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AI document extraction with human review
Purchase bills read by AI, checked by your accountant before posting

We build AI extraction for purchase invoices, freight invoices, bills of entry, purchase orders and bank statements. An LLM reads the PDF directly, with a prompt per document type. 88–95% of documents need zero correction, and every one still waits for a person to approve it before anything is posted to the books.
Who it's for: Trading, import-export and manufacturing businesses whose accounts team spends its day typing GST invoices, customs paperwork and bank statements into Tally.
How it works
- 01 A PDF arrives, uploaded in the browser or forwarded from a phone.
- 02 An AI model reads the PDF directly, with instructions for each type of document.
- 03 A person checks the extracted fields on screen and approves them.
- 04 Approved documents post into Tally as vouchers. Nothing is posted without approval.
The numbers
- Purchase order, zero-correction rate
- 95%
- Purchase invoice, zero-correction rate
- 94%
- Freight invoice, zero-correction rate
- 91%
- Bank statement, zero-correction rate
- 89%
- Bill of entry, zero-correction rate
- 88%
- Documents posted without human approval
- None
What to require from any vendor for this: 2 lines on the ERP requirements checklist, each with the test to ask for in a demo.
Questions buyers ask
- How accurate is it?
- 88–95% of documents need no correction, depending on the type: purchase orders highest at 95%, bills of entry lowest at 88%.
- Which documents can it read?
- Purchase invoices, freight invoices, bills of entry, purchase orders and bank statements.
- Does anything get posted on its own?
- No. Every document waits for a person to approve it before it reaches the books.
How it works, in detail
- AI extraction with a human in the loop, five document types
- The same confidence score, two different autonomy rules
- Keeping test certificates for a boiler's IBR folder
- AI drafts, a person confirms — never auto-post extracted data
- Let one deliberate human correction teach the system — but only for narrowly trusted error shapes
Built for
- LS Technologies — Electronics-components import/export trading
- A boiler and pressure-vessel manufacturer — Boiler and pressure-vessel manufacturing
Industries
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