Particle<\/a>, the AI newsreader startup<\/a> founded by former Twitter engineers, is shifting its focus to a potentially more lucrative idea: indexing the spoken conversations buried\u00a0in podcasts and making them discoverable. On Wednesday, the company introduced Radar<\/a>, 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. <\/p>\n The solution has business potential, as it\u2019s already attracted interest from hedge funds looking for data that their agents can\u2019t see, explains Particle co-founder and CEO Sara Beykpour.<\/p>\n \u201cHedge funds have been the highest-volume customers that are directly integrating with the API,\u201d Beykpour told TechCrunch. While journalists and researchers could also make use of the tools, other top-paying customers have included AI search platforms and data resellers. (The search API provider for AI agents, Exa<\/a>, for instance, is among Radar\u2019s partners.)<\/p>\n The idea itself stemmed from one of the Particle news-reading app\u2019s most beloved features. The app had used an API<\/a> to source interesting podcast clips<\/a> that it then included alongside related news stories in the app\u2019s feed.<\/p>\n Particle\u2019s team realized the product\u2019s value, but also that it was somewhat trapped in the news reader. 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 product.<\/p>\n \u201cOur vision is really to have all new media intelligence and all audio intelligence in that API. One of the reasons why it\u2019s an interesting space is that most API agents and services crawl the web and they\u2019re focused on text. We are providing that layer with audio,\u201d Beykpour said. \u201cAgents are generally blind to audio; they can\u2019t see it unless something or someone has transcribed it.\u201d <\/p>\n 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, with 20,000 episodes added to Radar\u2019s index daily.<\/p>\n The podcast transcriptions include speaker labels and rich metadata, as Radar understands the entities \u2014 people, companies, brands, products, and topics \u2014 being discussed. <\/p>\n It\u2019s 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. <\/p>\n The 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.<\/p>\n Radar can extract relevant self-contained clips, with timestamps, allowing users to both listen to and read the comments made.<\/p>\n \u201cWe\u2019ve pre-chosen notable clips, so if you can\u2019t listen to the whole podcast and you don\u2019t want to read a summary, this is the best way to just get an idea of what\u2019s happening in that podcast,\u201d Beykpour noted.<\/p>\n Radar can also track the topics mentioned in the podcast, who or what was mentioned and when, listener ratings and reviews, the episode\u2019s ads, and more. There\u2019s 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.<\/p>\n While all of this is available through Radar\u2019s web interface, its real product is the API and MCP<\/a>, which allows AI agents and other businesses to tap into this same intelligence programmatically.<\/p>\n Radar 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.<\/p>\n In the future, Radar plans to expand the service beyond podcasts to support other forms of audio, such as YouTube videos and news clips.<\/p>\n<\/div>\n When you purchase through links in our articles, we may earn a small commission<\/a>. This doesn\u2019t affect our editorial independence.<\/em><\/p>\n![\"\"](\"https:\/\/techcrunch.com\/wp-content\/uploads\/2026\/08\/Radar4.jpg?w=680\")
![\"\"](\"https:\/\/techcrunch.com\/wp-content\/uploads\/2026\/08\/Radar3.jpg?w=680\")
![\"\"](\"https:\/\/techcrunch.com\/wp-content\/uploads\/2026\/08\/Radar2.jpg?w=680\")
![\"\"](\"https:\/\/techcrunch.com\/wp-content\/uploads\/2026\/08\/Radar1.jpg?w=680\")