Particle's radar transforms podcasts into ai-accessible data

Particle, an AI newsreader startup co-founded by former Twitter engineers, has unveiled Radar, a podcast search engine that transcribes and interprets audio content, making it accessible for AI agents. The platform enables users to extract key quotes, highlights, and metadata from over 130,000 podcasts, positioning it as the largest transcribed podcast service. Radar includes all Apple Top 200 podcasts across 135 verticals, with 20,000 episodes added daily. The service provides speaker labels, entity recognition, and tracking of mentions across podcasts, with customizable alerts via email, Slack, or webhook. Radar's co-founder and CEO, Sara Beykpour, highlighted that hedge funds are among the highest-volume customers integrating with Radar's API, alongside AI search platforms and data resellers. The company also partners with Exa, a search API provider for AI agents. Radar's API and MCP allow businesses to access this intelligence programmatically, with pricing at $29 per seat monthly and $399 for businesses with 20 seats. The platform plans to expand beyond podcasts to support other audio formats like YouTube videos and news clips. Radar's features include a dedicated podcast ads search engine, political bias analysis, chart rankings, audience size estimates, sponsorship data, and brand suitability tools.