How does YP get month end close started before your team sits down?
A close AI Employee that walks the month end checklist every month, reconciles revenue against the ledger, flags anomalies and missing documentation against prior months, and posts the open items to your finance channel. It never writes a journal entry and never marks a period closed.
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Month end close runs the same way every month and takes days anyway: walk a checklist of a few dozen items, reconcile revenue against the ledger, chase down whatever documentation is missing, and sanity check the numbers against the trend before anyone signs off. None of it is hard. All of it is slow, and most of the time goes to confirming that the easy 90% is actually fine so the close team can focus on the 10% that isn't. The checklist itself isn't the bottleneck. It's reconfirming the same categories of thing every month: does recognized revenue tie out to what Billing actually processed, does every line have its supporting document, and does anything look different enough from the last few months to need an explanation before the numbers go out. A reconciliation formula in the ledger catches the exact ties but not the near ones, and doesn't know what 'looks anomalous' means without a person supplying that judgment fresh each time. So the checklist gets worked start to finish by hand, at the same cost, every single month, and only as carefully as there's time for.
The close AI Employee runs once a month after the period closes, inside your own environment, with read access to Billing revenue and to the close checklist and ledger tabs. It reconciles Billing revenue against what the ledger recorded, works the rest of the checklist for missing supporting docs, compares this month's figures against the trailing months for anomalies, and posts a close status summary with every open item to Slack. It assembles and flags; it never enters a journal line and never marks the close done. A named human owns the close.
See exactly how the work gets done.
Runs on a monthly schedule, after the period closes
A scheduled run fires once a month, once the prior period has closed. Each run starts clean. The checklist and ledger are the record, so nothing needs to carry over between runs.
Works to your close standard
What counts as a reconciled line, what tolerance a timing lag gets, which items need which supporting document, and how big a swing versus the trailing months counts as an anomaly worth flagging travel with the AI Employee as a skill, so every month is judged to the same standard.
Connects to your systems, read and flag only
It reads revenue, refunds, and payouts from Billing for the closed period, reads the ledger tab to reconcile against, adds notes and flags to the checklist tab without touching the recorded entries, and posts the summary to Slack. Credentials stay in memory, never written to disk, never exposed to the model.
Reconciles and flags, never closes
It never writes a journal entry, never edits a recorded ledger amount, and never checks the period off as closed. That decision, and every action it implies, belongs to a named human in finance.
Posts the open items
Each month produces a checklist worked end to end and one Slack post: what's still unreconciled, which items are missing documentation, and which figures moved enough against the trend to need a look, each with enough detail to act on without pulling the numbers again. The finance team reviews the list and closes the books.
Runs in your environment
Every run is isolated inside your own infrastructure. Only the checklist flags and the Slack post leave it.
Never closes the books
It never writes a journal line, never edits a recorded ledger amount, and never marks a checklist item or period as closed. It flags; a named human closes.
Read and flag only
Its access to Billing and the ledger is read only; its only writes are notes and flags on the checklist tab. It cannot move money or change a recorded figure.
Credentials stay contained
The Billing and ledger credentials connect with the permissions you set, stay in memory, are never written to disk, and are never exposed to the model or the logs.
You own every rule
The checklist rules, the reconciliation tolerances, and the per system permissions are yours, versioned and changed on your terms, not in a vendor dashboard.
The days that used to go to confirming the easy 90% of the checklist now go to the handful of items the AI Employee actually flagged. The close still runs on schedule whether or not anyone has gotten to it yet, and the open items list is waiting in Slack when the finance team sits down. The AI Employee reconciles and flags; your people close the books.
Every month
The checklist worked end to end on the current data
0 journal entries
No line written and no period ever marked closed by the AI Employee
1 post
Every open item in one place: unreconciled, missing doc, anomaly
Our free AI audit shows you where AI fits, what your security risks are, and gets your first AI employee working.
How do AI Employees process invoices the moment they land?
Extracts every invoice, matches it against POs and prior invoices, flags duplicates and overcharges, and routes for approval. It records, it never pays.
×How do AI Employees recover failed payments before they become churn?
Works every failed invoice through a fixed escalation ladder of smart retry, reminder, update card, and final notice, alerts the revenue team on Slack, and stops the instant it's paid. It never cancels a subscription, issues a credit, or refunds; those stay with a named human.
×How do you get reconciliation done even when no one has time?
Runs once a month against Billing, the bank feed, and the tracking sheet, matches transactions to invoices, posts a reconciled summary, and escalates every unmatched item to a named human, writing only to the sheet.
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