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SpyDelta – Real-Time Competitive Intelligence, Straight to Your Inbox

Hacker News

SpyDelta – Real-Time Competitive Intelligence, Straight to Your Inbox

I built SpyDelta because I needed a better way to track competitors’ website changes (for my "day job"). The existing tools that I tried were outdated and I figured I could make a better one using todays tech (LLMs/LVMs). SpyDelta continuously monitors competitor websites and delivers only key insights straight to your inbox. No dashboards, no fluff—just actionable updates on pricing changes, new products, job postings, and more. Features: - AI-powered – Filters out noise, surfaces only relevant competitor insights - Crawls around the website to monitor multiple pages - <1 min setup – Just enter the url + your email and you're done Would love your feedback, especially with prompt ideas to improve the final "insights" output!:)

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Actual performance

2points
Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →
Product HuntOn track for Day 1 leaderboard · Strong signals: new, inbox, email · Missing: mac, agents, macos
89%89% 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
69%69% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
45%45% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: way · 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: exist, existing, ide · Missing: https docs, excited, just released
28%28% 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
14%14% 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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