Radar Makes Podcasts Searchable for AI Agents

Podcasts contain a huge amount of useful information, but most of it is still trapped inside audio.

What happened

Particle launched Radar, a podcast search engine that transcribes and understands spoken conversations so quotes and highlights can be retrieved through an API.

The product is designed to make podcast content searchable and usable by AI agents, with early demand coming from customers that need to analyse large volumes of spoken information.

Why it matters

This is a media-data infrastructure signal. AI agents need structured access to information, but much of the internet’s knowledge is not neatly written in articles or databases.

Podcasts are especially difficult because they are long, conversational and full of context. Turning them into searchable data creates a new layer for research, monitoring, media analysis and financial intelligence.

The bigger picture

As AI agents become more common, the value of content may shift from page views to machine-readable access.

Radar points to that shift. Media archives, audio libraries and expert conversations could become data infrastructure for agents, not just content for human listeners.