Platter – Grow on X/Twitter by replying smarter, not harder

Hacker News

I built Platter to help solo founders and indie hackers grow their audience on X/Twitter without spending hours scrolling and replying manually. The idea is simple: It builds a digital profile of your voice, product, and interests It finds high-signal tweets where you can add value It helps you craft thoughtful replies in your voice, with a single click It’s not a Chrome extension. You can engage anywhere, even on your phone. I made this because I found social growth necessary but draining. Would love feedback from the community, especially from anyone trying to grow while building.

Visit product View on Hacker NewsJun 23, 2025

Share card

Actual performance

1points

Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →

Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

89%89% predicted probability of success on Indie Hackers, 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 · Strong signals: single · Missing: mac, agents, macos

63%63% 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, intuitive

36%36% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: growth · Missing: arr, mrr, revenue

28%28% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

25%25% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released

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

nativeThis product was originally launched on this platform.

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

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

Similar products

ReplyPack34%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

An AI twitter replier to grow twitter accounts

TrustMRRArtificial Intelligence

Grow Your Twitter Audience20%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Grow Your Twitter Audience

Hacker News1

Tweetify – Grow your X (formerly Twitter) audience with AI14%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Tweetify – Grow your X (formerly Twitter) audience with AI

Hacker News2

Twitter Overhead Projection44%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Twitter Overhead Projection

Hacker News1

Trying to bootstrap my biz with Twitter bootstrap63%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Trying to bootstrap my biz with Twitter bootstrap

Hacker News2

Hooking up Twitter with Angellist47%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Hooking up Twitter with Angellist

Hacker News1

sweepstakes + Twitter = TweetStakes63%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

sweepstakes + Twitter = TweetStakes

Hacker News7

Twitter in London50%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Twitter in London

Hacker News1

ThemeForest for Twitter Bootstrap51%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

ThemeForest for Twitter Bootstrap

Hacker News7

Discreet Twitter buttons41%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Discreet Twitter buttons

Hacker News16

Browse all products Analyze your launch