Ivy Interactive

Ivy Interactive

Indie Hackers

Build Enterprise Business Apps in Minutes. Using AI

We started Ivy because enterprises waste enormous time and money on internal tools. Low-code SaaS platforms create lock-in and technical debt, while AI code generators stop at snippets and don’t deliver real, full-stack

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Actual performance

Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →
Product HuntOn track for Day 1 leaderboard · Strong signals: apps, using, code · Missing: mac, agents, macos
77%77% 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 · Strong signals: started · Missing: supports, reddit linkedin, podcasting
64%64% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Hacker NewsStrong engagement from HN community · Missing: https docs, excited, just released
60%60% predicted probability of success on Hacker News, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Strong signals: apps · Missing: mobile apps, ios, personal
56%56% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform · Missing: plus, intuitive, reviews
34%34% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: saas, active · Missing: arr, mrr, revenue
33%33% 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
2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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