Podcasts are full of useful information, but most of that knowledge is trapped in long audio files that are hard for people and agents to search. Radar is interesting because it treats podcasts as a structured knowledge source rather than entertainment metadata.
This points to a broader product shift: AI agents need clean, permissioned, searchable inputs before they can be useful. The companies that organize messy media, documents, calls, and internal knowledge may become the data layer for everyday agents.
The practical question is quality. Searchable transcripts are only valuable if attribution, freshness, speaker identity, and context survive the conversion from audio to agent-readable data.
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