Cr
Create embeddings from JSON collections
Hacker NewsCreate embeddings from JSON collections
Share cardActual performance
2points
Did not reach leaderboard
Launch Intel predictions
Analyze your own launch →
BetaListSuited for BetaList early-adopters · Missing: web3, chat, crypto81%81% predicted probability of success on BetaList, 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: io · Missing: https docs, excited, just released54%54% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal42%42% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos30%30% 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, intuitive25%25% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting22%22% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue18%18% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
Incorrect prediction on native model
Similar products
Th
The Groundwork Collections42%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
The Groundwork Collections
Hacker News3li
libcodr7 – fundamental collections in the spirit of C42%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
libcodr7 – fundamental collections in the spirit of C
Hacker News67Pr
Probed Collections42%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Probed Collections
Hacker News2Of
Off-heap collections with speed comparable to Java Collections32%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Off-heap collections with speed comparable to Java Collections
Hacker News4Su
Supercharge your JSON using collections in PHP38%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Supercharge your JSON using collections in PHP
Hacker News1JS
JSON.stringify (without circular deps) for AngularJS 1.x41%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
JSON.stringify (without circular deps) for AngularJS 1.x
Hacker News3JS
JSON.is47%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
JSON.is
Hacker News100Pa
Parse JSON with Flex, Bison, and Ruby38%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Parse JSON with Flex, Bison, and Ruby
Hacker News3Ho
Homogenius – JSON packer/unpacker47%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Homogenius – JSON packer/unpacker
Hacker News1js
json.is47%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
json.is
Hacker News10