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Particle launches Radar, making 130,000 podcasts searchable for AI agents

Particle, an AI newsreader startup, has launched Radar, a podcast search engine that transcribes and analyses over 130,000 podcasts, making their content accessible to AI agents.

  • Radar transcribes and analyses more than 130,000 podcasts, including the Apple Top 200 across 135 verticals.
  • The platform provides an API and MCP for AI agents and businesses to access podcast intelligence.
  • Hedge funds are reported to be high-volume customers directly integrating with Radar's API.

Particle, a startup founded by former Twitter engineers, has introduced Radar, a new podcast intelligence platform. Radar transcribes and understands the meaning of spoken conversations within podcasts, allowing it to extract key quotes and highlights.

The service indexes over 130,000 podcasts, including all Apple Top 200 podcasts across 135 verticals, with 20,000 new episodes added daily. This makes it the largest transcribed podcast service available.

Radar provides speaker labels and metadata, understanding entities like people, companies, and topics discussed. It can also track mentions of these entities and send alerts via email, Slack, or webhook.

The platform offers an API and MCP, enabling AI agents and businesses to access this intelligence programmatically. Particle co-founder and CEO Sara Beykpour stated that hedge funds have been the highest-volume customers integrating with the API.

Radar is priced at $29 per month per seat, with a business plan at $399 per month for 20 seats. Custom pricing is available for API users.

Why this matters: This development could make the content of spoken audio, which AI agents are generally unable to process directly, more accessible for analysis and data gathering.

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