
Particle’s new podcast intelligence platform transcribes and analyzes more than 130,000 podcasts, making their conversations searchable on the web and accessible to AI agents through an API and MCP.
Radar is a podcast search engine that transcribes audio from over 130,000 podcasts and makes the content searchable and understandable to AI agents. The service extracts key quotes, tracks mentions of people and companies, and sends customizable alerts when specified topics or guests are discussed. This matters because most AI agents can only search text on the web and cannot access audio content, so Radar fills that gap by providing an API that allows hedge funds, researchers, and AI search platforms to access podcast intelligence programmatically. The product emerged from a feature in Particle's news reader app that had shown the value of indexing podcast clips, and the company decided to pivot toward building an API as interest in AI agents grew.

While restaurant owners might look to generative AI as a shortcut to sprucing up their menu, customers can viscerally sense that something is wrong with the food.
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ChatGPT, Claude, and Grok all suffered outages at nearly the exact same time for reasons that remain murky.

Most teams building a shopping assistant or agent rebuild the same scaffolding: an agent loop, a tool layer over the catalog, an approval gate, and an eval suite. Anthropic has now released that scaffolding as code. This week, they published anthropics/commerce-agents, a reference blueprint containing a shopping agent and a merchant agent, along with four runnable verticals: retail, travel, telecom and entertainment. It ships alongside two write-ups: a product announcement and an engineering de
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