Solution blueprint · Finance and accounts · AI automation
AI invoice processing for an accounts team, posted to Tally
Supplier invoices arrive by email and WhatsApp as PDFs and photos. The system reads every field, checks GSTIN, arithmetic, purchase order and goods receipt, routes exceptions to a person and posts approved bills to TallyPrime.
Design mockup with sample data. This is a solution blueprint by Infovion Technologies, not a client engagement.
- 0
- invoices typed by hand in the designed flow
- 3-way
- match: invoice, purchase order, goods receipt
- 8 – 10 weeks
- from kick-off to go-live
- ₹3 – 7 lakh
- typical build budget in India
The situation
The problem this solves
A distribution company receives a few thousand purchase invoices a month from hundreds of suppliers, each in its own layout. Three people key them into Tally. Mistakes in GSTIN or tax amounts surface only when input tax credit does not match GSTR-2B, and nobody can say at month-end which bills are still waiting for approval.
Template-based OCR was tried and abandoned: every new supplier format needed a new template. The team wants extraction that copes with any layout, shows how confident it is, and never posts a doubtful bill without a person looking at it.
The system
What it includes
Capture from email, WhatsApp and upload
A dedicated inbox and WhatsApp number collect PDFs, scans and phone photos. Duplicates are caught by supplier, invoice number and amount.
AI extraction without templates
Supplier, GSTIN, invoice number and date, line items, HSN, taxable value, CGST, SGST, IGST and totals are read from any layout, each with a confidence score.
Automatic checks
GSTIN format and state code, arithmetic of every line and tax, HSN against the item master, and a three-way match with the purchase order and goods receipt note.
Exception queue
Only invoices that fail a check or fall below the confidence threshold reach a person, who sees the document beside the extracted fields and corrects in one screen.
Approval on mobile
Bills above a set value go to the right approver by amount and department, with reminders. The full trail is kept: who approved, when, and what was changed.
Posting to TallyPrime
Approved bills become purchase vouchers with the correct ledgers, cost centres and tax lines, sent to Tally as XML. The original document is linked to the voucher number.
How it works
From input to outcome
- 01
Collect
Email, WhatsApp and uploads land in one queue; files are stored unchanged.
- 02
Read
A vision-capable language model extracts header and line items into a fixed schema.
- 03
Validate
Rules check GSTIN, totals, HSN, duplicates and the PO and GRN match.
- 04
Review
Clean invoices pass through; exceptions wait for a person, with the reason shown.
- 05
Post
Approved bills are posted to Tally and the supplier ledger is updated.
What the design is built to achieve
- Straight-through posting for clean, printed invoices; a person reviews only the exceptions.
- Tax and GSTIN errors caught on the day the invoice arrives, not at GSTR-2B reconciliation.
- A live list of every bill by stage: received, in review, awaiting approval, posted.
- Accuracy measured on the company's own invoices in a proof of concept before the build is committed.
Technology
Claude API (vision), Node.js / NestJS, PostgreSQL, React, TallyPrime XML, Email and WhatsApp intake, Queue workers, AWS Mumbai
Budget and timeline
| Build, clients in India | ₹3 – 7 lakh |
|---|---|
| Build, clients outside India | $3,500 – 8,000 |
Timeline. 8 – 10 weeks, after a two to three-week proof of concept on 200 to 300 real invoices.
Running cost. Model usage per page processed, estimated from the monthly invoice volume during the proof of concept.
Indicative planning ranges for 2026. Every project receives its own fixed-price proposal after a first call. Source code and accounts belong to the client.
Request a fixed-price proposalFAQ
Frequently asked questions
Can AI read invoices and enter them in Tally automatically?
Yes. A vision-capable language model reads the invoice fields and line items, rules validate them, and approved bills are posted to TallyPrime as purchase vouchers through Tally's XML interface. Doubtful invoices are held for a person to check.
How accurate is AI invoice extraction?
On clear printed invoices accuracy is typically high; handwritten bills and poor photos need review. This design does not rely on a single accuracy figure: every field carries a confidence score and anything below the threshold goes to the exception queue.
How is this different from OCR software?
Traditional OCR needs a template for each supplier layout. A language model reads the document the way a person does, so a new supplier's format works without setup. The validation rules and Tally posting are ordinary, deterministic software.
Is our financial data used to train AI models?
No. We use business API plans under which the provider does not train on customer data, and the documents and extracted data stay in your own database.
Is this a project you delivered for a client?
No. This page is a solution blueprint, shown with sample data. Infovion JMS, our own product, already exports vouchers to TallyPrime in production; see the case studies.
More blueprints
Other systems we have designed
Looking for delivered work? Read the case studies on our school ERP, jewellery software and website.
Planning a system like this?
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