BillSift: a local GST bill sorter that double-checks its own AI
This is a submission for the Hacktoberfest Open-Source AI Challenge Week 2: Side Hustle What I Built BillSift turns a folder of bill photos and PDFs into a clean spreadsheet for your CA, entirely on your own laptop. Anyone in India who runs a small shop, freelances, or works with a Chartered Accoun
Hacktoberfest Open-Source AI Challenge Week 2: Side Hustle Submission 馃捀
This is a submission for the Hacktoberfest Open-Source AI Challenge Week 2: Side Hustle
BillSift turns a folder of bill photos and PDFs into a clean spreadsheet for your CA, entirely on your own laptop.
Anyone in India who runs a small shop, freelances, or works with a Chartered Accountant ends up with a pile of GST bills: petrol pumps, restaurants, hardware shops, online orders. Someone has to read each one and type the vendor, GSTIN, date, taxable amount, CGST/SGST/IGST and total into a sheet. That someone is usually the CA's staff, once a quarter, and a wrong digit causes trouble at filing time.
Who would pay: freelancers and small shops who want to hand their CA clean data, and small CA practices that spend staff hours on data entry. I haven't sold it yet, so this is a prototype and not a business. But a per-client price only works if the cost per bill is close to zero, and local models give you that.
Live demo: https://billsift-demo.onrender.com
Press Try it with 11 sample bills to see it work: most pass every check, and 3 are flagged for review, with the reason shown for each. It runs on Render's free tier, so the first visit after a quiet spell can take about a minute while the server wakes up.
The hosted copy is deliberately limited. A free server has 512 MB of RAM and no GPU, so it has no AI model, it only shows pre-processed synthetic sample bills, and uploads are switched off. That also means nobody's real bills ever reach a server. The full version runs on your own laptop with a local model.
A local, privacy-first GST bill sorter for freelancers, small shops and their CAs.
Drop in photos or PDFs of bills. BillSift reads them with open-source OCR and a small open-weight LLM running on your own laptop, then checks the result with plain code before anything reaches your spreadsheet. Your clients' financial documents never leave your machine and there is no per-page API bill.
Small local models make small mistakes: a swapped digit, a wrong field. In accounting a silently wrong digit is worse than a missing one. So the model's output is never trusted as-is: