Run your firm's bookkeeping with an agent that learns each client's books.
Let AI Agent run your bookkeeping
Categorize Transactions
"Categorize this month's pending transactions across the connected client books. For each client, pull uncategorized entries from the ledger, apply prior coding corrections by vendor, department, and class, and check the chart of accounts for off-pattern entries. Flag novel vendors, duplicate descriptions, and entries that don't fit any learned rule. Pause before applying a new rule to posted history. Ask me where the firm stores its per-client coding cheat sheets if any exist. If a vendor's category is ambiguous, ask whether to follow last month's coding or open a new rule. Send a Slack digest per client with proposed coding and exceptions."
Reconcile Books
"Reconcile last month's books for the selected client portfolio. Tie ledger balances to the connected bank feed, clear obvious matches, and flag duplicates, stale uncleared items, and entries posted under a different vendor name. For multi-entity clients, check intercompany balances on both sides. Draft adjusting entries for known timing gaps; pause before posting any of them. If the client's bank is not yet connected, ask me to connect it. Ask me where prior reconciliation packs live if the folder is not obvious. Save the pack to Google Drive and send a Slack summary."
Catch Up Books
"Catch up a client whose books are months behind. Inventory the missing periods, ingest the historical statements and invoices the user uploads, and reconstruct categorization period by period using the client's coding rules where they exist. Flag missing documents, unsupported entries, and gaps in the bank feed. Draft journal entries to bring the books current. Pause for explicit per-period approval before posting any of them, and pause before applying retroactive rule changes to already-posted history. Ask me to upload missing bank statements, receipts, or vendor contracts for any period that lacks support. Save the catch-up status sheet by month."
Clean Up Books
"Clean up a client's books before the next close season. Scan the chart of accounts for unused, duplicate, or naming-drifted accounts. Audit the vendor master for duplicates, name variants, and stale records. Flag stale AR and AP, uncategorized items, and posted entries that contradict the learned coding rules. Propose merges, recoding plans, and chart-of-accounts consolidations. Pause before merging vendor records, archiving any account, or recoding posted history. Ask me for the firm's materiality threshold for recoding posted entries. Ask me whether the firm has a chart-of-accounts naming standard. Send a Slack digest with proposed merges and recoding."
Up to 80% Lower Cost to Serve
For an accounting firm, the buying question is cost per clean client month. Minded positions the AI bookkeeper for up to 80% lower cost to serve by moving the repeat hygiene loop, categorize, reconcile, catch up, clean up, from staff queues into supervised accounting automation runs without removing approval gates.
One Cockpit for the Whole Client Portfolio
Most bookkeeping software and bookkeeping platforms bind to a single ledger. Firms running 80-300 mixed-ledger client books need one cockpit. Minded runs the same AI accounting agent across every client and ledger, preserving each client's chart and reviewer policy. Single-workflow deep dives like bank reconciliation, GL coding, AP automation, journal entries, and month-end close live as their own pages.
An Accounting Assistant That Remembers Each Client
Generic AI accounting flattens every client's books to a global rule set, then breaks the moment a vendor codes differently for two clients. Minded's accounting assistant keeps memory per client books: prior coding corrections, learned vendor rules, materiality thresholds, reviewer preferences. The bookkeeping assistant proposes consistently with how the firm already handled the same situation last month.
What is AI bookkeeping for an accounting firm?
AI bookkeeping is an agent that performs the firm's repeat books work across client ledgers: categorizing transactions, reconciling books, catching up backlogged periods, and cleaning up the chart of accounts. Staff review exceptions and approve actions while the firm keeps standard IRS recordkeeping and double-entry bookkeeping practice intact.
How is Minded different from bookkeeping software like QuickBooks or Xero?
Bookkeeping software, or a bookkeeping app, is the ledger where the books live. Minded is the AI bookkeeper on top of those ledgers, handling transaction categorization, reconciliation, and review-ready entries aligned to AICPA practice. The agent works across QuickBooks Online, Xero, NetSuite, Sage Intacct, and Zoho Books.
Can one AI bookkeeper run books across many clients on different ledgers?
Yes. The agent keeps a per-client workspace with its own chart of accounts, coding rules, vendor history, and reviewer policy. The same firm-level cockpit can run categorization, reconciliation, catch-up, and cleanup workflows for clients on different ledgers without flattening the rules to a global default.
How does Minded learn each client's coding rules?
The agent reads prior coded transactions, reviewer corrections, vendor history, and any cheat-sheet the firm uploads, then proposes coding for new entries and asks when something is off-pattern. Rule changes pause for reviewer sign-off before they touch posted history. Every change lands in the audit log alongside GAAP review notes.
Which accounting systems and banks does Minded connect to?
Minded supports common firm-stack ledgers (QuickBooks Online, Xero, NetSuite, Sage Intacct, Zoho Books) and connected sources such as Gmail, Google Drive, and Slack. For banks, the agent works with the client's bank connection once the client links it; the agent will ask you to connect any missing bank.