Close Automation
Accelerate month-end close through reconciliations and journal entry drafts. Use this page as a sample implementation pattern, then validate whether it belongs on your roadmap with an AI MRI.
How this pattern usually works.
Use this as a starting point. The AI MRI tells you whether this workflow belongs near the top of the backlog, what to fix manually first, and what needs to stay human.
- Identify reconciliations with large variances
- Retrieve evidence and propose JE drafts
- Route to controller with explanations
- Post with audit trails
- Inputs: GL, sub-ledgers, bank feeds
- Outputs: JE drafts, reconciled items, audit artifacts
- Materiality thresholds and approvals
- Data consistency and schemas
- Auditability and SOX alignment
Before and after.
Typical improvements observed when this kind of workflow is implemented well. Your baseline determines exact gains.
| Metric | Before | After |
|---|---|---|
| Month-end close duration | 10 business days | 7 business days |
| Reconciliation items per day per analyst | 45 | 180 |
| Hours spent on JE preparation | 120 hours / close | 42 hours / close |
Frequently asked.
Direct answers to the questions we hear most from operators evaluating whether this workflow belongs on the roadmap.
AI accelerates close by automating the three most time-consuming activities: reconciliation matching, journal entry preparation, and variance analysis. The system identifies reconciling items across GL, sub-ledgers, and bank feeds, proposes journal entries with supporting evidence, and routes items to controllers with plain-language explanations of variances.
Yes. The system enforces materiality thresholds, segregation of duties, and multi-level approval workflows required by SOX. Every journal entry draft includes linked evidence, preparer and reviewer timestamps, and a complete audit trail. The system also generates close checklists and task completion reports for SOX documentation.
Most organizations reduce close by 1-3 business days in the first quarter. The biggest gains come from automated reconciliation matching (which runs continuously rather than waiting for period-end) and parallel JE preparation. Some mature deployments achieve a 5-day close from a 10+ day baseline over 6-9 months.
The solution integrates with SAP, Oracle, NetSuite, Microsoft Dynamics, and Sage. It reads from general ledger, sub-ledger, and bank feed data sources, and writes back journal entry drafts, reconciliation status updates, and audit artifacts. Multi-entity and multi-currency environments are fully supported.
Deployment starts with low-materiality reconciliations in a single entity to prove accuracy and build confidence. Coverage expands monthly to higher-materiality items and additional entities. Each expansion includes evaluator gates that verify accuracy meets controller-defined thresholds before increasing autonomy.
Book an AI MRI intro. We'll confirm the pain point, the signal sources, and whether this workflow deserves a build now, later, or not at all.