Local AI for developers.
No Docker. No cloud. No drama.
A desktop AI coding assistant you can run fully offline with Ollama. Your proprietary code never leaves your machine. Double-click to install.
The reality
Most local AI tools for developers require Docker, a working Python environment, a specific Node version, and 45 minutes of configuration before you can ask a single question. That friction kills the workflow before it starts.
Cloud coding assistants are faster to set up, but they process your code on external servers. For developers working on proprietary or NDA-protected codebases, that is not acceptable. For developers on restrictive corporate networks, it may not even be possible.
How Skales helps developers
Zero-config local AI. Works offline. Your code stays yours.
Ollama integration - truly local
Connect Skales to Ollama and run Llama 3, Mistral, DeepSeek Coder, or any model locally. Zero network calls, zero API costs, zero proprietary code leaving your machine. Works on M-series Mac and modern Windows PCs.
Debug, refactor, and review
Paste code and ask Skales to find the bug, suggest a refactor, or review the logic. Voice input supported - describe the problem out loud while looking at the screen instead of switching windows.
No Docker, no config hell
Install Skales with a double-click. No Docker, no WSL2 setup, no Node version conflicts, no Python environment to configure. It runs as a desktop app. You open it and it works.
Context-aware development
Skales has persistent memory. It remembers your project context across sessions - the architecture decisions, the constraints, the naming conventions - so you do not re-explain things every time.
Proprietary code stays local
Working on closed-source code under NDA? Skales with Ollama ensures your codebase never leaves your machine. No API call to OpenAI, no data in Anthropic's servers. Your IP stays yours.
Works without internet
On a plane, in a basement, behind a corporate firewall that blocks AI APIs? Skales with Ollama works fully offline. All AI processing happens on your CPU or GPU - no internet required.
Example: Debugging with Ollama
You ask: "This Python function is returning None when the input list is empty but it should return an empty dict. Here is the code."
Skales: Spots the missing else branch in the list comprehension. Suggests the fix and a unit test for the edge case.
You ask: "Explain what this 200-line legacy function does. I need to refactor it into smaller, testable pieces."
Skales: Plain-English explanation of the function's logic, followed by a proposed split into 4 smaller functions with clear responsibilities.
You ask: "Write the docstring for this function in Google format. Include Args, Returns, Raises, and a usage example."
Skales: Complete Google-style docstring, ready to paste. All offline, no API call.
“Finally - a local AI I could set up in 5 minutes, not 5 hours. And it actually works offline.”
Free for personal use. Windows and macOS. No account required.
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