Portfolio companies run 8–12 day closes on manual reconciliations, spreadsheet-driven consolidation, and after-the-fact variance analysis. AI compresses this to 3–5 days with cleaner numbers, drafted narrative, and cash forecasts that hold under sponsor scrutiny. Every day off the close is a day of better operational decisions.
Manual reconciliations, spreadsheet consolidation, after-the-fact variance investigation. By the time the board sees April, June's decisions are already made. Meanwhile the finance team is buried in mechanical work that has nothing to do with judgment — and the sponsor's ops team is doing a shadow forecast in parallel because they don't trust the timing.
We deploy inside the portfolio company's existing finance stack — NetSuite, QuickBooks, Sage Intacct, Xero, plus the reporting layer of choice. AI runs against the same data the team already touches. No ERP migration. No consultant handoff. No enterprise license.
Close cycle drops from 10 days to 3–5. Cash forecast accuracy triples. Manual work drops 85%. Accounting turnover drops from 45% to under 20%. Working capital metrics improve as AR AI shortens DSO. Every one of these shows up on the exit story.
Ranges reflect published 2026 benchmarks (ChatFin, Kognitos, FP&A Trends, Peakflo) and Alterra AI portfolio deployments across SaaS, services, and light-industrial mid-market companies.
Sources: ChatFin 2026 Finance Automation ROI, FP&A Trends Close Automation, Peakflo AI Close Guide, Kognitos CFO ROI Guide. Documented case studies show 60–70% close reduction, 85% fewer manual tasks, and 152% first-year ROI at the median. Direct savings $550–900K, error elimination $800K–$2M.
Bank, credit card, intercompany, and sub-ledger reconciliations run continuously — not in a batch at month-end. Exceptions surface daily with suggested resolution. The month-end batch is what's left after AI has already cleared 85% of the volume.
Every material flux (P&L or balance sheet) auto-analyzed with plain-language narrative — root cause, magnitude, comparison to plan and prior period. The Controller reviews and approves. What used to be a 3-day investigation cycle becomes a 3-hour review.
AR: automated dunning sequences, payment predictions, dispute detection. AP: invoice OCR, three-way match, coding suggestions, exception routing. Working capital improves without a treasury project. DSO down 5–10 days, DPO managed with sponsor-defined intent.
13-week cash forecast that pulls from AR aging, AP schedule, sales pipeline, seasonality, and historical collections patterns. Variance drops from ±20% to ±5–8%. Sponsor confidence goes up. Covenant compliance planning gets easier.
Board deck financial section auto-generated from the closed numbers — commentary, waterfalls, KPI callouts, budget-vs-actual. Consistent format across every portfolio company for the fund. LP report inputs standardized. The CFO reviews and edits, doesn't build from scratch.
48-hour deep dive on the last 3 close cycles.
The highest-volume manual workflows first.
First accelerated close run end-to-end.
Second accelerated close. Impact documented.
Ranges reflect typical outcomes for mid-market portfolio companies with 4–12 finance FTEs running on NetSuite, Sage Intacct, or QuickBooks Enterprise. Portfolio-wide rollouts standardize close cycles and cash forecasting across every portfolio co. for the fund.
Get the assessment →Portfolio companies with 8–12 day closes compress to 3–5 days within one to two close cycles. Documented case studies show 60–70% cycle reduction and 85% fewer manual tasks. Biggest levers: automated reconciliations, AI-drafted variance commentary, and continuous (vs. batch) consolidation. Net: board-ready numbers ~6 days closer to the decision.
150–300% first-year ROI with 12–18 month payback is the documented range. Direct efficiency savings $550–900K/yr at mid-market. Error/rework elimination another $800K–$2M. Strategic value from working capital, vendor, and revenue improvements adds $6–12M over the deployment cycle. Error cost elimination alone typically accounts for 30–50% of quantifiable value.
It reduces audit risk when built correctly. Every AI-generated entry, reconciliation, and narrative is logged with full traceability — inputs, model version, human approver. Audit trails are cleaner than manual processes (no lost email threads, no missing spreadsheet versions). Big 4 teams accept AI-assisted close when the control framework is documented. The failure mode is deploying without controls — a discipline problem, not an AI problem.
Pulls from AR aging, AP schedule, pipeline, seasonality, and historical collections. Portfolio companies with manual forecasts run ±20% on 13-week outlooks. AI brings this to ±5–8%. For companies with tight covenants, working capital lines, or sponsor-driven capital allocation, this precision materially improves every treasury decision — and reduces sponsor/CFO friction.
No. We build inside the existing GL — NetSuite, Sage Intacct, QuickBooks, Xero, and equivalents. AI runs against the same data the team already touches. No ERP migration, no consultant handoff, no enterprise license. That's the whole point.
48-hour AI opportunity assessment. Ranked by EBITDA impact. Delivered before the next partner meeting.
Book an assessment →Response within 1 business day. Fixed-scope, fixed-fee engagements.