Season after season of manual reading, and client data you cannot paste into a chatbot.
Statements, invoices and receipts read and keyed in by hand at every month-end.
Return information is protected by law — Sec. 7216 in the US — and consent rules are strict.
Contracts, ledgers and working papers that need to be searched and summarised fast.
Accountants know where their time goes — and tax rules make public AI tools a legal question, not just an IT one.
of accountants and bookkeepers say they spend too much time on admin; 89% say automation would free time for meaningful work.
US tax preparers who knowingly or recklessly disclose return information face up to $1,000 in fines and a year in prison per violation; disclosures abroad almost always need written consent.
of organisations say non-public company information has already been entered into public GenAI tools.
average cost of a data breach in financial services — second only to healthcare.
of organisations have banned public GenAI apps at least temporarily over privacy and data security.
Put your monthly volume into the calculator and see hours and dollars.
The path of one client’s month-end documents. Everything runs on the firm’s server; the accountant approves before anything is posted.
Uploads to the client folder, email attachments or a shared drive start a run per document.
CollectOCR reads every page; tables in bank statements are kept as tables.
CollectA local model tells invoices, receipts, statements and contracts apart and files them by client and period.
CollectDate, number, counterparty, net, VAT and total come out as structured data with the page they came from.
ExtractTotals are recalculated, VAT rates checked, duplicates found across the period.
ExtractA total that does not add up, a new supplier or a missing statement goes to the accountant’s queue.
ExtractClean lines are mapped to your chart of accounts and saved as an import file for QuickBooks, Xero or your local ledger.
PostStatement lines are matched to documents; unmatched ones get a suggested explanation.
PostStaff ask questions across a client’s years of files and get answers with the document and page.
AdviseMonth-end summaries and client letters are drafted from the numbers and your templates.
AdviseEvery document, extraction and change is logged per client — for reviews and regulators.
AdviseA local AI for accountants is a language model on the firm’s own server that reads client documents — invoices, receipts, bank statements, contracts — extracts the numbers, checks them and prepares clean import files. Staff can ask questions across years of a client’s files and get answers with the document and page. Client financial data stays inside the firm.
That is the difference from a public chatbot. Tax and confidentiality rules treat client information as something you disclose only with care and often with consent. A model you own keeps it in the building.
Documents arrive read, sorted and checked. Accountants spend their time on exceptions, tax positions and advice instead of retyping, and clients get their month-end note sooner.
Typical minutes per small-business client each month. Your own numbers go into the calculator below.
Based on 1 h 40 min by hand and 19 min with local AI per item, from the table above.
The model reads, extracts and drafts. Postings, tax positions and advice stay with the accountant.
The import is prepared; an accountant reviews and posts it.
Treatments and judgements are made by the accountant, not suggested by the model.
Where the law asks for it, the firm decides and documents consent.
Drafts are read and edited before they reach a client.
Anything that does not add up waits for a person.
Flip a switch to hand a step to the model or take it back.
Documents read and checked before the accountant opens them, answers from the client’s own files, and nothing sent to a third-party AI.
We look at the documents and the work, agree what the model may and may not do, and size the hardware.
The model on a server in your network, on your real documents, with a small group of users.
Access rules, logging and integrations, then the whole team — with the old way kept as a fallback.
Model updates in maintenance windows, monitoring and a monthly report of use and time saved.
Running the model on the firm’s own hardware avoids disclosure to an outside AI vendor, which is what Sec. 7216-type rules are about. Your own consent and engagement terms still apply — we leave that decision with you and your counsel.
On typed invoices and statements, very accurate; on poor scans and handwriting, less so. Every extracted line keeps a link to its page, totals are recalculated, and anything that does not add up goes to a person.
No. It prepares clean import files and answers questions; QuickBooks, Xero or your local ledger stays the system of record.
For a firm with up to a few hundred clients, one server with a 24 GB GPU handles reading and drafting. Heavier season peaks can run overnight in batches.
Yes — Ukrainian, Polish, German or English documents, local VAT layouts and bank statement formats. We test on your real documents in the first week.
Access follows your folders and user groups; staff only query the clients they work on. Every query is logged.
Describe your use case in two sentences — we reply within a day with a hardware and model recommendation.
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