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From 430 MB to 13 MB: Building an Offline AI Model for Indian GST Invoices
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From 430 MB to 13 MB: Building an Offline AI Model for Indian GST Invoices

DEV Community: android·pybankers·1 day ago
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pybankers

We built Tiny GST, a compact AI model designed to extract structured data from Indian GST invoices directly on-device.

The model:

  • Runs fully offline
  • Uses only 13.17 MB after INT8 ONNX quantization
  • Achieves 64.2% entity F1 on unseen vendor layouts
  • Reaches 84.6% F1 for unit-price extraction
  • Reaches 80% F1 for HSN/SAC extraction
  • Achieves 100% CGST amount F1
  • Generates validated TallyPrime-formatted XML
  • Includes invoice deduplication using supplier GSTIN, invoice number, and financial year

The goal is simple: reduce cloud costs, protect sensitive invoice data, and make invoice processing work even in warehouses or rural areas with unreliable internet.

The project is currently an early developer release. The XML workflow has been tested against a mock Tally server; live TallyPrime import testing is still pending.

MachineLearning #Android #OpenSource #India