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Webhooks for Any Event

Hacker News

Webhooks for Any Event

Hi, co-founder of markets.sh here. We are doing a lot of news processing and analysis around stocks and companies. One feature people like to use is “alerts” at certain price points. We have now extended this with LLM filters on the whole news feed so that you can create (near) real-time webhooks on arbitrary events like: - Notify me when Nvidia is worth 10 trillion - Notify me about AI breakthroughs - Notify me when Intel is the market leader again - Notify me about successful Starship launches - Notify me when a war breaks out - Notify me about bankrupt unicorn startups - Notify me about significant economic events The feature is still very early. If you write that you’re from Hacker News in the support chat, I’ll give personal support. Would greatly appreciate all feedback

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
78%78% 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.
Hacker NewsStrong engagement from HN community · Strong signals: hacker news, io · Missing: https docs, excited, just released
57%57% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRFits verified-revenue profile · Strong signals: personal · Missing: mobile apps, ios, entrepreneurs
52%52% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: new · Missing: mac, agents, macos
48%48% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
26%26% 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
12%12% 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
4%4% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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