Ramp + Ledge Integration
With the Ramp integration for Ledge, expense and card data is automatically pulled and prepared for month-end close, so spend-driven reconciliations and accruals are ready for review, not rebuilt by hand.
Close expense-driven accounts without rebuilding spreadsheets every month
For most accounting teams, this still means exporting Ramp data, pasting it into Excel, rolling formulas forward, and manually rebuilding reconciliations and accruals each month. The work resets every close.
Ledge removes that rebuild. Ramp becomes a direct data source inside the close, and task-focused agents—purpose-built by finance—prepare the work automatically so your team starts in review, not data collection.
What makes Ramp + Ledge different
Ramp data is operational by default. For close, it needs to be structured into reconciliations, rollforwards, and journal entry support that tie directly to the GL. Ledge agents, built by finance, pull the exact Ramp data required for each close task and prepare Excel-native workpapers in the format your team already uses.
Card transactions, reimbursements, and AP activity change throughout the month. Late expenses, reclassifications, and approvals create period-over-period movement that must be reconciled and explained. Ledge agents rebuild Ramp-related schedules every close with fresh data, keeping reconciliations, accruals, and flux analysis aligned with what actually changed.
How the Ramp + Ledge integration works
Securely connect Ramp to Ledge in minutes using a native integration. Setup is fast, lightweight, and flexible enough to support multiple entities and accounts.
Use Ledge’s Agent Studio to configure how Ramp data supports your close. Describe the workflow in plain language—such as expense reconciliations, accrual logic, or spend rollforwards—and create a custom agent in minutes.
Each period, agents automatically pull fresh Ramp data, rebuild Excel workpapers with live formulas, and prepare reconciliations and draft entries. Your team reviews and approves instead of rebuilding.
Expense and card-driven close work, prepared automatically
Prepared work, not manual rebuilds
Ramp data is used to prepare reconciliations, accrual schedules, and flux analysis before review begins.
Excel-native outputs
Agents generate fully editable Excel workbooks with live formulas, rollforwards, and clear source traceability.
Review instead of preparation
Accountants focus on judgment, exceptions, and approval rather than exporting and stitching data.
Visibility and control
Ramp-related tasks are tracked alongside the rest of the close, with clear ownership, status, and dependencies.
Audit-ready by default
Source data, calculations, assumptions, approvals, and changes are captured as part of the close, not reconstructed later.
FAQ
Ramp is treated as an expense and spend data source that feeds agent-driven close workflows. It is not a standalone reconciliation tool.
No. Ledge works alongside your ERP and Ramp. Agents use Ramp data to prepare close work, while posting follows your existing ERP approval process.
Yes. Ledge is spreadsheet-native. Agents generate Excel workpapers your team can open, edit, and review.
No. Ledge is human-in-the-loop by default. Agents prepare the work; accountants review and approve before anything posts.
What is Ledge?
Ledge is an agent-driven close management platform where AI agents don’t just track progress—they execute close work under your team’s direction.
Each close task can have its own agent that pulls data from systems like your ERP, banks, HRIS, AP platforms, CRMs, billing systems, and expense tools like Ramp. Agents prepare reconciliations, schedules, flux analysis, and draft journal entries before the task is even opened.
Ledge combines close orchestration, Excel-native workpapers, and human-in-the-loop approvals in a single platform—so the close runs on prepared work, not manual rebuilds.
See the Ramp + Ledge integration in action
Request a demo to see how Ramp fits into an agent-driven close and how expense data becomes close-ready without added manual work.
