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FomoRobo – AI that reads your newsletters so you don't have to

Hacker News

FomoRobo – AI that reads your newsletters so you don't have to

I subscribe to dozens of newsletters and didn’t want to miss key insights, so I built an AI that reads them all and lets me ask questions about the content. I originally built it for myself, but decided to open it up in case others find it useful. Forward your newsletters to FomoRobo, and the AI will summarize the important points. Ask it questions like "What are the key facts from my newsletters today?" or "Write a blog post based on today's newsletters." The tricky part was making email parsing reliable and keeping conversation context across newsletters. It’s already processing 100+ newsletters a day. Would love feedback, especially on the UX and on what other newsletter-related pain points you would want solved. https://www.fomorobo.com Thanks!

Visit productView on Hacker NewsSep 30, 2025
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Actual performance

2points
Did not reach leaderboard

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: new, email, context · Missing: mac, agents, macos
85%85% 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
74%74% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive
55%55% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
39%39% 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
38%38% 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 · Missing: arr, mrr, revenue
23%23% 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
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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