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Show HN: Podverse – AI Superpowers for Podcasters

4 pointsby mdwelsh8 months ago
Hey HN, I’m excited to show off a project I have been building the last few months called Podverse — it automatically generates transcripts, summaries, and a chatbot from a podcast’s RSS feed, and makes it easy to embed AI features onto any website.<p>You can check it out at <a href="https:&#x2F;&#x2F;podverse.ai" rel="nofollow">https:&#x2F;&#x2F;podverse.ai</a>.<p>See it in action on an example podcast here: <a href="https:&#x2F;&#x2F;www.podverse.ai&#x2F;podcast&#x2F;omnibus" rel="nofollow">https:&#x2F;&#x2F;www.podverse.ai&#x2F;podcast&#x2F;omnibus</a><p>I’m a former engineer at Google and Apple, former CS prof at Harvard, and was a co-founder at Fixie.ai. I truly feel that LLMs are a revolution in our field, and I wanted to bring something to life that bridged between two deep interests of mine — AI and podcasts.<p>I’ve been listening a ton of podcasts lately, but it&#x27;s frustrating to find relevant episodes, or even content that I had listened to previously. I also know that podcasters want to take advantage of the latest AI tech to connect with and expand their audience, but they&#x27;re not usually equipped to bring all the pieces together. I wanted to build a complete, end-to-end solution for podcasters that is easy to use.<p>All you have to do is provide your RSS feed URL, and Podverse does the rest — automatically ingesting new episodes as you release them, generating transcripts and summaries, identifying speakers, and populating a custom chatbot that knows about all of the content of your podcast.<p>I built the site from scratch over the last few months (in my copious spare time!). It’s built entirely using Next.js deployed on Vercel — no backend servers beyond Vercel’s server components and API handlers. For running background tasks, like podcast ingestion and transcription, I used Inngest, which fills a big gap in the Next.js stack. Deepgram is used for ASR, which is fast, affordable, and very high quality. Supabase handles the storage, including the vector database (using pgvector). Auth is done with Clerk, which was super easy to integrate. Happy to answer any questions about the stack.<p>I’d love to get your feedback, and especially hear from podcasters to learn more about what features you’d like to see. Thanks!

1 comment

skeptrune8 months ago
Cool stuff. Did you chunk the transcripts of the podcasts and embed them for the chat or do something simpler?<p>Generally been exploring ways to add value w&#x2F; search + RAG on youtube podcasts specifically for a long time [1][2]. Using the RSS feed is an excellent idea I have not thought of which makes this more generalizable.<p>I have some overall feeling that non-podcasters like us don&#x27;t know how best to the LLMs for them. Given that, I think tools like yours which lower the technical barrier of entry are exciting. If more people get to play around with the tool then I&#x27;m hopeful we end up with more ideas that have PMF.<p>[1]<a href="https:&#x2F;&#x2F;github.com&#x2F;devflowinc&#x2F;philosophize-this">https:&#x2F;&#x2F;github.com&#x2F;devflowinc&#x2F;philosophize-this</a> [2]<a href="https:&#x2F;&#x2F;github.com&#x2F;devflowinc&#x2F;youtube-transcribe">https:&#x2F;&#x2F;github.com&#x2F;devflowinc&#x2F;youtube-transcribe</a>