Describe what you actually retain
Podcast datasets can range from a finished episode to separate participant recordings with aligned text. These are materially different inputs for a speech pipeline. This Fiund sourcing site focuses on the formats, conversational coverage, and participant considerations that matter when evaluating podcast audio for AI. If you hold relevant material, explain its origin, approximate size, date coverage, and original file types. Distinguish an estimate from a reconciled inventory.
Explain the source characteristics
Recording level: Published episode, original session, mixed master, or independent participant tracks.; Dialogue coverage: Speaker count, recurring hosts, guest diversity, topics, languages, and recording conditions.; Editorial exclusions: Advertising, music, licensed inserts, intros, synthetic voices, and excluded contributors.; Speaker and source review: Permission scope, contributor documentation, attribution requirements, and any onward-use restrictions. List missing information instead of inferring details that have not been checked.
Identify the permission questions
Describe who produced the material, which other contributors or components may be involved, and what uses have previously been agreed. Possession of files alone does not resolve permission or confidentiality questions. Sensitive records and agreements should be handled through an appropriate review process.
Begin with an email, before a transfer
Send a high-level description to jaeden@fiund.com. Do not attach an archive or sensitive participant material to the first message. Any later access, review, preparation, and commercial scope must be agreed for the specific project; an inquiry does not promise a buyer, acceptance, or earnings.
Include in your inquiry
- Languages, topics, and conversation styles
- Hours and preferred speaker diversity
- Mixed audio or independent tracks
- Transcript, diarization, and edit exclusions
- Training use and participant-permission requirements