speakr vs meetily

Audio transcription and meeting notes compared

speakr is a self-hosted web app for turning recordings into searchable transcripts, summaries, and notes. meetily is a desktop meeting assistant with local transcription and storage; the main difference is speakr’s broader shared recording library versus meetily’s focus on meetings and local processing.

speakrmeetily
LanguagePythonRust
LicenseAGPL-3.0MIT
Stars4.1k31.4k
Forks3433.4k
Last analyzedOct 3, 2026Oct 3, 2026

Key differences

  • speakr supports audio capture and uploads for a searchable library of recordings, while meetily focuses on capturing and importing meeting audio.
  • speakr can connect to hosted or self-hosted transcription services; meetily transcribes locally with Whisper or Parakeet models.
  • speakr provides folders, tags, sharing, permissions, public links, and retention policies; meetily stores recordings and transcripts locally on the user's machine.
  • speakr is written in Python and licensed under AGPL-3.0, with a commercial license also offered; meetily is written in Rust and licensed under MIT.
  • speakr is a self-hosted web app; meetily is a desktop application for macOS, Windows, and Linux, with platform-dependent installation and acceleration options.
  • The supplied project figures list 4.1k stars and 343 forks for speakr, and 31.4k stars and 3.4k forks for meetily.

Choose speakr if you…

  • need a shared library for recordings, with folders, tags, groups, and configurable sharing.
  • want to search or ask questions across recordings and link answers to transcript moments.
  • need to configure transcription and language-model services, including self-hosted options.
Read the speakr analysis →

Choose meetily if you…

  • want local transcription and storage in a desktop meeting assistant.
  • need to capture microphone and system audio together for meetings.
  • want to use local Ollama summaries or route summaries through a supported remote provider.
Read the meetily analysis →

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This comparison is generated with AI from the OSRepos analyses of both projects. Always check each project's repository and documentation before choosing.