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NamesMixer – brandable, available domain ideas in seconds
Hacker NewsNamesMixer – brandable, available domain ideas in seconds
I built NamesMixer to speed up naming. Demo: https://namesmixer.com What it does: - Brandable ideas from keywords (prefix/suffix/dictionary) - Instant availability - TLD (.com/.ai/.io) & length filters - One-click registrar links - No signup Tech: React + Vite, FastAPI, Supabase, Nginx (Scaleway).
Share cardActual performance
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Did not reach leaderboard
Launch Intel predictions
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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting55%55% 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.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive48%48% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: nginx, ide, io · Missing: https docs, excited, just released48%48% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos29%29% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: way · Missing: mobile apps, ios, personal28%28% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue14%14% 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, crypto11%11% predicted probability of success on BetaList, based on ML models trained on real launch data.
Correct prediction on native model
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