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Smart Domain Search Engine - Review NameMesh

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Smart Domain Search Engine - Review NameMesh

Hi Everyone, I recently launched - http://www.namemesh.com and would love to have your feedback on it. Briefly: NameMesh is a smart .com domain search engine which quickly creates, ranks and checks names. It's 1) Complete - checks for lots of things like synonyms, antonyms, related words, portmanteau, misspellings, phonetic variations, short url, acronyms, suffixes, prefixes etc. 2) Relevant - ranks all the names based on quality metrics. supports ways to do complex queries. 3) Simple & Fast - single step process taking only seconds. Thanks

Visit productView on Hacker NewsNov 20, 2012
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Actual performance

1points
6comments
Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Strong signals: supports · Missing: reddit linkedin, podcasting, created
73%73% 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
61%61% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive
58%58% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released
55%55% 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 · Strong signals: way · Missing: mobile apps, ios, personal
26%26% 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, 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 · Strong signals: smart · Missing: web3, chat, crypto
2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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