Actual performance
Did not reach leaderboard
Launch Intel predictions
Analyze your own launch →
AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive59%59% predicted probability of success on AppSumo, 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: visual · Missing: mac, agents, macos53%53% predicted probability of success on Product Hunt, 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 released50%50% predicted probability of success on Hacker News, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto36%36% predicted probability of success on BetaList, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal32%32% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting27%27% predicted probability of success on Indie Hackers, 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, revenue15%15% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
Correct prediction on native model
Similar products
Imaginate27%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Explore visual interpretations of ideas before design
Indie Hackerscommitment-side-projectWh
What If_? – See ideas in a new perspective and explore them52%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
What If_? – See ideas in a new perspective and explore them
Hacker News2ImagineMyHouse47%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Upload a photo and explore AI home design ideas for your
Indie HackersEx
ExBERT – A Visual Tool to Explore Representations in Transformer Models51%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
ExBERT – A Visual Tool to Explore Representations in Transformer Models
Hacker News9Ex
Explore EBNF Grammars Interactively59%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Explore EBNF Grammars Interactively
Hacker News6Ex
ExploreTrees.SG – Explore trees in Singapore60%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
ExploreTrees.SG – Explore trees in Singapore
Hacker News1Ex
Explore Julia Sets33%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Explore Julia Sets
Hacker News10Ex
Explore Our Moon55%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Explore Our Moon
Hacker News5Ex
Explore every Winter Olympic medal since 1924 with D349%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Explore every Winter Olympic medal since 1924 with D3
Hacker News1leather flogger36%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Explore Leather Whip for whip cracking. Floggers,
Indie Hackersvertical-e-commerce