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Use case 01 · EBITDA lever: G&A reduction + faster decision-making visibility

AI-Augmented
Financial Close.

Days-to-close
10–15 → 5–7
30–50% reduction
FTE-hours
−30–50%
redeployed to judgment
Audit prep
−40–60%
PBC + walkthrough auto.
Engagement
12–16 wks
$250–500K

Typical mid-market ranges, not guarantees, your single target metric is agreed in week 1.

§ The problem

Books close in 10 to 15 days. The CFO wants 5 to 7.

Without AI, that's a headcount problem the sponsor doesn't want to solve. The close team spends 60–70% of its time on mechanical work (journal entries, reconciliations, flux analysis, audit prep) that AI agents do reliably and faster, leaving the human team to focus on judgment-heavy work the close actually requires.

§ What we deliver

Six things, in order.

  • Process redesign of the close calendar, with explicit decision rights and handoff artifacts.
  • AI agents for journal entry preparation and review across high-volume accounts.
  • AI agents for account reconciliation with auto-match thresholds and exception routing.
  • AI agents for flux analysis and variance commentary: first-draft narratives the controller edits, not writes.
  • AI-supported audit package preparation: PBC list automation, evidence collection, walkthrough documentation.
  • Change management: close team training, controller dashboard, governance for AI-in-the-loop steps.
§ Expected outcomes

Calibrated, not promised.

Days-to-close
10–15 → 5–7 days
Close-related FTE hours
30–50% reduction
Audit prep time
40–60% reduction
Variance commentary
days → hours
§ Prerequisites for success
  • Modern ERP (NetSuite, SAP, Workday, MS Dynamics, or comparable) with API or export access.
  • Defined chart of accounts and a controller willing to act as engagement champion.
  • Willingness to redesign close steps, not just automate the existing ones.
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