AI agent for accounting and bookkeeping
An agent that collects bank lines and receipts, suggests account codes, reconciles accounts and chases missing documents, so your accountant reviews a short list and does not type entries.
- Bank statements imported for 9 client accountsDone
- 312 transactions categorised using your rulesDone
- 3 transactions could not be matched to a categoryAsks a person
- Reminder sent to 2 clients for missing receiptsDone
An example. Your agent is built around your own work.
How it works
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Gather
The agent pulls bank and card transactions through your accounting system's API or a scheduled export, and collects receipts and statements from the inbox and the folders where your team drops them.
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Categorise and match
For each transaction it suggests an account code and tax rate from your past entries and your rules, and matches bank lines to ledger entries. Duplicates and reversals are flagged.
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Review
Items that follow a clear rule can post as drafts. Everything else goes into the accountant's queue with the reason it was not sure. The accountant approves a batch before anything counts.
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Chase and close
The agent emails the client or the staff member about missing receipts and unexplained items, tracks the answers, and keeps the month-end checklist up to date.
New to AI agents? How they work, in plain words
Real examples, setup steps and tool connections for this agent
An example conversation
An example of how a conversation runs. The grey lines show what the agent does in your systems meanwhile.
- CustomerHi, please get the Dubai branch ready for the September close.
- Pulled 312 bank and card transactions for September from the accounting system. Read 87 receipts from the shared folder and the accounts inbox.
- Matched 276 bank lines to ledger entries. Suggested account codes for 241 using last year's entries and your rules. Found 2 duplicate card charges.
- Agent276 of 312 lines are matched. I suggested codes for 241, and the 38 with a clear rule are ready as drafts. 36 lines are not matched, and 11 of them have no receipt.
- CustomerSend the receipt requests. Which ones are not categorised?
- AgentFour are payments to a supplier I have never seen, and two look like personal expenses. I can't tell the difference from the bank text, so I left them uncoded for you.
- Sent 11 receipt requests to the card holders by email, with the date, amount and merchant for each. Added the 6 open questions to the close checklist.
- CustomerFine. I'll go through the drafts after lunch.
- AgentThe draft batch and the open questions are in your review sheet. I will chase the missing receipts again on Wednesday.
How it is built
- Where the data comes from
- Transactions come from your accounting system through its API, or from a scheduled bank export if that is all you have. Receipts and statements come from a mailbox or a shared folder. Every source is saved with its date range, so you can see what was included.
- What the model does and what rules do
- A language model reads receipts and text on bank lines and suggests a category. Your rules, such as "fuel goes to vehicle costs", and the history of past entries decide how far a suggestion can go. Each suggestion carries a confidence score.
- Tax rates live in your system
- Tax codes and rate tables stay in your accounting software, not in the agent's instructions, because tax rules differ by country and change during the year. The agent picks from the codes that exist. Your accountant signs off each period.
- A fixed list of actions
- The agent can read transactions, suggest codes, create draft journal entries and bills, flag items, and send request emails. It cannot close a period, delete entries or change the chart of accounts. Each entry it creates is tagged with its source and the rule behind it.
- Review gate
- Entries with a clear rule and a high score can be posted as drafts. The accountant approves each batch before the month closes. You decide how much of the work stays in the queue.
- Learning from corrections
- When the accountant changes a category, the change is logged and used to tidy the rules. A wrong rule would repeat every month, so a fixed sample of automated entries is checked each week and the correction rate is tracked.
- Scope, logs and keeping data in your network
- Each run is limited to one client's or one company's data, and access is logged. If you use Excel only, the same flow works with a workbook and a bank CSV. The whole agent can run on your own servers: the agent, its database, its logs and the language model itself, using open models such as Llama, Qwen or Mistral, so documents never leave your network. Open models you host yourself are smaller than the largest cloud models. For categorising transactions, reading receipts and answering from your ledger they are usually enough, and we test on your own cases before choosing. Bank feeds and email still pass through the banks and mail providers that carry them.
What you can connect to it
- QuickBooks Online
- Reads transactions and accounts, suggests categories and creates draft entries through its API.
- Xero
- Reads bank transactions and accounts and creates manual journals and bills as drafts.
- Zoho Books
- Reads bank transactions and bills and creates drafts through its API.
- Sage Intacct
- Reads the general ledger and creates journal entries through its web services.
- Microsoft Dynamics 365 Business Central
- Reads accounts and posts to the general journal as drafts through its API.
- Bank and card statements
- Reads exports or statement files when a live bank feed is not available.
- Gmail or Outlook
- Reads receipts sent by staff or clients and sends requests for what is missing.
- Google Sheets or Excel
- Holds the review queue, the close checklist and client reports, or the books themselves for a small business.
- Shared folders and document storage
- Collects receipts, contracts and statements and files them against the transaction.
Connects to your tools. You stay in control.
- Works with what you have
- QuickBooks Online, Xero, Zoho Books, Sage Intacct, Microsoft Dynamics 365 Business Central, bank and card statements, Gmail, Outlook, Excel and Google Sheets.
- A person approves what matters
- Payments, orders, discounts or anything you choose wait for approval. Every action is logged.
- Can run on your own servers
- The agent, its data, its logs and even the language model (open models such as Llama, Qwen or Mistral) can run on your servers, so documents and customer data stay inside your network. How that works
What it does not do
- It does not sign off the books. Your accountant reviews and approves each period.
- It does not file tax returns or decide tax treatment. It uses the tax codes you already have.
- It does not invent receipts, amounts or explanations. If a document is missing, it asks for it.
- It does not close a period, delete entries or change your chart of accounts.
- It does not mix clients. Each run uses one client's or one company's data.
Questions
Is this for accounting firms or in-house teams?
Both. Firms use it across many client files, with each run limited to one client. In-house teams use it for their own month-end.
Who signs off the books?
Your accountant. The agent prepares and flags, and a person reviews and approves each period. Its entries are drafts until then.
Does it work for small business bookkeeping?
Yes. For a small business it keeps the books up to date from bank statements and receipts, ready for your accountant to review. The owner sees a short weekly list of items that need a decision.
How does an AI agent do automated bookkeeping?
It reads bank lines and receipts, suggests a category from your past entries and rules, matches the bank lines to the ledger, and asks for what is missing. An accountant approves the result before it counts.
What if it categorises something wrongly?
The accountant changes it, and the change is logged and used to fix the rule behind it. A weekly sample check catches a wrong rule before it repeats for months.
Do we have to switch accounting software?
No. It works with QuickBooks, Xero, Zoho Books, Business Central and others through their APIs, or with exports and an Excel workbook. A workbook suits a few hundred transactions a month. Above that, an accounting system is easier to keep correct.
How is client financial data protected?
Each run is limited to one client's data, the agent uses an account with only the rights it needs, and every access is logged. It can run on your own servers. We explain where the data is stored before you start.
How much does an agent like this cost?
It depends on the task and the systems it connects to. After a first call we give you a clear estimate of cost and time.
Want this agent built around your work?
Tell us in a few lines what the job looks like today and we will set up an online intro call.
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