Particle launches Radar podcast search for AI agents
Startup Particle, founded by former Twitter engineers, has unveiled Radar, a search platform for podcasts. The service transcribes audio, analyzes conversation content, and makes it possible to find quotes, key excerpts, and mentions of people, companies, brands, products, and topics. TechCrunch reports on the launch.
An index of more than 130,000 podcasts
According to the company, Radar transcribes more than 130,000 podcasts, including all shows in the Apple Top 200 across 135 categories. Twenty thousand episodes are added to the index every day. The transcripts include speaker labels and metadata, making it possible to identify the entities and topics being discussed.
Users can monitor mentions in podcasts and configure alerts by email, Slack, or webhook. These can be filtered, for example, by the appearance of a specific guest and discussion of a certain topic, as well as limiting searches to the most popular podcasts.
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Access via API and MCP
Radar also isolates self-contained audio clips with timestamps that can be listened to or read. The platform tracks topics, mentions and when they appear, listener ratings and reviews, advertising in episodes, and other data. A separate search for podcast advertising makes it possible to find episodes in which a particular company is advertised and track the dynamics of such mentions.
Radar's main product is its API and MCP, through which AI agents and companies can access this data programmatically. Particle co-founder and CEO Sara Beykpour told TechCrunch that hedge funds account for the largest volume of API integrations. Radar's partners include Exa, a provider of a search API for AI agents.
A Radar subscription costs $29 per month per seat. The business plan for 20 seats costs $399 per month, while pricing for API users is determined individually. In the future, Particle plans to add support for other audio formats, including YouTube video and news clips.
