Prepare Tally import columns from AI-extracted invoice data

Stable source columns still need a TallyPrime mapping

• Supplier layouts change, so the workbook needs stable source headers before a reusable mapping can work.
• Party ledgers, voucher types, stock items, units, and tax ledgers come from the TallyPrime company, not from OCR.
• Document fields and item rows may need separate sheets or multiple mapped rows for one voucher.
• A technically successful import can still be wrong if signs, masters, dates, or tax ledgers are mapped incorrectly.

Document types this workflow handles

• GST tax invoices: sales and purchase invoices with tax splits
• Credit & debit notes: adjustments exported with distinct document types
• Purchase bills: vendor bills for goods and services
• Sales bills: outward customer invoices

What appears in the exported rows

के साथ शुरू

REVIEWED INVOICE DATA

→डायनामाइट डॉक्स→

इसके लिए काम करें

Tally import columns

उदाहरण स्रोत

REVIEWED INVOICE DATA

Source row key

INV/24-25/0144 · line 01

Document type

Tax invoice

Mapping status

Party ledger review required

Keep the original beside the result. Review before export.

Exports include reviewed invoice fields as clean, standardized columns. A typical extraction provides:

• Source row key: INV/24-25/0144 · line 01
• Document type: Tax invoice
• GSTIN (party): 27AABCS1429B1ZP
• Invoice number: INV/24-25/0144
• Invoice date: 2026-08-02
• Place of supply: Maharashtra (27)
• HSN / SAC code: 4820
• Taxable value: ₹24,000.00
• CGST amount: ₹2,160.00
• SGST / IGST amount: ₹2,160.00 / ₹33,480.00
• Invoice total (incl. tax): ₹28,320.00
• Mapping status: Party ledger review required

एक यथार्थवादी उदाहरण

Sample data. Not a real invoice or filing record.

A reviewed batch exports into organized rows like these, one row per document, ready for your accounting workflow:

What to validate before export

Validation issue

Confirm column mapping, ledger names, dates, and debit-credit treatment.

Limitation

The export is not a native Tally import file and is not posted automatically.

Reviewed by Dynamite Docs content team. Last verified 2026-09-30.

Standardized columns for a controlled accounting import

के साथ शुरू

REVIEWED INVOICE DATA

→डायनामाइट डॉक्स→

इसके लिए काम करें

Tally import columns

1. 01Check required columns
2. 02Confirm voucher types
3. 03Test a small import

After reviewTally mappingएक्सेल

Export reviewed rows, map the receiving system's fields, then test the import.

A stable export schema separates document capture from accounting configuration. The extracted invoice number, date, GSTIN, HSN or SAC, taxable value and tax amounts stay in predictable columns even when supplier layouts change. TallyPrime supports mapping Excel columns to company fields, but the required masters and import configuration still belong to the TallyPrime company. Keeping that translation outside extraction makes exceptions easier to see and mapping changes easier to audit.

Treat the export as a staging file, not as a posting-ready truth source. Review low-confidence fields against the invoice, confirm that line totals reconcile to the taxable value, and check that the tax components add up to the document total. Look for duplicate invoice references within the same supplier and financial period. If a source uses an unfamiliar item description or party spelling, resolve it to an approved master value in a separate mapping column rather than overwriting the captured source text.

Before a large import, use a small pilot containing a normal invoice, an interstate transaction, an adjustment document and at least one multi-line bill. Import it into a test company or controlled workflow, inspect the resulting vouchers, then lock the accepted header order and mapping version. Record who reviewed the source rows and who approved the import. This simple checkpoint makes rework much easier to trace than editing vouchers after a full batch has been posted.

Excel and CSV exports also work as review schedules. You can filter by supplier, GSTIN, document type or exception status; compare the batch total with the invoice register; and retain the reviewed sheet with the accounting period. JSON is useful when an internal script or integration needs explicit field names and predictable value types. Whichever format you choose, preserve the original documents and the reviewed export together so a later query can be traced back to its source.

Reliable data exports with complete user control

Consistent headers reduce repeated cleanup, but they do not decide which ledger, voucher type or tax treatment is correct for your company. That judgment stays with the reviewer and the accounting system mapping.

Digital PDFs may contain usable embedded text, while scans and photos require visual extraction. Both can contain ambiguous values, broken tables or missing labels, so both should pass through the same review controls.

Reviewed rows can be exported to Excel, CSV or JSON, or pushed to Google Sheets when that connection is enabled. Every signed-in tier can connect a provider key. Free and Hobby own-key runs use their monthly PE allowance; Pro and Ultra own-key runs do not consume PE.

सवालों के जवाब

Related extraction articles

• Build a Tally invoice import workflow using AI-extracted data
• Map AI-extracted GST invoice data into Tally import columns