NorthBridge Capital compressed month-end close from 14 days to 3 with an AI-augmented ledger
A private equity firm managing 23 portfolio companies was spending half the month closing books. An AI-augmented ledger platform auto-categorized transactions, flagged anomalies, and reconciled across entities — freeing the finance team to actually advise the business.
This is an illustrative case study. Company names, identifying details, and testimonials have been changed to protect client confidentiality. The technical solution and target outcomes are representative of the work we do. We extend the same confidentiality to every client.
Where they started
NorthBridge's 23 portfolio companies each ran their own books on a mix of QuickBooks, Xero, and one stubborn legacy system. Consolidating for reporting took 14 days every month, with 6 analysts reconciling intercompany transfers by hand. Anomalies — duplicate invoices, misclassified spend, duplicate vendor payments — surfaced weeks late, by which point the cash was gone. The firm was paying $1.2M a year in external audit fees to verify numbers nobody fully trusted.
What we built
We deployed our Ledgercore AI platform with a multi-entity ledger, AI transaction categorization trained on 18 months of NorthBridge's history, real-time anomaly detection that flags duplicates and misclassifications the moment they post, and automated intercompany reconciliation. Close workflows now run on a single timeline with every adjustment audit-tracked. The system went live across all 23 entities in 12 weeks.
Target outcomes
More from this project
We used to spend the first two weeks of every month proving the numbers were right. Now we spend them advising portfolio companies on what the numbers mean. The duplicate-payment detection alone paid for the platform in the first quarter.
Representative testimonial — name and role changed to protect client identity.