SlowSort AI — Let AI Handle the File Chaos

This is a submission for the Hacktoberfest Open-Source AI Challenge Week 3: Slow and Steady

What I Built

Ever opened your Downloads folder and found hundreds of files you meant to organize “later”?

That is the problem I wanted to solve with SlowSort AI.

SlowSort AI is a local-first, privacy-conscious file organization tool that helps turn a messy folder into something manageable. Instead of manually opening files, figuring out what they are, creating folders, renaming documents, and searching for duplicates, you can scan a folder and get an AI-assisted organization plan.

Here is what it does:

• Smart organization: Uses Google Gemini to suggest meaningful categories, destination folders, and cleaner filenames.
• Review before action: Lets you review, edit, approve, or reject proposed file operations before they happen.
• Duplicate detection: Uses SHA-256 content hashes to identify exact duplicate files and estimate wasted storage.
• Safer file operations: Prevents path traversal and accidental overwrites, and verifies file integrity before and after moves.
• One-click undo: Records completed operations locally so they can be reversed.
• Fallback sorting: Includes a deterministic rule-based organizer when AI inference is unavailable.

The idea is simple: spend less time managing files and more time doing the work those files are meant to support.

Demo

Repository: https://github.com/saivardhan1245/slowsort-ai

Live preview: https://slowsort-ai.onrender.com

The application is designed to run locally when working with files on your own computer. A hosted preview does not automatically have access to your computer's filesystem.

Note: The Render build recently encountered an esbuild dependency conflict. Verify the deployment is working before relying on the live-preview link.

Code

Explore the source code, setup instructions, and technical details here:

GitHub: https://github.com/saivardhan1245/slowsort-ai

The project is built with React, TypeScript, Vite, Tailwind CSS, Node.js, Express, SQLite, and Zod. It also includes tests for important filesystem, collision-prevention, and AI-resilience behavior.

How I Built It

I built SlowSort AI around the principle that file organization should be helpful without being destructive.

The frontend provides a reviewable interface for scanning files and inspecting proposed changes. The Node.js backend handles filesystem operations, hashing, validation, and persistence. SQLite stores operation history locally, while Zod validates structured AI responses.

For AI-powered suggestions, I integrated Google Gemini through the open-source @google/genai SDK. The model receives file metadata by default rather than the private contents of documents. Its suggestions are validated before they are presented to the user.

I also added a deterministic rule-based fallback so basic organization suggestions do not depend entirely on an available AI API.

A key engineering decision was to avoid automatic destructive actions. Duplicate files are identified, not automatically deleted. File changes require explicit approval, destination collisions are rejected, and completed operations can be undone.

Why Does Open Innovation Matter?

Open innovation matters because useful tools should be understandable, adaptable, and open to improvement—not just something people can use without knowing how it works.

By building SlowSort AI with open-source libraries and an inspectable codebase, I could combine AI-assisted classification with practical safeguards for real filesystem operations. Developers can study the implementation, test the safety logic, adapt the rules, and contribute improvements.

The project also demonstrates that AI does not need unrestricted access to private data to be useful. File metadata can provide enough context for organization suggestions while the actual file contents remain local by default.

For me, open source is not just about making code available. It is about making the design decisions, limitations, and opportunities for improvement visible to others.

Prize Categories

Add the partner prize categories that are explicitly listed on the challenge page and that SlowSort AI genuinely qualifies for.