From 430 MB to 13 MB: Building an Offline AI Model for Indian GST Invoices
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 8
We built Tiny GST, a compact AI model designed to extract structured data from Indian GST invoices directly on-device.
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.
馃敆 GitHub profile: https://github.com/sanprat 馃敆 Tiny GST repository: https://github.com/sanprat/GstEngine 馃敆 Full engineering article: https://pybankers.com/blog/from-430mb-to-13mb-offline-ai-gst-invoice 馃敆 PyBankers: https://pybankers.com