Playlist Rider
Price history
- On sale
- 79 of the last 90 days
- Lowest in 90 days
- $79.99
- Highest in 90 days
- $149.00
About this plugin
Playlist Rider addresses a genuine pain point in live and broadcast audio: maintaining consistent output levels across multiple input sources with disparate characteristics. Rather than functioning as a traditional compressor, it operates as a dynamic level controller that rides gain in real time, automatically adjusting to keep your master bus output within specified LKFS targets.
The plugin offers three preset loudness standards (-24, -18, and -14 LKFS), covering everything from streaming podcasts to broadcast television. What distinguishes Playlist Rider from standard limiting is its approach to dynamics control. A variable threshold mechanism preserves the natural dynamics of source material, preventing the over-compressed sound that results from aggressive limiting. The detector circuit can intelligently ignore low-level content such as fade-outs and silence, preventing unnecessary gain riding in these regions. Attack time selection ( - fast or slow) lets you choose how aggressively the plugin responds to level changes, affecting whether transitions sound transparent or more controlled.
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The optional tone shaping feature adds practical utility for live scenarios where source material varies significantly in spectral balance. Rather than solving tonal inconsistency through EQ (which requires individual attention per input), Playlist Rider can smooth broad tonal differences across feeds in a single processor.
This tool sits comfortably in broadcast workflows, live podcast production, and theater reinforcement applications where multiple speakers or audio sources demand consistent loudness without constant manual intervention. Among similar tools, it occupies a practical middle ground between transparent gain automation and transparent loudness control, making it particularly valuable for time-constrained live operations where neither perfection nor complete hands-off operation is realistic.