Softpiper Solutions

Finance and accounting · Documents and back office

Invoice-to-Tally and GST reconciliation assistant

Extract purchase-invoice data from PDFs and photos, post approved vouchers to TallyPrime, chase vendors on WhatsApp and clear GST mismatches before filing.

  • ClaudeAnthropic
  • Typical timeline: 3–6 weeks

The problem

Small and mid-sized businesses re-key purchase invoices into Tally, chase vendors on WhatsApp for missing documents and reconcile GST mismatches by hand.

  • Month-end means hours of data entry.
  • Missing invoices are chased one message at a time.
  • GST mismatches surface just before filing.

How we solve it

Claude reads invoices from PDFs and phone photos into a strict schema, posts vouchers to TallyPrime after an accountant approves, drafts vendor follow-ups on WhatsApp and lists mismatches to clear before filing.

It plugs into TallyPrime, Zoho Books, Gmail / Google Drive and WhatsApp Business, so nothing you rely on today is replaced. The architecture below shows each step and which model does the work.

Architecture

From your stack, through the AI layer, to numbers you can track

Each step names the model or system doing the work. Writes to your systems wait for a person to approve them.
Invoice-to-Tally and GST reconciliation assistant. Your systems (TallyPrime, Zoho Books, Gmail / Google Drive and WhatsApp Business) connect to Softpiper's AI layer, which runs these steps: Collect invoices (Gmail · Drive · WhatsApp); Extract (Claude Haiku / Sonnet · vision); Check (Validation rules); Approve (Approval screen); Post (TallyPrime HTTP/XML · Zoho MCP); Follow up with vendors (WhatsApp Cloud API). Outcomes are measured as invoices processed per hour, data-entry error rate, days to close the month and mismatches resolved before filing.

Your stack

  • TallyPrime
  • Zoho Books
  • Gmail / Google Drive
  • WhatsApp Business

AI layer

Softpiper AI layer

  • Claude
  1. Collect invoices, using Gmail · Drive · WhatsApp

    Invoices arrive by email, Drive folder or WhatsApp photo.

  2. Extract, using Claude Haiku / Sonnet · vision

    Supplier, GSTIN, invoice number, line items, tax and totals are extracted into a strict schema.

  3. Check, using Validation rules

    Duplicates, arithmetic and GSTIN format are checked; anything odd is flagged.

  4. Approve, using Approval screen

    An accountant approves or corrects each voucher.

  5. Post, using TallyPrime HTTP/XML · Zoho MCP

    Approved vouchers are posted to TallyPrime over its HTTP/XML interface, or to Zoho Books through Zoho MCP.

  6. Follow up with vendors, using WhatsApp Cloud API

    Drafted WhatsApp messages ask vendors for missing or corrected invoices.

Outcomes you measure

  • Invoices processed per hour
  • Data-entry error rate
  • Days to close the month
  • Mismatches resolved before filing

Why this model

Why Claude

We choose per task on capability, cost and where your data must stay. Final versions are picked at kickoff.
ClaudeAnthropic

Claude reads PDFs and images, including phone photos of paper invoices, and returns schema-valid fields. A small model handles volume, a larger one handles messy documents, and month-end backlogs run through the Batch API at half price.

Delivery

What you get, how long it takes, and how we keep it safe

Guardrails

  • An accountant approves every voucher before posting.
  • Duplicate detection on supplier, invoice number and amount.
  • Statutory filings remain your accountant's responsibility.
  • Vendor messages use approved WhatsApp templates.

Plus the guardrails on every build: facts from your systems, approvals for writes and money, a human one step away, audit logs and evals. See all

Deliverables

  • Extraction pipeline for PDFs and photos
  • Validation and duplicate checks
  • Approval screen
  • TallyPrime or Zoho Books connector
  • Pre-filing mismatch report

Typical timeline

  1. Extraction, approvals and Tally connector3–6 weeks

A planning range for a first production release. We confirm scope, price and dates in a tailored proposal.

KPIs to track

  • Invoices processed per hour
  • Data-entry error rate
  • Days to close the month
  • Mismatches resolved before filing
  • Vendor response time

Goals we agree with you and measure from a baseline. They are what we track, not results we promise.

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Pip · Softpiper's AI

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Ask Pip how this would work for you

Pip is Softpiper's AI. Tell it what you run today and it will walk through how this playbook fits, what we would build first and a tailored price range. Or book a call with the team.

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