Bank statements
Digital and scanned PDF statements from Indian and overseas banks, converted into dated, categorised transaction lists.
Document automationfor finance teams.
Bank statements, invoices and scanned records converted into structured, verified data by vision-language models and OCR, with accounting checks built in so the output can go straight into reconciliation and the books.
What gets processed
Documents in, verified data out.
Purchase & sales invoices
Supplier, GSTIN, invoice number, dates, taxable value and tax components extracted line by line.
GST data
Purchase registers matched against GSTR-2B to flag missing, mismatched and excess input tax credit.
Vouchers & receipts
Expense bills and receipts read and coded for posting, with source images linked to each entry.
Loan & credit analysis
Multi-month bank statements summarised for inflows, outflows, EMIs, bounces and cash-flow patterns.
Audit support
Document populations extracted for vouching, sampling and exception testing.
Accuracy controls
Every figure is checked before it is used.
Extraction alone is not enough. A model that misreads one digit produces a figure that looks right and is wrong. Each pipeline therefore includes the checks an accountant would apply:
Running-balance checksum. Every bank statement line is tested against the opening and closing balance, so a missing or misread transaction shows up immediately.
Totals tie-out. Invoice line items must add up to the stated taxable value and tax.
Duplicate detection. The same document or transaction is not processed twice.
Exception queue. Anything that fails a check goes to a person for review instead of being posted.
Technology
Vision-language modelsGoogle GeminiOCR pipelinesPythonGoogle Cloud RunExcel / CSVTally importDataversePower Automate
Engagement
How an engagement runs.
Document survey
Samples of each document type, format and bank, and the output format required.
Pipeline build
Extraction, validation checks and output mapping set up for those documents.
Parallel run
Output compared against manually prepared data for the same period.
Production
Documents processed routinely, with the exception queue reviewed by the team.
FAQ
Common questions.
Can it read scanned or photographed documents?
Yes. Vision-language models read scanned and photographed pages. Poor scans are more likely to fail a validation check, and those pages go to review instead of being posted with errors.
Does it handle different bank formats?
Yes. The pipeline does not depend on fixed templates for each bank, and the balance checksum confirms that the extraction is complete whatever the layout.
Can the output be imported into Tally?
Yes. Output can be produced as Tally-importable vouchers, Excel/CSV, or records in Dataverse or other accounting systems.
How is client data kept confidential?
Processing runs in a controlled cloud environment, documents are not used to train public models, and retention is limited to what the engagement requires.
Related
Other systems work.
Rendered by Vishal Agarwal & Co, Chartered Accountants, as Management Consultancy Services within the scope permitted for members in practice by the Council of the Institute of Chartered Accountants of India.