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Podsi – AI Podcast Search Tool, Generates What U Can’t Find - Any Topic

Hacker News

Podsi – AI Podcast Search Tool, Generates What U Can’t Find - Any Topic

I want to give up. Almost every time I search for a podcast on something specific, it’s like an endless scroll through stuff I don’t care about. Finding the latest episode on a niche topic feels nearly impossible, and I just end up frustrated. I spend more time searching than actually listening to podcasts—and the episodes are already long enough! That’s why I built Podsi, a natural language search engine just for podcasts, to help solve this problem. What makes Podsi different? An AI-powered search engine that delivers deep, accurate results across multiple platforms—Podsi, Spotify, Apple Podcasts, and more—so you get global results in one place. The game-changing feature: If there’s no recent or newly published podcast on the topic you’re searching for, Podsi will search the web and create a dynamic podcast for you using AI, generating fresh, on-demand content tailored to your query. Top Features: AI-Powered Search: Understands your queries in context, providing precise results. Global Search results: Unified results across Podsi, Spotify, Apple Podcasts, and other platforms on the way. Dynamic Podcasts: If no recent podcast exists on your topic, Podsi will search the web and generate a new podcast just for you. Collections: Organize and curate your favorite episodes into personalized collections. Transcriptions with Playable Highlights: Follow along with accurate transcriptions, with playable highlights to jump to key moments. What’s coming soon: Better, Interactive Dynamic Podcasts: Inspired by Google's NotebookLM, these will offer podcast-like discussions between AI hosts, summarizing your topics in an engaging, conversational format. AudioDrops: Get real-time alerts, summaries, or updates on new podcast episodes directly to your device. Newsletters: Stay updated with personalized podcast recommendations and summaries delivered to your inbox. Dubbing: Listen to podcasts in 29 languages with AI voiceovers. Podcast Snapshots: Get short-form highlights of episodes when you're pressed for time. Extended User Profiles: Personalized recommendations and curated collections. IntelliScout: AI-driven recommendations tailored to your usage and preferences. Conversations with Podcast Episodes: Chat with podcasts—ask questions or interact with the content, and the AI engine will provide answers based on the episode or related topics. Expanded Transcriptions: Searchable, multilingual transcriptions for all episodes. For more details, check out our roadmap and upcoming features at Podsi Roadmap. https://about.podsi.xyz We’re still early, but you can try the prototype now at Podsi. https://www.podsi.xyz/ We’d love your feedback and ideas to help us keep building!

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Actual performance

2points
4comments
Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →
Product HuntOn track for Day 1 leaderboard · Strong signals: apple, google, user · Missing: mac, agents, macos
96%96% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
81%81% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: personal, google, answers · Missing: mobile apps, ios, entrepreneurs
46%46% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform, host, soon · Missing: plus, intuitive, reviews
46%46% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: exist, ide, io · Missing: https docs, excited, just released
24%24% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Acquire.comPre-revenue stage for this audience · Strong signals: active · Missing: arr, mrr, revenue
10%10% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: chat, audio · Missing: web3, crypto, cryptocurrency
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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