AyeWatch – Your Personal AI Internet Monitor – To Monitor the Situation

Hacker News

Monitor topics, sources, and pages with AI. Get instant alerts only when your rules match or something new happens , less noise, more signal. Most monitoring tools are glorified Google Alerts. They dump everything on you. “Here’s 200 mentions of your keyword today. Good luck.” The internet moves too fast. By the time you check Twitter, Reddit, HackerNews, industry blogs, career pages, research papers etc…, something important already happened three hours ago. Or three days ago. For example: Every morning: check 15 tabs. Every lunch: scan social feeds. Every evening: catch up on industry news. Still missed that competitor’s funding announcement. Still found out about that viral ai announcements two days late. Still discovered that game-changing research paper after everyone else. AyeWatch monitors the entire internet for you — anything like news sites, blogs, social media, documents, research papers etc... But here’s the kicker: it only bothers you when something actually matters. Not “someone mentioned your keyword in passing.” Not “here’s the same news story from 47 different sources.” Just the real stuff. The signal. Download App Today and start using with free limited Quota to experience. AyeWatch watches everything so you can focus on what matters. No more tab sprawl. No more FOMO. No more finding out late.

Visit product View on Hacker NewsAug 30, 2025

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Launch Intel predictions

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

84%84% 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: google, new, using · Missing: mac, agents, macos

73%73% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released

59%59% 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: personal, google · Missing: mobile apps, ios, entrepreneurs

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

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

24%24% 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

15%15% 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.

Incorrect prediction on native model

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Personalized AI Internet Monitor

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