Particle launches Radar, making over 130,000 podcasts searchable and AI-ready
Radar transcribes and analyzes podcast conversations, making the data searchable on the web and accessible to AI Agents
Particle, a company founded by former Twitter engineers, has launched Radar, a Podcast Intelligence platform that transcribes and analyzes content from more than 130,000 podcasts. It makes conversations that previously had to be heard episode by episode accessible beyond their original audio files.
Users can search the web for quotes, topics, people, brands, and products mentioned across shows. Radar can also set Alerts when podcasts discuss topics of interest, identify ad segments, and retrieve audio clips with Timestamps so users can verify the original source.
Another key feature gives AI Agents access to the database through an API and MCP, or Model Context Protocol. For example, an AI could find what a person has said about a particular topic on podcasts or compile product mentions from multiple shows for analysis.
This approach makes audio content searchable and processable much like web articles. However, transcript results should still be checked against the original clips and Timestamps, especially when quoting someone or covering sensitive issues.
The Radar covered here is a Particle product and is unrelated to RADAR Podcasters, Spotify's program supporting podcast creators.
Radar could help Thai journalists, researchers, and businesses search large volumes of podcast content faster and use audio data in AI systems without building their own end-to-end transcription and indexing pipelines.