What I Built
Meet LazyFlow AI — an AI-powered file organizer that helps people spend less time managing files and more time doing what matters.
We all have folders filled with confusing filenames, certificates we cannot find, resumes with generic names, and images mixed with important documents. LazyFlow AI helps turn that digital mess into an organized collection.
✨ What it can do:
- 📂 Categorize files into meaningful folders.
- 🧠 Suggest descriptive filenames using file metadata and content-aware AI.
- 📄 Recognize certificates and resumes using text extraction and OCR.
- 🖼️ Classify images when visual recognition can identify their contents.
- 📦 Package selected, organized files into a downloadable ZIP.
- ✏️ Let users review and customize suggested names and destination folders.
The goal is simple: make file organization easier, faster, and less boring.
Demo
🎥 Watch the project demo: LazyFlow AI — YouTube Demo
🌐 Live app: https://lazy-flow-ai.vercel.app
Code
💻 GitHub Repository: LazyFlow AI
How I Built It
LazyFlow AI combines a modern web interface with a Python backend and open-weight AI.
Technology stack:
- Frontend: React, TypeScript, and Vite
- Backend: Python and FastAPI
- AI model: Meta Llama 3.1 8B Instruct, accessed through Backboard
- Text recognition: OCR and document text extraction
- Image recognition: MobileNetV3-Small for visual classification
- Export: ZIP generation with organized folder structures
The application uses file metadata, extracted text, and image classification where appropriate to produce more useful organization suggestions.
The AI does not simply rename everything blindly. When the available evidence is insufficient, the application can retain the original filename rather than inventing details.
Why Does Open Innovation Matter?
Open innovation matters because AI tools should not be limited to a handful of closed platforms.
By building around an open-weight model, I could create an AI-powered utility while keeping the model choice visible and the application architecture flexible. Open-weight models also make it possible for developers to experiment, inspect model options, and adapt applications to different environments.
Using Meta Llama 3.1 8B Instruct through Backboard helped me integrate AI into a practical application without building a model from scratch.
For me, open innovation means making useful AI applications more accessible to developers and users.
The Lazy Payoff
Imagine downloading a certificate with a random filename, searching through dozens of files to find your resume, or manually sorting images into folders.
LazyFlow AI aims to reduce that repetitive work by suggesting meaningful filenames, grouping related files, and packaging the results into a ZIP archive.
Instead of manually organizing every file, users can upload, review, customize, and export.
Upload the mess. Let AI do the rest.
Prize Categories
Open-Source AI Challenge — Week 3: Slow and Steady
Best Use of Backboard.
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