Clammer – share and discuss article excerpts with friends

Hacker News

Clammer is a social platform for sharing and discussing excerpts from online written content. It's like Twitter but every post and thread stems from the facts, quotes, and insights you collect online, all tied back to the source. In fact, you can have a whole conversation without ever writing a single word. I made this because I was tired of rehashing vague opinions, the real juicy conversations are in the details. Would love to know if this resonates with anyone; any and all feedback is hugely appreciated. Demo: https://www.youtube.com/watch?v=ZU-4uMcNiGk

Visit product View on Hacker NewsSep 26, 2022

Share card

Actual performance

4points

2comments

Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →

AppSumoStrong fit for a featured deal · Strong signals: platform · Missing: plus, intuitive, reviews

63%63% 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 HuntUnlikely to reach the leaderboard · Strong signals: single · Missing: mac, agents, macos

44%44% 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: io · Missing: https docs, excited, just released

43%43% 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, personal

28%28% 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

18%18% 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

13%13% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

4%4% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

Similar products

TMinus is where you share what you're counting down to with your friends41%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

TMinus is where you share what you're counting down to with your friends

Hacker News4

Sunsaya14%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Share hobbies with your friends

Indie Hackerscommitment-full-time

Video to Article31%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Video to Article

Hacker News5

My first article: SSO using Flask and selenium48%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

My first article: SSO using Flask and selenium

Hacker News8

Interactive article on convolutions52%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Interactive article on convolutions

Hacker News1

Hypodash69%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

AI Article Automation

Indie Hackers1ai

I wrote a 2000 word article on dealing with chargebacks44%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

I wrote a 2000 word article on dealing with chargebacks

Hacker News15

Chimp Rewriter52%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

The fastest article rewriter

Indie Hackers1advertising

Just The Article Please38%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

A simple article reader for the web

Product Hunt+127Web App

Narrating the web one article at a time44%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Narrating the web one article at a time

Hacker News1

Browse all products Analyze your launch