Commentify

Commentify

Indie Hackers

AI LinkedIn Automatic Commenting Agent

Your AI LinkedIn Comments Agent that automatically engages with 100+ targeted posts daily—better than you ever could.

Share card

Actual performance

Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →
Product HuntOn track for Day 1 leaderboard · Strong signals: agent · Missing: mac, agents, macos
83%83% 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.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
47%47% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
45%45% predicted probability of success on BetaList, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
43%43% 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
38%38% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Missing: https docs, excited, just released
30%30% predicted probability of success on Hacker News, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting
21%21% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.

Correct prediction on native model

Similar products

Au
Automatic Parallelization for Haskell74%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Automatic Parallelization for Haskell

Hacker News1
Au
Automatic CloudWatch Alarms52%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Automatic CloudWatch Alarms

Hacker News1
AP
APReF: An Automatic Parallelizer of Recursive Functions for Haskell67%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

APReF: An Automatic Parallelizer of Recursive Functions for Haskell

Hacker News2
Au
Automatic Installer for ArchLinux ARM51%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Automatic Installer for ArchLinux ARM

Hacker News1
AI
AIlight: Automatic Highlighting52%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

AIlight: Automatic Highlighting

Hacker News1
Ga
Galene-stt: automatic captioning for the Galene videconferencing system58%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Galene-stt: automatic captioning for the Galene videconferencing system

Hacker News2
Sm
Smig – Automatic SurrealDB Migrations36%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Smig – Automatic SurrealDB Migrations

Hacker News1
Au
Automatic initializer methods for Objective-C39%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Automatic initializer methods for Objective-C

Hacker News3
Au
Automatic feedback on your LinkedIn profile31%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Automatic feedback on your LinkedIn profile

Hacker News2
AI
AI LinkedIn Banners21%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

AI LinkedIn Banners

Hacker News3