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Meet Project Alex, an experimental AI desktop companion that runs entirely offline on Windows. It follows your cursor, sits on active windows, and chats with you in real time via voice. Local Whisper, Llama, and Kokoro TTS ensure privacy. Early alpha—expect bugs.

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Publisher/Developer

berillidev

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Project Alex description

Project Alex — Your Intelligent Desktop Companion

Project Alex is an experimental AI assistant that lives on your desktop, not in a browser tab. It runs entirely offline on your machine, seeing your cursor, sitting on your active windows, and talking with you in real-time through voice. This is an intimate desktop companion designed to blend into your work environment while keeping control firmly in your hands.

Core capabilities

  • Full voice control: Speak naturally and engage with Alex. You don’t need a dedicated wake word—the system uses voice activity detection to listen when you start talking, letting conversations flow as you work.
  • Interruptible conversations: If you need to change direction, you can cut Alex off mid-sentence to switch topics, just like talking to a human partner.
  • Private and offline: All processing happens locally. Whisper handles speech-to-text, Llama powers the local reasoning, and Kokoro provides text-to-speech. No audio or personal data leaves your PC.
  • Desktop presence: Alex follows your cursor, reacts to your actions, and sits on your active windows to stay contextually aware as you work.

Early access and reliability

This is an Alpha build. You may encounter bugs with window transparency or overlapping interfaces, and the settings menu is a work in progress. If you experience crashes or issues, please share feedback in the Community Hub to help improve the experience for everyone.

System requirements

  • OS: Windows 10 or Windows 11
  • GPU: NVIDIA GTX 1060 (6GB) or better recommended
  • RAM: 8GB minimum, 16GB+ recommended
  • Microphone: Required

Technology and build

Project Alex is built with Godot 4 and runs on a local AI stack for privacy and responsiveness. It leverages Silero VAD for voice activity detection, Whisper for speech-to-text, Llama for local language modeling, and Kokoro TTS for natural-sounding speech synthesis.