Anarlog

Anarlog captures system audio and microphone input directly on your desktop to transcribe meetings without dispatching a bot participant to the call. The application stores audio files, transcripts, and personal notes inside a local database and standard Markdown documents on your drive. Rather than forcing all conversations through remote servers, it lets users run transcription and summarization entirely on-device or connect their preferred model keys.

Why Anarlog instead of Granola

Granola established the standard for human-in-the-loop meeting notetaking by avoiding conspicuous meeting bots and pairing personal shorthand with automated audio transcription. However, Granola relies on a hosted architecture where meeting transcripts and notes reside on corporate servers, and speech recognition depends on third-party cloud infrastructure. Anarlog implements the same bot-free desktop experience while reversing the data path: every recording, raw transcript, and generated summary stays on your computer by default.

This architectural difference alters how teams manage privacy and vendor dependency. With Granola, confidential client calls, legal consultations, and internal strategy sessions must pass through external processing pipelines. Anarlog gives users strict data ownership by running local speech models and saving plain text files that work with standard backup and synchronization tools like Syncthing or iCloud. While Granola offloads computation to managed cloud clusters, Anarlog requires local machine resources to process speech offline, offering full operational autonomy in exchange for local processing overhead.

What it does well

• Records meeting audio silently from desktop sound cards and microphones, avoiding the distraction of automated bots joining client or team calls.
• Performs speech-to-text conversion on-device using local speech models, keeping sensitive discussions isolated from cloud servers.
• Stores every conversation as a plain Markdown file on your hard drive, preventing format lock-in and allowing quick text searches across historical meetings.
• Supports flexible intelligence backends, enabling users to run offline models through Ollama or supply private API keys for external providers.
• Operates reliably without internet connectivity, making it practical to review past transcripts and draft summaries while traveling or working offline.