How is automated bookkeeping different from AI bookkeeping?

AI bookkeeping refers to the model that classifies transactions. Automated bookkeeping is the full pipeline that wraps the model — bank import, categorization, reconciliation, posting, recurring billing, and the close — running on a schedule with a human approving exceptions.

What still needs a human?

Setting up the chart of accounts, designing the close process, signing off period-end financials, and approving any AI decision below the confidence threshold. In practice that is 30–60 minutes per week for a typical SMB, vs the 8–15 hours a manual close used to take.

Can I run it across multiple companies?

Yes. Accountants and bookkeepers use a single workspace to manage every client they serve, with scoped permissions per staff member. Multi-entity businesses get consolidated reporting and intercompany elimination built in.

Does automation work on day one or do I have to train it?

It works on day one because the model has already seen the long tail of vendors most SMBs touch (Stripe, Uber, AWS, DoorDash, etc.). Your custom rules layer on top and the AI improves on your specific edge cases over the first 2–3 weeks.

How does the audit trail work?

Every AI-posted entry stores the source transaction, model version, confidence score, the rule that fired, and the alternative categories considered. Click any journal line to replay the decision. Overrides are versioned and used to retrain your rules.

Automated Bookkeeping

Automated bookkeeping from bank feed to financial statements

Stop touching every transaction. HelloBooks chains together bank import, AI categorization, receipt matching, reconciliation, and journal posting into one workflow that runs every night — with the exceptions queued for a human in the morning.

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What gets automated, end-to-end

Automated bookkeeping is more than auto-categorization — it is the whole pipeline from raw bank transaction to closeable financials. HelloBooks runs every link in that chain on a schedule, with confidence thresholds and human approvers at the points where judgement still matters.

Bank and card feeds pulled live via Plaid (US), Open Banking (UK), and direct rails in IN/AU/CA/SG/NZ/AE
AI categorization with confidence scores; high-confidence transactions post automatically
Receipts auto-matched from Gmail, Outlook, mobile capture, and email-in inbox
Bank reconciliation with AI-suggested matches and a one-screen exception queue
Journal entries posted to the GL with full audit trail (model version, confidence, input)
Recurring invoices and bills generated on cadence, with auto-payment matching
Period-close checklist that surfaces unreconciled items before the books close

Rules you can write in plain English

Every team eventually wants a rule that says “if the vendor is Stripe and the description includes payout, post to Sales clearing with a split for fees.” HelloBooks lets you write that in plain English; the AI compiles it into a structured rule and runs it on every matching transaction going forward, with a backfill option for historical data.

Rules are versioned. If a rule misfires you can roll it back, see every transaction it touched, and re-classify in bulk. No more debugging a regex in your accounting tool.

Multi-entity and multi-client by design

Accounting firms run HelloBooks across their entire client book from one workspace. Each client lives in its own ledger; the same AI runs across all of them; permissions scope staff to the right clients; and a global queue lets a reviewer triage exceptions across every book in one session.

Multi-entity businesses run the same way — one parent workspace, one chart-of-accounts template, one set of rules — with consolidated reporting that rolls up intercompany eliminations automatically.

A reviewer mode built for accountants, not founders

The hardest part of automation is the trust handoff. HelloBooks ships a reviewer mode that shows every AI-posted entry, the source transaction, the rule that fired, and the alternative categories the AI considered. The reviewer can approve in one click, override and retrain the rule, or send back to the client with a question.

A free reviewer seat ships with every Pro plan so your accountant can work directly inside your books instead of asking for a Drive folder of CSV exports.

How it works

How to automate your bookkeeping workflow

Set up end-to-end bookkeeping automation in HelloBooks — from bank feed to financial statement — in under 15 minutes.

Step 1
Connect all your bank and card accounts
Link checking, savings, credit cards, and processor accounts (Stripe, Square, PayPal) via Plaid or direct rails. HelloBooks pulls every transaction in real time.
Step 2
Turn on AI categorization and reconciliation
Enable the AI Accountant in Settings. It will begin categorizing transactions and proposing reconciliation matches immediately, using pre-trained models for common vendors.
Step 3
Write your first plain-English rule
Create a rule like "Stripe payouts → Sales clearing, minus fees" in plain English. The AI compiles it into a structured rule and backfills historical transactions.
Step 4
Set up recurring invoices and bills
Configure recurring invoices for retainer clients and recurring bills for software subscriptions. HelloBooks auto-generates, sends, and matches payments.
Step 5
Review the exception queue weekly
Instead of touching every transaction, open the one-screen exception queue, approve or override AI decisions, and sign off the period close in minutes.

FAQ

Frequently asked questions

How is automated bookkeeping different from AI bookkeeping?: AI bookkeeping refers to the model that classifies transactions. Automated bookkeeping is the full pipeline that wraps the model — bank import, categorization, reconciliation, posting, recurring billing, and the close — running on a schedule with a human approving exceptions.
What still needs a human?: Setting up the chart of accounts, designing the close process, signing off period-end financials, and approving any AI decision below the confidence threshold. In practice that is 30–60 minutes per week for a typical SMB, vs the 8–15 hours a manual close used to take.
Can I run it across multiple companies?: Yes. Accountants and bookkeepers use a single workspace to manage every client they serve, with scoped permissions per staff member. Multi-entity businesses get consolidated reporting and intercompany elimination built in.
Does automation work on day one or do I have to train it?: It works on day one because the model has already seen the long tail of vendors most SMBs touch (Stripe, Uber, AWS, DoorDash, etc.). Your custom rules layer on top and the AI improves on your specific edge cases over the first 2–3 weeks.
How does the audit trail work?: Every AI-posted entry stores the source transaction, model version, confidence score, the rule that fired, and the alternative categories considered. Click any journal line to replay the decision. Overrides are versioned and used to retrain your rules.