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Sneha Ghosh
Sneha Ghosh

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Local Invoice & Receipt Sorter

#devchallenge #hf26challenge

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

What I Built

I built Local Invoice & Receipt Sorter, a privacy-first bookkeeping tool for freelancers, creators, and small side-hustle businesses.

Managing receipts and invoices manually is time-consuming and error-prone. This tool allows users to upload multiple invoice or receipt files and automatically extracts useful bookkeeping information, including:

  • Vendor name
  • Total amount
  • Date
  • Tax amount
  • Expense category
  • Source filename

The application also detects potential duplicate expenses, summarizes spending by category, and exports the processed data as a bookkeeping-ready CSV file.

The main users are freelancers, independent contractors, and small business owners who want a lightweight alternative to expensive accounting software while keeping their financial documents private.

Demo

The project currently runs locally as a Flask web application.

To run it:

python -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt
python app.py
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Then open:
Text

http://localhost:5000

Code

The complete source code is available on GitHub:

https://github.com/SnehaghoshBarsha444/hf26_-Side_Hustle-DevChallange-
How I Built It

The application is built with Python and Flask.

The document-processing pipeline uses open-source tools, including:

Tesseract OCR through pytesseract for extracting text from invoice and receipt images
Pillow for image processing
pypdf for extracting text from PDF files
Python-based parsing and classification for identifying vendors, dates, totals, taxes, and expense categories
Flask and HTML/CSS for the web interface
CSV generation for exporting bookkeeping data
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Users upload one or more files through the browser. The application processes each document locally, extracts the relevant fields, identifies possible duplicates, groups expenses by category, and presents the results in a simple dashboard.

No financial documents need to be sent to a remote server or third-party API.
Why Does Open Innovation Matter?

Open innovation made it possible to build this project using accessible, transparent, and locally runnable tools instead of relying on expensive proprietary accounting APIs.

Using open-source OCR and document-processing libraries provides several advantages:

Financial documents remain on the user's machine
Users are not locked into a cloud provider
The project can run with low infrastructure costs
Developers can inspect, improve, and customize the extraction logic
The tool can be adapted for different invoice formats, languages, and bookkeeping workflows
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For a side-hustle product, local-first open-source technology makes it possible to create a useful and affordable tool while respecting user privacy.
My Agent Session

My First User

Prize Categories

Open-Source AI
Productivity
Small Business / Side Hustle
Privacy-first Technology
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Important: Your current implementation uses open-source OCR and rule-based document extraction, but I did not find a generative AI or local language model in the repository. To keep the submission accurate, describe it as an open-source OCR and document-processing project unless you add an actual open-weight AI model.

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