How Plailstr uses your data when you upload a song

Last updated: 2026-01-14

When you upload a track (or paste an audio URL), Plailstr uses that audio only to run the analysis you requested and generate your dashboard results (fit scoring, playlist signals, and—if enabled—draft pitches).

Important note about “where your audio exists” Plailstr’s analysis pipeline may involve two separate “copies/locations” of your audio:

1. Upload handling storage (used to receive your file upload and create a download reference), and
2. Our analysis ingest copy (used to run feature extraction/scoring). We aim to minimize retention of the analysis ingest copy and delete it after processing. Upload-handling storage may persist longer depending on the platform flow and deletion/purge schedules (and can be removed on request).

What you provide

Depending on how you submit your track, we process:

• Audio content
  • Either an uploaded .mp3 / .wav (or similar) file, or
  • A HTTPS audio URL you paste in (we’ll use it to fetch/analyze the file)
• Basic submission metadata
  • File name (or a filename derived from the URL)
  • File type / MIME type and file size (bytes)
  • A job/request identifier generated for processing
• Rights confirmation (gating)
  • We require you to confirm you have the rights to submit the audio for analysis before processing begins.
• Account linkage
  • Your Plailstr user/account ID (so we can associate results with you, apply plan features, and enforce quotas)

What happens behind the scenes

1. Upload / source resolution
   • If you upload a file, the app first uses upload-handling storage to receive the file and generate a reference we can fetch.
   • If you paste a URL, we treat that URL as the audio source for analysis.
2. Analysis ingest
   • We send your audio (or the audio URL) to our analysis service to run feature extraction.
   • The system assigns and stores references like a job ID and a track fingerprint/hash so the results can be retrieved and shown in your dashboard.
3. Feature extraction + scoring
   • We compute derived musical features (e.g., tempo/energy-related values, embeddings/summaries used for scoring).
   • We compute fit/insight outputs (fit scores, rationales, and related playlist targeting signals).
   • We may look up playlist metadata (for example, playlist IDs/links and other non-login playlist info) to support discovery/scoring.

What we generate (derived data)

From your audio, we generate and may retain:

• A track fingerprint / hash (a non-reversible identifier used to reference your analysis)