We were frustrated by the limitations of traditional file managers. For decades, we've been forced to organize digital lives into rigid, list-based hierarchies and nested folders that hide information rather than reveal it. Our brains don't work in lists; they work through associations and spatial relationships. We wanted to build a system that reflects this—moving away from "where did I save that file?" to "what is this project about?" by using semantic and visual grouping to reveal the hidden structure of our data.
Sorana is an AI-powered visual workspace that transforms how you organize and interact with digital files. Using semantic AI analysis, it automatically groups related files and folders onto a spatial 2D canvas, replacing traditional hierarchies with intuitive visual layouts. Build drag-and-drop workspaces and no-code agent pipelines, connect to on-prem or cloud AI backends (OpenAI, Mistral, LLamacpp, Lemonade, Ollama), and keep your data under your control.
Demonstration of Sorana workspace
Get started with your intelligent workspace.
$ md5sum Sorana.exe 55e9f2f8179fc59ce552947d30433d4f
Sorana is designed for users who need to organize and analyze complex digital information:
The application functions through these steps:
Sorana uses AI models to intelligently group files and folders based on semantic meaning and logical relationships. The built-in default model is lightweight and works offline, but may not always classify files perfectly, especially for less common file types. For optimal performance, we strongly recommend using Llama 3.1 8b Instruct or higher models. Processing time depends entirely on the folder size - fewer files mean faster processing times. Naturally, the best performance is achieved with paid cloud services.
If your system has limited hardware resources, you have two main options:
Note: Larger models can provide better grouping, but require more memory and processing power. Processing time is directly proportional to the number of files - fewer files result in faster processing. For the best performance, especially with large folders, we recommend using paid cloud services.
Sorana includes powerful Optical Character Recognition (OCR) capabilities for processing various document types with support for common character encodings:
To enable OCR for PDFs with images, you need to install the official Tesseract OCR engine with default settings and ensure it's available in your system PATH. Tesseract is an open-source OCR engine that provides high-quality text extraction from images.
Download Tesseract from:
The application primarily uses UTF-8 encoding for document processing and falls back to Latin-1 (ISO-8859-1) when UTF-8 decoding fails. For optimal results, we recommend using UTF-8 encoding for your documents. This ensures the best compatibility with international characters and special symbols.
Technical differences between Sorana and traditional file management approaches:
| Feature | Sorana | Traditional Tools |
|---|---|---|
| File Organization | AI-driven spatial layout | Manual folder structure |
| Document Analysis | Interactive document interface | Basic search functionality |
| Workflow Creation | Visual drag-and-drop interface | Manual scripting |
| Visualization | Dynamic visual representations | Static list views |
| Privacy | Local AI processing | Cloud-based processing |
| Deployment | Portable application | Installed application |
Basic installation steps:
Sorana.exe.| Component | Minimum |
|---|---|
| OS | Windows 11 (64-bit) |
| 🧠 AI Support | Built-in models or on-prem/cloud AI services |
| 💾 RAM | ≥ 4 GB |
| 💽 Storage | Minimum 2 GB (app + model) |
| ⚡ Rights | Standard user |
Download and install the application.
$ md5sum.exe Sorana.exe 55e9f2f8179fc59ce552947d30433d4f
Support Sorana development.
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