

27 Aug 2026 · 6m · 1 chapter

Particle’s Radar turns podcast audio into searchable, AI-readable intelligence by transcribing and understanding meaning, extracting quotes/highlights, tracking entity mentions, and serving clips via an API for AI agents.
Sarah Beckpour, co-founder and CEO of Particle; previously a Twitter engineer. Particle previously built an AI newsreader before pivoting to podcast intelligence.
Radar indexes 130,000+ podcasts (Apple Top 200 across 135 verticals; 20,000 new episodes daily). It adds speaker labels, rich metadata, entity tracking with alerts (email/Slack/webhook), and customizable filters (e.g., specific guests/topics). Agents are “blind” to audio unless transcribed.
Pre-chosen notable clips with timestamps; dedicated podcast ads search engine to find episodes where a company advertises and track trends.
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Discussion on Particle's Radar, a podcast search engine that transcribes and indexes audio content.
“She said, its API to source interesting podcast clips that it then included alongside related news stories in the app's feed.”

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0:01This is TechCrunch.
0:09Sierra has all the best active and outdoor brands you need From athletic stuff, like a full-court pickup game Swish! To athletic-ish stuff, like a half-mile stroll Get those steps in! And for morning hikes up the mountain trail Good pace! To nighttime ghost stories from the camping chair What a twist! Whatever level of active, Sierra loves it all Head to Sierra or Sierra.com for the brands you want at the prices that let you do it all. From athletic to athletic-ish, Sierra's got it. The AI newsreader startup called Particle, founded by former Twitter engineers, is shifting its focus to a potentially more lucrative idea, indexing the spoken conversations buried in podcasts and making them discoverable.
0:57On Wednesday, the company introduced Radar, a podcast search engine that not only transcribes podcast audio, but also understands what it means, enabling it to pull out key quotes and highlights. The solution has business potential, as it's already attracted interest from hedge funds looking for data that their agents can't see, explains Particle co-founder and CEO Sarah Beckpour. She said,
1:53its API to source interesting podcast clips that it then included alongside related news stories in the app's feed. Particle's team not only realized the product's value, but also that it was somewhat trapped in the newsreader. As the movement around AI agents began to gain steam, the company decided to pivot and focus on building an API for its podcast intelligence report. Bekpour said, our vision is really to have all new media intelligence and all audio intelligence in that API. One of the reasons why it's an interesting space is that most API agents and services crawl the web and they're focused on text.
2:31We are providing that layer with audio. Agents are generally blind to audio. They can't see it unless something or someone has transcribed it. With Radar, the company transcribes more than 130 ,000 podcasts, making it the largest transcribed podcast service in existence. This includes all the Apple Top 200 podcasts across its 135 verticals and 20 ,000 episodes added to Radar's Index Daily. The podcast transcriptions include speaker labels and rich metadata as Radar understands the entities, people, companies, brands, products, and topics being discussed. Now, it's also able to track mentions of these entities across podcasts and send alerts whenever they come up, either when the mention occurs or as a daily or weekly digest.
3:22The alerts, which can be delivered via email, Slack, or Webhook, can be customized with filters. These let users configure Radar to only send alerts when certain guests appear and discuss a particular topic, for instance. The search can also be narrowed in other ways, such as limiting it to top podcasts only. Radar can extract relevant self-contained clips with timestamps, allowing users to both listen to and read the comments made. Beckpore noted, we've pre-chosen notable clips, so if you can't listen to the whole podcast and you don't want to read a summary, this is the best way to just get an idea of what's happening in that podcast.
4:03Radar can also track the topics mentioned in the podcast, who or what was mentioned and when, listener ratings and reviews, the episode's ads, and more. There's even a dedicated podcast ads search engine that can find every episode where a given company advertises and track how it trends over time. This feature has additional monetization potential alongside other tools offering political bias analysis, chart rankings data, audience size estimates, sponsorship data, and brand suitability. While all of this is available through Radar's web interface, its real product is the API and MCP, which allows AI agents and other businesses to tap into this same intelligence programmatically.
4:51Radar is priced at$29 a month per seat, with a$399 per month plan for businesses that includes 20 seats. API users have custom pricing based on their needs. In the future, Radar plans to expand the service beyond podcasts to support other forms of audio, such as YouTube videos and news clips. That's all for now. For the latest in startup tech news, go to TechCrunch.com.
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On Wednesday, the company introduced Radar, a podcast search engine that not only transcribes podcast audio but also understands what it means, enabling it to pull out key quotes and highlights.
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