Particle, an AI startup founded by ex-Twitter engineers, has introduced Radar, a podcast search engine that transcribes and analyzes spoken content from more than 130,000 podcasts. The tool aims to unlock buried conversations for AI agents and businesses by offering a rich API with detailed metadata and customizable alerts.
- Radar transcribes 130,000+ podcasts daily adding 20,000 episodes
- API used by hedge funds, AI platforms, and data resellers
- Includes podcast ads search and entity tracking with alerts
What happened
Particle, a startup headed by former Twitter engineers, has launched Radar, a cutting-edge podcast search engine designed to reveal the conversations and insights hidden within podcast audio. By transcribing and understanding podcast content from over 130,000 shows, Radar makes the audio discoverable and accessible in a searchable web interface and through a powerful API.
The system enriches transcriptions with metadata such as speaker identification, entity recognition for people and brands, and allows real-time alerts based on customized filters. Radar’s database includes the complete Apple Top 200 podcasts across more than 130 verticals, with new episodes continually added, positioning it as the largest transcribed podcast index available.
Why it matters
Most AI agents and search tools today focus on crawling and analyzing text-based content, leaving audio sources like podcasts invisible to them. Radar fills this gap by unlocking podcast audio through transcription and semantic analysis, enabling AI agents to access insights previously hidden in spoken form. This innovation offers significant value to high-volume data consumers such as hedge funds, which directly integrate with the Radar API for investment and research intelligence.
Beyond finance, Radar’s customizable alerts, clip extraction, and ad analytics support a wide range of use cases including journalism, AI search platforms, political analysis, and brand monitoring. The addition of podcast advertising search provides new monetization opportunities and granular insight into sponsorship trends and messaging across the podcast ecosystem.
What to watch next
Radar’s current focus is on podcasts, but Particle plans to extend its indexing and AI-readability technology to other audio-based formats including YouTube videos and news clips, broadening the scope and utility of their platform. The evolution of Radar’s API and alerting features will likely attract more sectors looking to incorporate audio intelligence into their workflows.
Pricing ranges from $29 per month for individual seats to customized plans for businesses and API users, indicating a scalable model for different customer segments. Observers should watch for how Radar integrates with emerging AI agents and platforms, potentially becoming a backbone for audio content discovery and analysis in the AI economy.