I built web app that let you Chat with YouTube videos

Hacker News

Hi HN! I built Vidiopintar - an AI-powered tool that transforms how we consume YouTube content through interactive conversations. What it does: - Generate concise, meaningful summaries to save your time - Provide suggested questions to trigger "aha moments" - Give straightforward answers without corporate speak - Extract key concepts automatically - Work with any YouTube video Demo: https://vidiopintar.com Source: https://github.com/ahmadrosid/vidiopintar.com --- I also looking for a job if you have any opening position in your company please reach me out alahmadrosid [at] gmail.com or my twitter account https://x.com/_ahmadrosid Thank you!

Visit product View on Hacker NewsJun 26, 2025

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Did not reach leaderboard

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Product HuntOn track for Day 1 leaderboard · Strong signals: open · Missing: mac, agents, macos

64%64% 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.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

50%50% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

46%46% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released

40%40% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRLess likely to generate early MRR · Strong signals: video, answers · Missing: mobile apps, ios, personal

40%40% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: active · Missing: arr, mrr, revenue

14%14% 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 · Missing: web3, crypto, cryptocurrency

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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