AI bookkeeping for accounting firms and finance teams
A three-hour bank statement, done in 25 minutes.
Darban categorises every transaction into your chart of accounts, gives a reason for each one, and sends your team only the exceptions.
Measured at a mid-size accounting firm in India. Works with Zoho Books today.
Results
- 97.5%
- of bank transactions categorised without a person touching them
- 100%
- precision. Of the 466 it categorised on its own, none were wrong
- 3 h down to 25 min
- of work per bank statement, from PDF to finished books
Source: validation on one bank statement covering about six months (478 transactions) at a mid-size accounting firm in India. 466 categorised automatically, 12 sent to review.
One statement, by hand, is five jobs.
None of it is hard. All of it is slow. At the firm we measured, it came to about three hours a statement.
- 01Open the PDF and key in every row.
- 02Decode the narration. Who was this, really?
- 03Look up how the same payee was booked last month.
- 04Pick the account, find the invoice, post the entry.
- 05Repeat for every line, every client, every month.
Four stages. Then a short list for your team.
- 01
Extract
Reads the bank statement PDF row by row and checks the running balance, so nothing is dropped or doubled.
- 02
Remember
Builds a memory from your own ledger history in Zoho Books, kept separately for each client.
- 03
Gate
Three checks have to agree before a transaction is categorised on its own. If they do not, it is held.
- 04
Review
An AI reviewer looks at what the gate held, using only past entries from your books as precedent.
What reaches your team: the few transactions the engine would not categorise, each with the reason it was held. Entries post directly to Zoho Books, so nothing is keyed twice.
How it works, in detailIt does not guess.
A reason on every line
Each categorisation shows what it was based on: the earlier entries it matched, or the invoice it found. Review is reading, not redoing.
A gate, not a hunch
Three separate checks have to agree before a transaction is categorised on its own. When they disagree, the transaction goes to a person.
Your books are the memory
The engine learns from each client's own ledger history, kept apart from every other client. It is not a general model of everyone's books.
Built for teams that close a lot of books.
Offshore accounting firms
Take on more client books with the team you have. Built on Zoho Books today. If your clients are on QuickBooks Online or Xero, talk to us.
Finance teams on Zoho Books
Stop keying bank statements. Review a short list of exceptions and close the month sooner.
CA firms with a books practice
Run every client through one engine. Each client keeps its own memory and its own chart of accounts.
A mid-size accounting firm in India cut a statement from three hours to 25 minutes.
The firm keeps its clients' books on Zoho Books. Every bank statement meant keying rows, decoding narrations and matching invoices by hand. We built the engine on the firm's own ledger history. In validation it categorised 466 of 478 transactions on its own, sent 12 to review, and got none wrong.
Tell us what your books run on.
Setup starts with your own data. We connect to your accounting software and read your past transactions. That history is how the engine learns the way your team books each payee. Pricing is discussed directly.
- +91 89035 11480
- hello@darban.ai
- Call
- Book a time
Need something that is not bookkeeping?
We also design and build custom AI systems for operations teams. Fixed scope, fixed price, no hourly billing.
- 83%
- less handling time on chargeback disputes for a leading ethnic wear brand, from 90 minutes to 15 a case
- 250x
- lower cost for catalog images at the same brand, produced 12 times faster
Asked before every first call.
What does Darban do?
Darban is an AI bookkeeping engine for accounting firms and finance teams. It reads bank statements, categorises every transaction into your chart of accounts with a stated reason, matches invoices, and sends your team only the exceptions.
How accurate is it?
In validation at a mid-size accounting firm in India, the engine categorised 466 of 478 bank transactions on its own (97.5%) and sent 12 to review. None of the 466 were wrong.
What happens when it is not sure?
It does not guess. Three checks have to agree before a transaction is categorised automatically. Anything that fails goes to your team as an exception, with the reason it was held.
Which accounting software does it work with?
Zoho Books today, with entries posted directly into it. Tally is planned. If your books run on QuickBooks Online or Xero, talk to us.
How do we get started?
We connect to your accounting software and read your past transactions. That history is how the engine learns the way your team books each payee. Contact us and we will walk you through it.
What does it cost?
Pricing depends on your volume and setup. Contact us and we will discuss it with you directly.
Two founders. You talk to both.
Reach either of us on WhatsApp at +91 89035 11480.
Abhishek Nahar
Co-founder and CEO
Vamshi Krishna
Co-founder and CTO