Our take
Activeregular commits and releases- Activity
- 72
- Community
- 60
- Issues
- 83
- Pull requests
- 36
+584 stars in the last 16 days
- Slower to merge pull requests than 93% of the projects we track
Meetily is an actively maintained, MIT-licensed desktop option for privacy-conscious meeting transcription, with a recent release cadence and contributions spread across its contributor community.
Good fit if
- You want local transcription and storage, and can use a desktop application on macOS, Windows, or Linux.
- Your workflow benefits from choosing between local Ollama summaries and supported external AI providers.
- You can work with a Rust 1.77 development environment if building from source; the project has regular commits and releases and is not dependent on one contributor.
Look elsewhere if
- You need speaker identification or other PRO-only capabilities now, rather than features described as planned or coming soon.
- You need a ready-made Linux installer, since the README directs Linux users to build from source.
- Your team requires a mature, documented automated test suite; the supplied project facts do not indicate tests.
All health signals
| Last commit | 2026-09-10 (29 days ago) |
|---|---|
| Commits, last 90 days | 100+ |
| Releases, last 12 months | 6 (latest v0.4.1, 2026-09-12) |
| Contributors | 18 (top contributor: 43% of commits) |
| Issues closed, last 90 days | 33+ (typically closed in 1 day) |
| Pull requests merged, last 90 days | 21 (typically merged in 7 days) |
| Project age | 22 months |
Checked on 2026-10-10 with the GitHub API.
Overview
Meetily is a desktop application for capturing meetings, producing live transcripts, and generating summaries. Its local-processing approach is aimed at people and organizations that want meeting content to stay on their own machine rather than rely on a hosted transcription service.
It combines a Rust backend with a Next.js interface and supports local transcription models as well as several AI providers for summaries. It is most relevant when privacy and control over recordings matter, and a locally run desktop workflow is acceptable.
Key Features
- Transcribes meetings in real time using Whisper or Parakeet models.
- Generates meeting summaries with Ollama or supported cloud and OpenAI-compatible providers.
- Captures microphone and system audio together, with audio mixing features.
- Imports existing audio for transcription or re-transcription.
- Stores recordings, transcripts, and transcription models locally.
- Offers platform-specific GPU acceleration, including Metal and CoreML on macOS and Vulkan-enabled Whisper builds on Windows.
Use Cases
- Professionals handling sensitive conversations who need transcripts and summaries without sending meeting recordings to a cloud transcription service.
- Teams that want to summarize meetings using a local Ollama model or their own OpenAI-compatible endpoint.
- Users with existing audio recordings who want to create or regenerate transcripts locally.
- Organizations that want to inspect, modify, or self-host an open-source desktop meeting tool.
What you need
Detected in the repository
- Rust 1.77 or newer (from Cargo.toml)
- Automated checks on GitHub Actions
License in plain words
MITpermissive
- Commercial use: yes
- Modify and redistribute: yes
- You must keep: the copyright and license notice
- Share your changes: no
A summary, not legal advice: the LICENSE file is what applies.
Getting Started
On macOS or Windows, download the current installer from GitHub Releases. For Linux or a source build, follow the build instructions. See the README for setup details and platform-specific requirements.
Alternatives
- mityu: Mityu emphasizes source-linked summaries and action items, while Meetily centers on local transcription and configurable AI providers.
| Project | Language | License | Stars | Status |
|---|---|---|---|---|
| meetily | Rust | MIT | 31.6k | Active |
| mityu | Rust | MIT | 1 | New |
Considerations
The project is active, with recent commits and releases, but the supplied project facts report no automated tests. Teams should validate transcription quality and their target platform before relying on it for critical records. GPU acceleration depends on the platform and build configuration, and the standard Windows installer requires an AVX2-capable x64 CPU. Linux users need to build from source. The README also distinguishes the free Community Edition from separate PRO capabilities, and lists speaker identification and several other features as planned or coming soon. The repository is MIT licensed; adopters should review the license terms for their distribution and use.
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