while DataRails acts as the backend database.
"We are not replacing anything," Gurfinkel explained. "Implementation can be very fast, ranging from a few hours to perhaps a few days".
From a technical point of view, this means "Engineering" The requirement has been almost completely eliminated. There are no ETL pipelines to build or Python scripts to maintain. The system comes pre-wired with over 200 native connectors – directly connected to ERPs like NetSuite and Sage, CRMs like Salesforce, and various HRIS and bank portals.
heavy lifting has been replaced by a "no code" Mapping process. A finance analyst, not a developer, maps fields from your general ledger to your Excel model in a self-service workflow. For modules like Month-End Close, the company clearly promises that "No IT support required," A phrase that probably comes as a relief to the overstretched CTO. Even complex setups, such as a new cash management module that requires banking integration, are usually fully operational within two to three weeks.
The result is a system where "technical debt" Talks generally associated with financial change have become obsolete. The finance team gets their due "single source of truth" Without ever asking engineering to provision the database.
From version control to vision control: a pivot that paid off
Datarails wasn’t always there "FinanceOS" For the AI era. Founded in 2015 by Gurfinkel with co-founders Eyal Cohen (COO) and Oded Har-Tal (CTO), the Tel Aviv-based startup spent its early years tackling a dryer problem: version control for Excel. The initial premise was to synchronize and manage spreadsheets across enterprises, but adoption was slow as the team struggled to find the right product-market fit.
Success came with a strategic pivot in 2020. The team realized that finance professionals did not want to replace Excel with a new dashboard; They wanted to fix Excel’s limitations – particularly manual consolidation and data fragmentation. By focusing on and adapting SMB finance teams "excel-native" Automation philosophy, the company found its progress.
This alignment led to rapid scaling, fueled by a $55 million Series A led by Zeev Ventures in June 2021, followed by a $50 million Series B led by Kumra Capital in March 2022. While the company faced headwinds during the tech recession – resulting in an 18% workforce reduction at the end of 2022 – it has since bounced back aggressively. By 2025, driven by a multi-product expansion strategy, Datarails had nearly doubled its headcount to more than 400 globally, which now includes month-end close and cash management solutions.
promote expansion
The new AI capabilities are backed by One Peak’s $70 million Series C injection with existing investors Vertex Growth, Vintage Investment Partners and others. The funding comes after a year of 70% revenue growth for DataRails, primarily driven by the expansion of its product suite.
More than 50% of the company’s growth in 2025 comes from solutions launched in the last 12 months, including Datarails Month-End Close (a tool to automate reconciliation and workflow management) and Datarails Cash Management (for real-time liquidity monitoring).
These products work "Plumbing" Which makes new AI agents effective. By automating month-end closing and integrating cash data, DataRails ensures that when a CFO asks the AI a question, the underlying numbers are accurate and up to date.
For Gurfinkel, the goal is to create a finance office "ai-native" Without forcing users to abandon their favorite tool: Excel.
"We are not replacing anything," Gurfinkel said. "We connect Excel so that Excel now becomes calculations and presentations."
With the launch of these new agents, DataRails is betting that the future of finance is not about learning new software, but about interacting with the data you already have.
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