Month-end close dropped from five days to overnight.

Closing the books is mechanical work that demands precision. The team had the precision; what they lacked was time. We built an agent that does the mechanics overnight.

The challenge

Every month, this mid-market finance team spent five gruelling days on close. Reconciling accounts across multiple ledgers, chasing down anomalies, and assembling the reports leadership needed - all manual, all deadline-driven.

The team was capable. The bottleneck was the work itself: repetitive, data-heavy tasks that required precision but not judgement. Every month, the same patterns, the same corrections, the same late nights.

What we built

We deployed an AI accounting agent that plugs directly into the firm's ERP and banking data feeds. Each month it runs reconciliation automatically and prepares a close-ready report.

• Auto-reconciliation. Transactions are matched across ledgers and bank feeds without manual intervention.
• Threshold-based flagging. Discrepancies above a configurable threshold are surfaced for review.
• Explained anomalies. Each exception comes with context - what changed, why it likely changed, and the probable resolution.
• Close-ready reports. Output is structured for leadership review, not raw data the team has to repackage.

The team reviews, approves, and signs off - instead of rebuilding the close from scratch.

The numbers

What changed

Month-end close now completes overnight. The finance team arrives on day one to a report that's ready for review, not ready to be built.

What took five days now takes hours - and accuracy has improved, because exceptions are caught systematically rather than by whoever happens to notice.

"We used to dread the last week of every month. Now close just happens. The team is working on things that actually require their expertise."- CFO, financial services firm