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News Voyager – Explore Tech News which are relevant for you

Hacker News

News Voyager – Explore Tech News which are relevant for you

I find it challenging to stay up-to-date with the latest tech news, especially with the overwhelming amount of content out there. News feeds and social media algorithms often prioritize grabbing your attention rather than showing you what's actually relevant. So, here's my early version of News Voyager—a text-only RSS feed explorer. You can customize the topics that interest you most, and your feed will display the latest articles from those topics. I'm currently working on a feature that will let you define your own topics. Until then, let me know if there are specific news topics you're interested in or if I’ve missed any relevant news providers. Happy Shipmas to all of you!

Visit product View on Hacker NewsDec 25, 2024

Actual performance

2points

Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →

Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

56%56% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

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

53%53% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

30%30% predicted probability of success on TrustMRR, 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

26%26% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

21%21% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

16%16% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

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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