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Guggy V2 – Smartly predicting the GIFs and stickers you want to send

Hacker News

Guggy V2 – Smartly predicting the GIFs and stickers you want to send

Hi all, We are extremely excited about Guggy V2. This is what we've done in the last few months. - Introducing "Guggy Stickers" - Context-based stickers as well as GIFs - A major overhaul of our image rendering server (generating GIFs and stickers under 200 milliseconds - we are now the fastest GIFs generator in the world) - Added multiple choices (as the users requested) - Significantly improved our prediction abilities - Added /guggysticker command to our slack app Go to https://guggy.com and try it out, you will love it!

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Actual performance

3points
6comments
Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
70%70% 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: slack, user, context · Missing: mac, agents, macos
58%58% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: excited, io · Missing: https docs, just released, exist
53%53% 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 · Strong signals: month, users · Missing: mobile apps, ios, personal
52%52% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: users · 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
16%16% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: smart · Missing: web3, chat, crypto
1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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