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Podlog review

Free#22 of 25 in Podcast Transcription Software

A technical, self-hosted archive for searchable podcast transcripts and speaker analysis.

7.1/10Editor score
Podlog7.1 Visit Podlog

Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026

Podlog is an open-source, self-hosted web application for transcribing podcast episodes and uploaded audio. It imports episodes from RSS feeds, processes speech with WhisperX, labels speakers locally with pyannote, and stores transcripts in a searchable library. Its audience is technical users who want control over a podcast archive, local processing options, and tools for exploring a growing collection rather than a hosted transcription workspace.

Its strongest area is the depth of transcript discovery and analysis. Keyword and semantic search work across the transcript library, while timestamp-linked playback connects text to the relevant audio. The Ask AI interface can answer questions over the library, and speaker analytics provide talking-time comparisons. Podlog also supports Markdown and plain-text transcript export, which suits documentation and text workflows. Local inference through Ollama supports a self-hosted approach, while Fireworks AI provides an optional remote inference path.

The workflow is broader than transcription alone. RSS feed ingestion and direct audio uploads feed a monitored queue with retry handling, and optional Telegram and email notifications can report activity. These capabilities make Podlog a fit for maintaining an ongoing archive with recurring processing needs. Its tradeoff is focus: transcript editing and caption-format export are not part of the product’s published feature set, so teams centered on polished subtitle production should choose a tool built around those workflows instead. Choose Podlog for searchable, speaker-aware archival analysis and self-hosting; look elsewhere if you need an editor-led caption pipeline.

Podlog pros and cons

  • Where it wins
    • WhisperX transcription with local pyannote speaker diarization
    • Keyword, semantic, and AI-powered search across transcript libraries
    • RSS ingestion, timestamped playback, analytics, and notifications
  • Where it doesn't
    • Requires Docker Compose and technical self-hosting involvement
    • Transcript export is limited to Markdown and plain text
    • Editing and caption-format export are not included

Podlog fact sheet, pricing and score →

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