

What is Drivetrain?
Drivetrain is a strategic finance platform that helps CFOs and finance teams consolidate data, build financial models, and forecast revenue. It connects with over 200 systems to automate reporting while providing real-time visibility into business metrics that finance leaders need for planning and decision-making.
What sets Drivetrain apart?
Drivetrain sets itself apart through AI-powered assistants that augment financial modeling by identifying key trends and anomalies in your data. The platform's unique focus on driver-based modeling helps CFOs understand the business levers that directly impact financial outcomes. Its combination of ML insights and intuitive visualization tools gives finance teams the ability to make smarter decisions backed by data.
Drivetrain Use Cases
- Financial modeling and forecasting
- Revenue pipeline analysis
- Cash flow management
- Headcount and capacity planning
Who uses Drivetrain?
Features and Benefits
- Consolidate financial data from over 200 systems including ERPs, CRMs, and billing platforms into a single source of truth for analysis and reporting.
Data Integration
- Build multi-dimensional financial models using plain English formulas and AI-powered forecasting capabilities.
Financial Modeling
- Track performance metrics and variances in real-time through interactive dashboards and drill-down reporting capabilities.
Real-time Analytics
- Plan and forecast revenue across new business, renewals, and expansions while aligning sales, finance and revenue operations teams.
Revenue Planning
- Monitor cash flow and runway in real-time while creating forecasts and scenarios to optimize working capital management.
Cash Flow Management
Drivetrain Pros and Cons
Pros
Seamlessly integrates data from multiple systems into a single source of truth
Significantly reduces time spent on financial reporting and forecasting through automation
Intuitive interface makes it easy for both finance and non-finance users to navigate
Highly responsive customer support team that quickly addresses issues and feature requests
Flexible customization options for reports and dashboards
Cons
Initial implementation and model setup requires significant time investment
Manual data cleaning needed to ensure accurate reporting
Limited self-service capabilities for data transformations
Creating new datasets requires support team assistance
Report formatting options are somewhat restricted