Producers manually matched timestamps. Now, teams edit transcripts directly, and AI generates social clips without video skills.
One of the world's largest podcast networks produces shows across every genre, from true crime and narrative storytelling to interview shows and branded content.
Producers and editors were siloed in separate tools, relying on timestamped documents that required hours of manual matching in audio timelines....
“Once we had teams using Descript as an editor and using text-based workflows, we noticed those teams accelerated the amount of content they were able to push out.”
Audio media company specializing in broadcast radio, podcasting, and digital streaming.
AI video and podcast editor featuring script-based text editing.
Related implementations across industries and use cases
Manually tailoring assets took weeks. AI generated the full strategy and hundreds of audience-specific creative pieces in one day.
Standard tools sounded flat across 3,000 weekly episodes. Now, 50 AI hosts engage listeners with nuanced, programmable emotion.
Human dubbing took 5 days, slowing expansion. Editors now use AI to generate multilingual audio in 2 days, streamlining production.
Standard tools sounded flat across 3,000 weekly episodes. Now, 50 AI hosts engage listeners with nuanced, programmable emotion.
Human dubbing took 5 days, slowing expansion. Editors now use AI to generate multilingual audio in 2 days, streamlining production.
Manually illustrating vintage assets would have tripled production time. Now, a 3-person team uses AI to generate and animate the visuals.
Custom analytics required months of full-stack development. Now, self-serve AI apps connect analysts directly to data models.
Data scattered across systems forced generic content. Now, AI agents surface personalized stats and videos via chat during live matches.
Rigid search rules forced endless manual tagging sprints. Now, ML classifies products at ingestion to match natural shopper language.
Producers manually matched timestamps. Now, teams edit transcripts directly, and AI generates social clips without video skills.
One of the world's largest podcast networks produces shows across every genre, from true crime and narrative storytelling to interview shows and branded content.
Producers and editors were siloed in separate tools, relying on timestamped documents that required hours of manual matching in audio timelines....
“Once we had teams using Descript as an editor and using text-based workflows, we noticed those teams accelerated the amount of content they were able to push out.”
Audio media company specializing in broadcast radio, podcasting, and digital streaming.
AI video and podcast editor featuring script-based text editing.
Related implementations across industries and use cases
Manually tailoring assets took weeks. AI generated the full strategy and hundreds of audience-specific creative pieces in one day.
Standard tools sounded flat across 3,000 weekly episodes. Now, 50 AI hosts engage listeners with nuanced, programmable emotion.
Human dubbing took 5 days, slowing expansion. Editors now use AI to generate multilingual audio in 2 days, streamlining production.
Standard tools sounded flat across 3,000 weekly episodes. Now, 50 AI hosts engage listeners with nuanced, programmable emotion.
Human dubbing took 5 days, slowing expansion. Editors now use AI to generate multilingual audio in 2 days, streamlining production.
Manually illustrating vintage assets would have tripled production time. Now, a 3-person team uses AI to generate and animate the visuals.
Custom analytics required months of full-stack development. Now, self-serve AI apps connect analysts directly to data models.
Data scattered across systems forced generic content. Now, AI agents surface personalized stats and videos via chat during live matches.
Rigid search rules forced endless manual tagging sprints. Now, ML classifies products at ingestion to match natural shopper language.