Month-end is a tick-and-tie marathon
Your best accountants spend the first week of every close matching bank activity, processor settlements, and ledger entries line by line. It is your most senior people doing the least senior work, on a deadline.
Department automation
Reconciliation and commission runs, drafted by AI — approved by your finance team
Matching, reconciling, and calculating are the most automatable work in your company — and the most dangerous to automate badly, because they sit one step away from your ledger. b2bei builds finance automations where AI drafts the match overnight and a person on your team approves it before anything posts, running on your own servers inside the systems you already close in. This exact architecture runs live today in the finance operation of a North American manufacturing and packaging company.
The grind
Where the hours actually go
Commission runs start from scratch every cycle
Someone rebuilds the spreadsheet, re-applies the splits and tiers, and braces for the disputes. One mis-keyed rate and sales stops trusting finance for a quarter.
Invoice exceptions sit in inboxes
A price variance or quantity mismatch kicks an invoice out of the three-way match, and then it waits for someone to open it, research it, and decide — while the early-payment discount window quietly closes.
Aging reports get eyeballed, not analyzed
Cross-referencing the AR aging against remittances, credit memos, and short-pay history is hours of manual lookup. So it happens once a month at best, and the pattern behind a repeat short-payer goes unnoticed.
The split
Automate the repetitive. Protect the cognitive.
We automate
Invoice matching — line-level match against PO and receipt, with each exception flagged and the reason attached
Commission and payout calculation — statements drafted from source transactions, every split and tier traceable to its order
Account reconciliation — bank, processor, and ledger activity matched overnight; unmatched items surfaced, not buried
Aging-report cross-referencing — AR aging tied to remittance history, credit memos, and short-pay patterns automatically
Exception research prep — the source documents behind each mismatch gathered onto one screen before a person looks
We protect
Posting to the ledger — nothing hits the GL without a named person's approval — by design, permanently
Exception judgment — whether a variance is a dispute, a discount, or an error is your team's call
Commission disputes — when a rep challenges a number, your people own the answer — and can trace every line of it
The close itself — your controller signs the close; the automation just shortens the road there
How it runs
Prepare-and-confirm, always
AI drafts. A person reviews and approves. Nothing touches a live system without a human gate — that's the architecture, not a phase.
The full build architecture →A worked example
Commission calculation, as it runs live today: overnight, the system pulls the month's invoiced orders and applies your commission plan — splits, tiers, draws — as deterministic, auditable rules, then drafts a statement for each rep with every line traceable back to its source transaction. The next morning, your finance manager opens a review queue, sees each drafted statement beside the orders behind it, and approves, corrects, or holds each one. Nothing is sent and no entry posts on the AI's say-so — only what a person approved. Plan changes, dispute calls, and final sign-off stay with your team, and the whole thing ran in parallel with the old spreadsheet until the numbers agreed month after month.
Questions operators ask
Is the goal to shrink my finance team?
No. The goal is to stop paying senior accountants to tick and tie. When the matching arrives drafted, they spend their time on variance analysis, exception judgment, and the questions your auditors and your CFO actually care about. The people who used to lose the first week of close to matching become the people who can explain a variance before anyone asks.
How does this hold up in an audit?
Better than the spreadsheet did. All matching and calculation is deterministic code — the same inputs always produce the same outputs — and every draft, correction, and approval is logged with a name and a timestamp. The AI language model touches only unstructured text, like reading a remittance PDF; it never does math and never posts an entry.
What happens when the automation gets a match wrong?
A person catches it before it posts, because a person reviews every batch — that review queue is part of your close calendar this month and every month after, not scaffolding that comes off once trust is earned. New automations also run in parallel with your existing manual process until the outputs agree consistently. And your team keeps the ability to run everything by hand, so a system problem never means a missed close.
Map the repetitive work in finance operations.
We sit with your team, map how the work actually happens, and draw the split: what's worth automating, and what automation should never touch. You keep the map either way.
Map your workflows