Postscript cuts month-end close to 4 days with Rillet's AI-powered finance platform
Postscript's legacy GL could not handle their transaction volume, requiring aggregated revenue journal entries to keep pace, while AR aging was managed in Excel across separate QuickBooks instances with limited visibility, weak audit controls, and growing compliance risk.
Postscript had a documented material weakness in journal entry approvals flagged by auditors, and ad hoc Excel-based workflows left the team exposed with no consistent controls or audit trail.
Rillet reduced Postscript's month-end close from more than 8 days to 4 days, and the team passed their first audit with no issues, with auditors noting improved traceability compared to legacy systems.
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Frequently asked questions
What did this team achieve with this AI workflow?
Rillet reduced Postscript's month-end close from more than 8 days to 4 days, and the team passed their first audit with no issues, with auditors noting improved traceability compared to legacy systems.
What tools did this team use?
Rillet, QuickBooks, Excel.
What results were reported?
Month-end close time: more than 8 days to 4 days; Implementation time: 45 days; Historical data imported: 5 years; Audit outcome: passed with no issues (source-reported, not independently verified).
What failed first in this deployment?
Postscript had a documented material weakness in journal entry approvals flagged by auditors, and ad hoc Excel-based workflows left the team exposed with no consistent controls or audit trail.
How is this finance ops AI workflow structured?
Multi-entity centralization → Broader stack integration → Automated accounting functions → Audit controls and approvals → Close and audit output.