Meetily
Meetily is an open-source, privacy-focused, on-device AI meeting assistant. Unlike typical cloud-based meeting summarization services that transmit audio data to external servers, raising privacy concerns, this tool performs 100% local audio capture, real-time transcription, summarization, and Q&A within the user's personal computer (PC). Its core architecture combines the desktop cross-platform framework Tauri, the front-end framework Next.js, and Rust for the back-end, which requires high-performance computing.
Meetily is an open-source, privacy-focused, on-device AI meeting assistant. Unlike typical cloud-based meeting summarization services that transmit audio data to external servers, raising privacy concerns, this tool performs 100% local audio capture, real-time transcription, summarization, and question answering within the user's personal computer (PC). Its core architecture is designed around the desktop cross-platform framework Tauri, combining Next.js for the front-end and Rust for the back-end, which requires high-performance computing. This allows it to operate offline, completely disconnected from external networks, and leverages Whisper and Parakeet ONNX models locally to ensure excellent processing speed.
Existing AI meeting assistant tools primarily use a method of recording by having a virtual bot participate in video conferences, which has the limitations of visually exposing the recording to other participants and being restricted by corporate security policies. Meetily adopts a bot-free approach, directly capturing system audio in the background, allowing secure and confidential transcriptions to be obtained without the attention or security restrictions of other participants. This is like having your own private record-keeper that is not exposed externally, and it operates flexibly regardless of the video conferencing platform (Zoom, Teams, etc.). Furthermore, by using a local Ollama server and open-source large language models (LLMs) for summarization instead of external paid APIs, it eliminates long-term costs and guarantees complete data sovereignty.
Biotech researchers and pharmaceutical developers conduct numerous confidential meetings that require extreme security, such as discussions on the structural formulas of new drug candidates before patent applications or the design of clinical trials. When using cloud-based tools, they had to rely on manual recording due to concerns about technology leakage, but by combining Meetily and Ollama's Llama 3 model, meeting minutes can be automatically generated in complete security on an offline workstation. The researcher activates the audio capture function, conducts the meeting, and then uses the local Whisper model to convert one hour of presentation audio data into high-quality Korean text in just over two minutes. The converted text is stored in a SQLite local database, allowing keyword searches at any time, and the core milestones and action items are quantitatively extracted through Ollama's summarization function and safely integrated as knowledge assets in the internal RAG (Retrieval-Augmented Generation) system.
💻 System Requirements
NVIDIA GPU VRAM 4GB or higher recommended (speed improvement when Metal/CUDA acceleration is enabled; reduced transcription speed when running on CPU alone)
Approximately 1GB (including Whisper/Parakeet ONNX models and local database size; additional LLM capacity is separate)
⚡ Installation
4-1. Quick Start
macOS (using Homebrew):
brew tap zackriya-solutions/meetily
brew install --cask meetily
4-2. Detailed installation
Windows:
- Download the latest
meetily_x64-setup.exeor.msifile from the official GitHub Releases page. - Run the downloaded file and follow the on-screen instructions to install it.
Source build for developers (requires Rust and Node.js):
# Clone repository
git clone https://github.com/Zackriya-Solutions/meetily.git
cd meetily
# Install frontend dependencies
npm install
# Starting Tauri Development Server and Building
npm run tauri:dev
FAQ
What is Meetily?
Meetily is an open-source, privacy-focused, on-device AI meeting assistant. Unlike typical cloud-based meeting summarization services that transmit audio data to external servers, raising privacy concerns, this tool performs 100% local audio capture, real-time transcription, summarization, and question answering within the user's personal computer (PC). Its core architecture is designed around the desktop cross-platform framework Tauri, combining Next.js for the front-end and Rust for the back-end, which requires high-performance computing. This allows it to operate offline, completely disconnected from external networks, and leverages Whisper and Parakeet ONNX models locally to ensure excellent processing speed. Existing AI meeting assistant tools primarily use a method of recording by having a virtual bot participate in video conferences, which has the limitations of visually exposing the recording to other participants and being restricted by corporate security policies. Meetily adopts a bot-free approach, directly capturing system audio in the background, allowing secure and confidential transcriptions to be obtained without the attention or security restrictions of other participants. This is like having your own private record-keeper that is not exposed externally, and it operates flexibly regardless of the video conferencing platform (Zoom, Teams, etc.). Furthermore, by using a local Ollama server and open-source large language models (LLMs) for summarization instead of external paid APIs, it eliminates long-term costs and guarantees complete data sovereignty. Biotech researchers and pharmaceutical developers conduct numerous confidential meetings that require extreme security, such as discussions on the structural formulas of new drug candidates before patent applications or the design of clinical trials. When using cloud-based tools, they had to rely on manual recording due to concerns about technology leakage, but by combining Meetily and Ollama's Llama 3 model, meeting minutes can be automatically generated in complete security on an offline workstation. The researcher activates the audio capture function, conducts the meeting, and then uses the local Whisper model to convert one hour of presentation audio data into high-quality Korean text in just over two minutes. The converted text is stored in a SQLite local database, allowing keyword searches at any time, and the core milestones and action items are quantitatively extracted through Ollama's summarization function and safely integrated as knowledge assets in the internal RAG (Retrieval-Augmented Generation) system.
When should I use Meetily?
Meetily is an open-source, privacy-focused, on-device AI meeting assistant. Unlike typical cloud-based meeting summarization services that transmit audio data to external servers, raising privacy concerns, this tool performs 100% local audio capture, real-time transcription, summarization, and Q&A within the user's personal computer (PC). Its core architecture combines the desktop cross-platform framework Tauri, the front-end framework Next.js, and Rust for the back-end, which requires high-performance computing.
📝 Update Notes
- vv0.4.19/15/2026
Meetily v0.4.1 업데이트는 회의 기록의 정확도와 안정성을 대폭 강화했습니다. 전사(transcription) 과정에서 데이터가 누락되거나 끊기는 오류를 수정하여, 중요한 실험 프로토콜이나 세미나 내용을 더욱 정밀하게 기록할 수 있습니다. 또한 블루투스 마이크 연결 안정성과 실시간 음성 분할 기능이 개선되어, 긴 학술 회의 중에도 끊김 없는 기록이 가능합니다. 요약 기능의 UI와 분석 로직도 정교해져, 복잡한 연구 논의 내용을 한눈에 파악하기 훨씬 수월해졌습니다.
- vv0.4.07/6/2026
What's Changed
- feat/multi language summary by @p-s-vishnu in https://github.com/Zackriya-Solutions/meetily/pull/447
- docs: archive legacy backend setup guidance [skip ci] by @safvanatzack in https://github.com/Zackriya-Solutions/meetily/pull/463
- fix: make analytics opt-in by default [skip ci] by @safvanatzack in https://github.com/Zackriya-Solutions/meetily/pull/452
- fix: use TDT duration head in Parakeet greedy decoder by @lorenzojb in https://github.com/Zackriya-Solutions/meetily/
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