Datarails AI Connector brings the power of artificial intelligence directly into your financial planning and analysis (FP&A) workflows. It connects your Datarails data to AI platforms, allowing you to ask questions in natural language and get meaningful answers without manually pulling reports, building pivot tables, or writing complex formulas.
Whether you need a quick revenue update for a board meeting, want to compare actuals against budget, or need to investigate an unexpected expense, AI Connector helps you get the insights you need faster.
By connecting your financial data with the AI tools you already use, AI Connector makes it easier to explore your data, analyze performance, and make informed decisions.
How does the AI Connector work?
AI Connector securely connects your Datarails account to supported AI platforms using the Model Context Protocol (MCP). Think of MCP as a secure bridge that allows an AI assistant to interact with your Datarails data.
Here's how it works:
- Ask a question. Use natural language to ask a question, just as you would ask a colleague. For example: "What was our total revenue in Q1 2025?"
- Connect securely. Authenticate using your existing Datarails credentials through OAuth 2.0.
- Access your financial data. The AI uses Datarails-connected tools to discover and query available tables, fields, and account structures.
- Get actionable insights. Receive answers in the form of summaries, financial analysis, reports, or Excel files, depending on the platform and task.
No need to manually export data or explain your financial structure each time. AI Connector helps bring your Datarails data into the AI-powered workflows you already use.
AI makes finance faster. Datarails makes it reliable.
Our library of actions
AI Connector supports a range of financial analysis and reporting workflows. Here are some examples of what you can accomplish:
| Capability | What it does | Example prompt |
|---|---|---|
| Financial Summaries | Get an overview of revenue, expenses, and key financial metrics. | "Give me a financial summary for Q4 2025" |
| Data Extraction | Export financial statements and KPIs into Excel. | "Extract our P&L for 2025 to Excel" |
| Budget vs Actuals | Compare actual performance against budget and identify variances. | "How are we tracking against Q1 budget?" |
| Anomaly Detection | Identify unusual transactions, outliers, and potential data discrepancies. | "Are there any unusual transactions this month?" |
| Department Analysis | Analyze financial performance across departments and cost centers. | "Compare expense trends across departments" |
| Executive Dashboard | Create KPI dashboards with visualizations and financial summaries. | "Build me an executive dashboard for this quarter" |
| Audit & Compliance | Support audit preparation with financial reports and supporting evidence. | "Prepare audit evidence for Q4 revenue recognition" |
| Executive Insights | Identify financial trends and generate insights to support business decisions. | "What are the key trends I should present to the board?" |
| Reconciliation | Compare financial results across data sources and identify discrepancies. | "Reconcile our P&L totals against the KPI table" |
| DR.GET Formulas | Generate workbooks using live Datarails formulas. | "Create a P&L template with live DR.GET formulas" |
What differentiates our AI Connector
Connecting a generic AI tool to your ERP or spreadsheets may give you quick answers, but speed alone isn't enough for finance. You need numbers you can trust, controls your auditors accept, and a platform that understands your financial environment.
AI Connector brings the power of AI into your Datarails environment, backed by the governance, security, financial expertise, and support that finance teams need.
1. Your financial models are too valuable to rebuild
Your mappings, definitions, hierarchies, and financial models represent years of work. Rebuilding that foundation in a generic AI tool introduces unnecessary complexity and risk.
AI Connector works with the financial data already organized in Datarails, helping you preserve the structure and business logic your team relies on. Spend less time recreating your financial environment and more time putting your data to work. For more information, read Semantic Layer overview.
2. Governance AI can't skip
Financial data requires strict access controls. Datarails applies its permission framework to ensure users can only access the information they're authorized to see.
Your existing permissions, approvals, and controls remain central to how financial information is accessed. AI shouldn't create a separate path around the governance your organization has already established.
3. Every number should be auditable
Finance teams need more than an answer. They need to understand where the number came from and how it was calculated.
Datarails provides the financial data foundation and reporting capabilities to support traceability, including source data, version history, and sign-offs. This gives finance teams greater confidence in the numbers they use for reporting, forecasting, and business decisions.
4. Security you can trust
Your financial information deserves enterprise-grade protection.
Datarails is SOC 2 certified, with user authentication and encryption in transit. AI Connector builds on Datarails' security framework to help protect sensitive financial information while enabling AI-powered analysis.
5. Finance experts on your side
AI can accelerate financial analysis, but understanding the business behind the numbers still matters.
Datarails' implementation and Customer Success teams understand FP&A, financial reporting, budgeting, forecasting, and consolidation — not just software. You have experts who understand the workflows you're trying to improve and can help you get more value from the platform.
6. Support that knows your setup
When something goes wrong, you shouldn't have to start from scratch explaining your environment.
Datarails' support teams understand your financial data, integrations, models, and configuration. That context helps teams investigate issues more effectively and resolve problems with a better understanding of how your business operates.
The bottom line: AI Connector combines the speed and flexibility of AI with the financial foundation, governance, security, and human expertise that make Datarails a trusted platform for finance teams.
Available tools
AI Connector supports multiple AI platforms, giving your organization flexibility to choose the tools that best fit its workflows.
Regardless of the platform you choose, AI Connector provides a way to bring your Datarails financial data into your AI workflows while maintaining the applicable security and permission controls.
Frequently asked questions
Is my financial data secure?
AI Connector uses OAuth 2.0 authentication to establish a secure connection to Datarails. Users authenticate through their existing Datarails credentials, and access to financial data is governed by the applicable Datarails permission settings. Refer to the relevant platform-specific documentation for additional details about authentication and data handling.
Can AI Connector modify my Datarails data?
AI Connector is designed for querying, analyzing, and extracting financial information. Its available capabilities depend on the tools and permissions enabled for the connection. It does not automatically grant an AI platform permission to modify your Datarails data.
Do I need technical skills to use AI Connector?
No. You can ask questions using everyday language. For example, instead of building a report manually, you can ask: "Show me how our operating expenses compare to budget this quarter."
The AI helps translate your question into the appropriate data queries and analysis.
How accurate are the results?
AI Connector allows supported AI platforms to query your actual Datarails data rather than relying solely on information provided in a prompt or general AI knowledge.
Results depend on the underlying data, the question being asked, and the AI platform's interpretation. As with any financial analysis, we recommend reviewing important calculations and outputs before using them in financial reporting or business decisions.
Can I export results to Excel?
Yes. Supported workflows can generate Excel workbooks using Datarails data. Examples include P&L statements, financial reports, variance analyses, dashboards, and workbooks containing live DR.GET formulas. Available export capabilities depend on the AI platform and workflow.
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