da

database of the world's brands

Hacker News

database of the world's brands

Share card

Actual performance

12points
3comments
Made the leaderboard

Launch Intel predictions

Analyze your own launch →
BetaListSuited for BetaList early-adopters · Missing: web3, chat, crypto
67%67% 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
54%54% 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
51%51% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRFits verified-revenue profile · Missing: mobile apps, ios, personal
50%50% 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
45%45% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
44%44% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
20%20% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

Correct prediction on native model

Similar products

A
A database for rollercoasters from all around the world66%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

A database for rollercoasters from all around the world

Hacker News7
Da
Database of >2M creators and brands grouped into categories32%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Database of >2M creators and brands grouped into categories

Hacker News3
Rags
Rags47%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Discover the coolest clothing brands in the world.

Indie Hackers1b2c
Th
The Evolution of Brands36%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

The Evolution of Brands

Hacker News2
PartnerUp
PartnerUp51%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

We're the matchmakers for brands

Indie Hackerscommitment-full-time
Rhizata
Rhizata67%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Database, meet world

Indie Hackerscommitment-full-time
Su
SummaDB, a hierarchical database that syncs with PouchDB60%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

SummaDB, a hierarchical database that syncs with PouchDB

Hacker News5
No
Noms – The versioned, forkable, syncable database68%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Noms – The versioned, forkable, syncable database

Hacker News43
Di
Digestable Ingredient Database68%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Digestable Ingredient Database

Hacker News2
Ne
NebulaDB, my first attempt at a database63%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

NebulaDB, my first attempt at a database

Hacker News30