Namicious – Curated AI Business and Domain Names

Hacker News

After spending time and energy thinking about a domain name for my website I find that most .com domains are reserved at unaffordable prices for a startup. That's when I thought of using GenAI technologies to create ideas of names that could be free to acquire and reserve those that sound good but at an affordable price for everyone. Namicious eliminates that disappointment by providing you with an inventory of available domain names at your fingertips. Harnessing the speed and intelligence of AI. GenAI creates numerous names and we select the best ones and put them on this page for you. Many times GenAI, creates repetitive and uncreative names so we try different prompts to get better ways. We continuously generates fresh and exclusive domain options. I would really appreciate your comments and also if you can share some ideas of what we could implement to stop having unused .coms. Kudos! Dan

Visit product View on Hacker NewsJun 21, 2023

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Actual performance

2points

Did not reach leaderboard

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

78%78% 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 · Strong signals: exclusive · Missing: plus, platform, intuitive

48%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: ide, io · Missing: https docs, excited, just released

42%42% 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

33%33% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: using · Missing: mac, agents, macos

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

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

11%11% 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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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