Le
LeapHubAI – drop-in AI tools for every SaaS
Hacker NewsLeapHubAI – drop-in AI tools for every SaaS
I'm building leaphub.ai, a set of tools that can be included in any web platform to improve it with common AI-powered features, such as text assistants, API-connected chatbots, etc. The idea is that these are copy&paste integrations. Also, *looking for Design Partners at this point*! Link: leaphub.ai Demo in the Playground (need to register)
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Product HuntOn track for Day 1 leaderboard · Missing: mac, agents, macos62%62% 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 HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting35%35% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform · Missing: plus, intuitive, reviews32%32% 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, personal31%31% 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 released30%30% 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 · Strong signals: saas · Missing: arr, mrr, revenue24%24% 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, cryptocurrency10%10% predicted probability of success on BetaList, based on ML models trained on real launch data.
Correct prediction on native model
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