AI for finance, across 5 workflow patterns.

Reads transactions from the firm's bank and credit card feeds, matches each one against the bookkeeping system's open items (open invoices, expected receipts, recorded bills), and categorizes the unmatched ones to the right GL account based on description, amount, vendor pattern, and historical categorization. Surfaces the small set of genuinely ambiguous transactions for a human to decide. Replaces the slow, manual back-and-forth between bank statements and the books that bookkeepers traditionally do, and shifts the work from data-entry to exception handling. Builds the categorization model from the firm's own historical books, not a generic chart.

Watches the firm's accounts receivable, identifies invoices coming due or already overdue, and drives the follow-up process: drafts collection emails at the right tone for the right stage, schedules calls for high-value or delinquent accounts, notifies sales when customer relationships are at risk, and tracks every touch in a single timeline. Different from generic dunning automation because it adapts to the firm's tone, the relationship with each customer (don't dun a customer in active expansion talks), and history (some customers always pay on day 45). The pattern's value is consistent, timely AR follow-through without burning the controller's time or annoying customers who pay reliably anyway.

Reads expense submissions — receipts uploaded by employees, card transactions to be coded, mileage logs — and produces complete, policy-checked expense entries with the right GL category, project, and approval routing. Catches policy violations (out-of-policy meal, missing receipt, duplicate submission) at submission time rather than during approval. Routes flagged items back to the submitter with specifics. Different from E19 (bank reconciliation) because this pattern works with employee-driven submissions and policy enforcement; different from D12 (document extraction) because the document type and downstream workflow are narrower and more standardized. The pattern's value is compressing the expense cycle from days to hours while reducing the controller's role in chasing down corrections.

Takes the numbers from the monthly or quarterly close — P&L, balance sheet, cash flow, KPI dashboards — and writes the narrative that goes around them: what moved this period, why it moved, what's worth flagging to leadership. The pattern reads not just the numbers but the supporting context (sales pipeline, headcount changes, project milestones) to explain the why behind the what. Drafts go to the finance lead for review and editing before going to the audience. Replaces the slow, manual writeup that delays monthly reporting and often gets compressed at month-end into something less thoughtful than it should be.

Maintains a rolling cash flow forecast — 13-week or longer — that updates daily based on what's actually happening: AR aging changes, AP commitments, payroll runs, expected revenue from pipeline. Surfaces what's coming, what could go wrong, and what scenarios would matter. Different from E22 (which writes commentary on past periods) because this looks forward and updates continuously. The pattern's value is moving cash forecasting from a quarterly board exercise to an always-on view: the CFO or controller sees liquidity risks weeks before they'd otherwise notice, and the team can answer 'can we hire' or 'should we accelerate this payment' with current information rather than month-old spreadsheets.