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Laundry Labs is a banglore-based laundry business serving [add: customer type, e.g. households, hotels, businesses]. The company has an annual turnover of around ₹5 crore.
Its accounts are managed in-house by a three-member team, without an external CA, with TallyPrime 7.1 at the centre of its accounting workflow. The team maintains the books for three companies in Tally.
Laundry Labs has access to all AI Accountant modules, with accounts payable as its primary use case.
Since going live with AI Accountant in [Month Year], Laundry Labs has processed 40 purchase bills and 2,020 transactions.
Every voucher entered by hand, across three companies
Before AI Accountant, every voucher at Laundry Labs was entered into Tally manually.
Most of the documents coming in were purchase bills in PDF format. For each one, an accountant had to open the file, read the vendor, invoice number and date, check the line items and GST, choose the right ledger and type the entry into Tally.
For a three-person team maintaining three companies in Tally, that is a lot of repetitive entry, spread across three sets of books.
“It is avoiding, you know, manual entries.”Shivraj, Accountant, Laundry Labs
Looking for a way to stop typing vouchers
Laundry Labs wanted to reduce the manual entry involved in keeping three companies' books current, without changing the accounting system the team already relied on.
Instead of moving to a new accounting system, the team added AI Accountant to its existing TallyPrime setup.
AI Accountant prepares the voucher
Laundry Labs connected AI Accountant with its existing TallyPrime 7.1 setup for all 3 companies.
There was no migration to a new accounting system. The existing Tally workflow stayed in place, while AI Accountant took over the work of reading documents and preparing entries.
Uploading a purchase bill
The process is simple:
AI Accountant reads the purchase bill and extracts important information such as:
- Vendor name and details
- Invoice number and date
- Individual line items
- Quantities and amounts
- Taxable value
- GST details
It then uses Laundry Labs' existing accounting configuration to predict the appropriate ledger and GST treatment. The accountant reviews the prepared entry before it is posted.
“Easily, you can upload a PDF, so easily convert to necessary accounting.”Shivraj, Accountant, Laundry Labs
1 to 1.5 minutes per bill, including review
Each bill now takes about 1 to 1.5 minutes from PDF upload to a reviewed, Tally-ready voucher. That includes the time the accountant spends checking it.
The team's job changes from typing every voucher to checking prepared ones and handling exceptions.
98% prepared correctly means the team reviews instead of re-enters
Speed only matters when the output is usable.
Laundry Labs reports that 98% of entries are prepared correctly by AI Accountant. The accountant reviews every entry before it is posted and fixes the few that need it, so the final accounting decision stays with the team.
For a three-person team maintaining three companies, that means far less time spent typing, across all three sets of books.
Uploads from anywhere
Because bills are uploaded rather than typed at a desk, the work doesn't have to wait until someone is in the office.
“Easily can upload from anywhere, even the outside of the office, within minutes of time.”Shivraj, Accountant, Laundry Labs
Transactions, too
Alongside purchase bills, AI Accountant also prepares entries for Laundry Labs' transactions, predicting the ledger for each one. The team has processed 2,020 transactions this way.
What's next
Laundry Labs has asked about extending the same approach to sales: uploading sales PDFs and getting AI insights on items through the WhatsApp bot.
Since going live [in Month Year]
Since going live with AI Accountant, Laundry Labs has:
For Laundry Labs' accounts team, the change is not about replacing Tally or replacing the accountant.
It is about removing the typing between receiving a document and getting a Tally-ready entry.
The team still reviews every entry and remains in control. AI Accountant handles the repetitive work in between.
