A local AI that types up a Brazilian accountant's receipts (and knows when it's wrong)

Hacktoberfest Open-Source AI Challenge Week 2: Side Hustle Submission 💸

This is a submission for the Hacktoberfest Open-Source AI Challenge: Week 2 — Side Hustle.

A self-employed accountant in Brazil gets ~100 documents a week from her small-business clients: NF-e invoices (PDF), NFC-e receipts photographed on a phone, Pix transfer screenshots, and the occasional handwritten recibo. Today she types every one of them into a spreadsheet by hand.

Leitor de notas ("receipt reader") turns that pile into a reviewed Excel file:

Who pays for it? Accountants bill small businesses a monthly fee, and data entry is the part of that work that doesn't scale. Saving a few hours a week per client is worth money. The catch is that these are clients' financial records, covered by Brazil's data protection law (LGPD). "Upload your clients' bank receipts to our cloud" is a hard sell to her, and to her clients.

This project only works because the model is open-weight and runs on the machine:

Evaluation on 10 fictitious documents (text PDFs, Pix receipts, tilted phone photos, a handwritten receipt, and one deliberately unreadable blurry receipt):

95% of fields correct. All three misses come from the blurry receipt. The model hallucinated a date and a CNPJ there, and validation caught both, so the document landed in the review queue, which is exactly what should happen. Average time on an AMD RX 9060 XT (Ollama, Vulkan): 2.2 s per text PDF, 4.0 s per image. That's about 5 minutes for a week of documents.

Projeto para o DEV Hacktoberfest 2026 — desafio "Side Hustle": IA open-source rodando 100% local (Ollama + Qwen 2.5 / Qwen 2.5-VL) para ler notas fiscais, cupons NFC-e, comprovantes de Pix e recibos de uma contadora autônoma e transformar tudo numa planilha Excel, sem nenhum dado sair da máquina (LGPD).

Resultado nas amostras: 95% dos campos corretos, com os 2 documentos problemáticos enviados para revisão.