Datarails AI Agents are organized into three specialized roles: Strategy, Planning, and Reporting. Each agent is designed for a specific type of finance work and utilizes guided flows tailored to that context.
Strategy Agent
The Strategy Agent helps finance leaders think ahead, frame decisions, and guide the business. It focuses on big-picture questions, trade-offs, and strategic direction.
Role and Key Value
Role: Supports leadership conversations by turning data into perspective and options rather than just operational detail.
Key Value: Helps leaders make better strategic decisions and communicate them clearly by converting financial data into executive-ready insights and recommendations.
Common Use Cases
Exploring investment or cost-optimization opportunities.
Understanding the financial impact of entering new markets or launching products.
Comparing strategic scenarios and trade-offs.
Preparing board and executive-level materials.
Creating concise decision summaries.
Typical Outputs
PowerPoint presentations for leadership and board discussions.
PDF summaries for executive decision-making.
Charts and widgets to visualize trends and strategic insights.
Planning Agent
The Planning Agent supports ad-hoc forecasting, scenario analysis, and forward-looking FP&A work. It helps you explore “what if” questions without needing to rebuild full models.
Role and Key Value
Role: Focuses on short- to mid-term planning needs, helping teams test assumptions and build flexible planning structures.
Key Value: Enables fast, ad-hoc forecasting and scenario analysis. It allows you to prepare for upcoming changes and validate planning ideas through conversation.
Common Use Cases
Building ad-hoc forecasts based on recent actuals.
Exploring scenarios and sensitivities.
Testing the impact of changing assumptions.
Structuring planning logic for decision support.
Validating and refining planning ideas.
Typical Outputs
Excel reports with Datarails-connected formulas.
Ad-hoc forecasting datasets.
Charts and widgets to compare scenarios.
Reporting Agent
The Reporting Agent helps explain what happened and communicate performance with confidence. It focuses on analyzing actual data and exploring variances.
Role and Key Value
Role: Focuses on analyzing real actual data, creating trusted outputs, and telling the story behind the numbers.
Key Value: Makes it easier to analyze performance, investigate anomalies, and generate insights quickly.
Common Use Cases
Creating ad-hoc reports comparing actuals to budget or forecast.
Exploring variances by department, account, or project.
Investigating anomalies and unusual patterns.
Building controlled expense analyses.
Drilling down from summaries to detailed data.
Typical Outputs
Excel reports with Datarails-connected formulas.
Insight reports with narrative explanations.
Charts and widgets for dashboards.
PDFs and PowerPoint decks for reporting.
Frequently Asked Questions (FAQ)
Do I need to choose the right agent before starting? AI Agents are designed to guide you, but starting with the right agent (Strategy, Planning, or Reporting) helps ensure the conversation stays focused on your specific goal.
Can I drill down into the data behind an answer? Yes. The Reporting Agent can guide you from high-level summaries into detailed views—such as departments, accounts, or transactions—to help explain what is driving the results.
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