Particle launched Radar, a podcast intelligence platform that transcribes and indexes over 130,000 podcasts, making their content searchable and accessible to AI agents via API and Model Context Protocol (MCP).
Radar transforms podcast discovery by enabling full-text search across a massive catalog of audio content. The platform transcribes conversations and surfaces specific moments, clips, and topics that would otherwise remain buried in hours of audio.
The service also exposes podcast data through an API and MCP integration, allowing AI agents to autonomously search and analyze podcast content. This opens use cases ranging from research tools to AI-powered podcast discovery applications.
Particle's approach addresses a fundamental limitation of podcasting: discoverability. While written content has been indexed and searchable for years, audio remains largely opaque to traditional search and AI systems. Radar bridges that gap by converting spoken word into queryable, machine-readable data.
The platform handles the technical heavy lifting—transcription, indexing, and API management—so developers can build podcast-powered applications without managing infrastructure. Availability and pricing details were not immediately disclosed.
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