Bill Divvy Card + Ledge Integration
With the Divvy integration for Ledge, expense and card transaction data is automatically pulled and prepared for the month-end close—so Divvy-driven reconciliations and accruals are ready for review instead of rebuilt in spreadsheets.
Close expense accounts without rebuilding Divvy reports every month
For most accounting teams, this work is still manual. Finance exports Divvy transactions, clean and reformat data, reconcile card activity to the GL, and rebuild the same Excel workpapers every period. The close slows down because the same Divvy-related prep work resets each month.
Ledge removes that manual rebuild, giving finance tools to build their own AI agents to help with the manual work. Divvy becomes a direct data source inside the close, and agents prepare the work consistently every period.
What makes Divvy + Ledge different
Divvy is designed for spend control and approvals, not month-end accounting. With Divvy connected to Ledge, agents pull the exact transaction and expense data required for close tasks and prepare accounting-ready workpapers automatically—instead of relying on CSV exports and manual formulas.
Divvy activity changes every month as spend fluctuates, cards are issued, receipts arrive late, and transactions are reclassified. Ledge agents rebuild expense reconciliations, accrual support, and rollforwards each close with fresh Divvy data, so balances and explanations stay aligned with what actually happened.
How the Divvy + Ledge integration works
Securely connect Divvy to Ledge in minutes using a native, lightweight integration via OAuth or API access. Setup is fast and flexible enough to support multiple entities and card programs.
Use Ledge’s Agent Studio to configure how Divvy data supports your close. Describe the workflow in plain language—such as expense reconciliations, card accrual logic, or receipt completeness checks—and create a custom agent in minutes.
Each period, agents automatically pull fresh Divvy data, rebuild Excel workpapers with live formulas, and prepare reconciliations and supporting schedules. Your team reviews and approves instead of rebuilding.
Expense close work, prepared automatically
Agent-prepared work
Expense reconciliations, card transaction tie-outs, accrual support, and flux analysis are prepared before review begins.
Excel-native outputs
Agents generate fully editable Excel workpapers with live formulas, rollforwards, and clear source traceability back to Divvy activity.
Review instead of preparation
Accountants focus on judgment, exceptions, and approvals—not exporting reports and fixing spreadsheets.
Audit-ready by default
Source data, calculations, assumptions, approvals, and changes are captured as part of the close.
Full visibility and control
Divvy-driven tasks are tracked alongside the rest of the close, with clear ownership, dependencies, and status.
FAQ
Divvy is treated as an expense and card transaction data source that feeds agent-driven close workflows. It is not a standalone reconciliation or close tool.
No. Ledge works alongside your ERP and Divvy. Agents use Divvy data to prepare close work, while posting follows your existing ERP approval process.
Yes. Ledge is Excel-native. Agents generate Excel workpapers that 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 finance direction.
Each close task can have its own agent that pulls data from systems like your ERP, banks, HRIS, AP and expense platforms like Divvy, CRMs, and billing systems. Agents prepare reconciliations, schedules, flux analysis, and draft journal entries before the task is even opened.
Ledge combines close orchestration, Excel-native outputs, and human-in-the-loop approvals in a single platform—so the close runs on prepared work, not manual rebuilds.
See the Divvy + Ledge integration in action
Request a demo to see how Divvy expense data fits into an agent-driven close—and how month-end starts with prepared work instead of spreadsheets.
