Th

The Pond – Find Relevant Cofounders and Startups

Hacker News

The Pond – Find Relevant Cofounders and Startups

Share card

Actual performance

13points
4comments
Made the leaderboard

Launch Intel predictions

Analyze your own launch →
BetaListSuited for BetaList early-adopters · Missing: web3, chat, crypto
73%73% 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.
Product HuntOn track for Day 1 leaderboard · Missing: mac, agents, macos
60%60% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Missing: https docs, excited, just released
57%57% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
34%34% 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, personal
31%31% 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, podcasting
23%23% 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, revenue
15%15% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

Correct prediction on native model

Similar products

Fi
Find YC startups relevant to you71%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Find YC startups relevant to you

Hacker News4
Fi
Find relevant/irrelevant files from SHA1 sums50%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Find relevant/irrelevant files from SHA1 sums

Hacker News2
#1
#10SecondPitch (Techcrunch Disrupt startups)53%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

#10SecondPitch (Techcrunch Disrupt startups)

Hacker News1
Dr
Drunk Startups53%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Drunk Startups

Hacker News1
Qu
Questmate for Startups53%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Questmate for Startups

Hacker News1
Ex
ExpertsVault - A Thinktank For Startups53%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

ExpertsVault - A Thinktank For Startups

Hacker News2
A
A Graveyard of Startups57%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

A Graveyard of Startups

Hacker News2
Proton
Proton26%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

MVPs for Startups.

Indie Hackerscommitment-full-time
StarterCircle
StarterCircle60%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Where startups begin.

Indie Hackers1communication
Startups.fyi
Startups.fyi33%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Startups

Indie Hackers