SoloBooks AI: A Local-First AI Bookkeeper for Freelancers | Hacktoberfest 2026
This is my submission for the Hacktoberfest Open-Source AI Challenge: Week 2 — Side Hustle . What I Built Meet SoloBooks AI — a local-first AI-powered expense and receipt organizer built for freelancers, independent creators, and side hustlers. When you're running a small side business, keeping track of receipts and expenses can quickly become a tedious task. Receipts get scattered across…
This submission for the Hacktoberfest Open-Source AI Challenge is the second week's entry, focusing on a side hustle. SoloBooks AI is an AI-powered expense and receipt organizer designed specifically for freelancers, independent creators, and side hustlers. Keeping track of receipts and expenses can quickly become overwhelming for small business owners, taking up valuable time that could be spent on actual work. The SoloBooks AI app aims to simplify this process.
The app offers several features, including receipt processing using OCR and AI-assisted extraction, expense organization in one central location, a visual expense dashboard, CSV export for further analysis and bookkeeping workflows, and uses Gemma 3 4B through an Ollama-compatible inference setup.
The main objective of SoloBooks AI is to help users save time on financial paperwork so they can focus more on growing their businesses. It is essential to note that this is a prototype, not a replacement for professional accounting or tax advice.
A YouTube video demonstration can be found at https://youtu.be/v3q1ZUP28O0, showcasing the project and its workflow. The code for the application, including setup instructions and tests, is available on the GitHub repository at https://github.com/rudrakshk25060-csds/solobooks-ai. The technology stack includes Python and FastAPI for the backend, SQLite for database storage, HTML, CSS, and JavaScript for the frontend, Chart.js for charts, and Tesseract OCR for receipt processing.
Building SoloBooks AI involved using an AI-assisted development workflow and open-source technologies. The application was developed using FastAPI for its backend, SQLite for storing expense records, and a lightweight web interface built with HTML, CSS, and JavaScript. Receipt processing combines OCR and AI-assisted extraction, with Gemma 3 4B being utilized through an Ollama-compatible inference setup.
One crucial design decision was to keep financial calculations in the application logic rather than relying on an LLM to perform arithmetic. This way, AI focuses on interpreting unstructured information, while deterministic code handles calculations. This approach ensures more control over data and infrastructure, making it suitable for handling financial documents.
Local inference offers advantages such as more control over data, flexibility, cost reduction, and less vendor lock-in, but it also has trade-offs, including hardware requirements and potential model performance limitations. The primary goal is to make useful AI-powered bookkeeping tools more accessible to individuals who cannot afford expensive software for their small side hustles.
Written by urgent.news from Dev.to's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.
