A developer just shipped something worth a real look. VaXil is an open-source, local-first AI assistant that doesn’t just answer questions. It opens apps, runs shell commands, browses the web, creates and edits files, sets reminders, and installs custom skills on demand. All from voice or text. All on your machine. Think about what that actually means in practice: you’re talking to something that can reach into your file system, execute code, and come back with a result, without ever touching a cloud server. This isn’t a chatbot with a nice UI. It’s closer to a scripting layer with ears, one that you actually own and control.
The project was built around a straightforward philosophy: your assistant should be a tool you own, not a subscription you rent. Most AI assistants in this space are thin wrappers around cloud APIs. They’re fast, polished, and convenient right up until the pricing changes or the API goes down or the terms of service get updated in a way you don’t like. VaXil takes a different bet: keep everything local, keep everything yours.
The twist: the voice stack is fully local too. Wake word, speech-to-text, text-to-speech, no cloud, no subscription, no data leaving your box. That’s the part most “AI assistant” projects quietly skip. It sounds like a small detail. It isn’t. A local voice pipeline means the assistant works offline, responds without network latency, and never logs your commands to a third-party server. If you’re asking your assistant to run shell scripts, open sensitive files, or automate anything touching real data on your machine, that distinction matters a lot. Other projects in this space will handle the AI backend locally but then quietly phone home for speech recognition or text-to-speech. VaXil closes that gap entirely, handling the full audio pipeline on-device from start to finish.
🔧 How to try it:
- Clone the repo at github.com/xRetr00/VaXil, the README is clean and the setup is well-documented for a project this early in its development
- Pick your AI backend, local model or API-based, your call. If you want full offline capability, point it at a locally running model like Ollama. If you want stronger reasoning and you’re okay with API calls specifically for the AI layer, you can do that too. The voice stack stays local either way.
- Configure your wake word and voice settings. Pick something distinct from words you use casually in conversation so you’re not accidentally triggering it mid-sentence while talking to someone else in the room.
- Say the word. It listens. Ask it to open an app, write a file, run a script. Start simple: “open Chrome” or “create a file called notes.txt on my desktop.” Once you trust the setup, push it further with multi-step requests.
- Install extra skills via URL to add new capabilities without touching core code. This is where the real leverage lives, and it deserves more than a single line.
💡 Pro tip: The skill system is the sleeper feature here. Tools installed via URL means the community can extend VaXil without forking the whole project. That’s how this thing compounds over time. To be specific about why that architecture matters: a fork-to-extend model creates fragmentation. Every developer builds their own version, and the ecosystem splinters into a dozen incompatible branches. URL-installed skills keep a shared core while allowing an unlimited surface area of extensions on top of it. You can already imagine a skill ecosystem forming around this: a “git workflow” skill, a “calendar management” skill, a “research and summarize” skill, each one installable with a single command and shareable with the whole community. The project is early enough that there’s real opportunity here. If you build something useful and share the URL, you’re at the front of a community that’s just getting started.
Still early.
The Windows-only limitation will frustrate Linux folks. But the architecture is solid and the direction is clear: an AI that acts, not just responds. Being Windows-only at launch isn’t necessarily a permanent decision. It’s a scoping call that let the developer ship something that actually works rather than a half-working cross-platform prototype. The underlying components (wake word detection, local speech models, shell execution) are all portable in principle. Cross-platform support is the kind of addition that lands once the core stabilizes, and the core here looks stable enough to build on. If Linux or macOS support is what you’re waiting for, watch the issues tab and consider contributing. If you’ve been waiting for a JARVIS that doesn’t phone home to OpenAI every time you ask it to open a file, this one’s worth bookmarking. 👉 Grab it here: github.com/xRetr00/VaXil
I attempted to build a real JARVIS — so i build a local Assistant that actually does everything.
by u/Apart_Operation_9358 in PromptEngineering