Hi hackers! I built NameQL to help me find names for my new products, and I hope you'll find it helpful too.
It considers 100k+ names in milliseconds and shows you the best for which [name].com is available. Sure, tools like this exist, but I don't know of any that come close in terms of speed.
I used an n-gram predictive model, trained on an English word corpus to generate the suggestions. For ridiculous performance, I used a Bloom filter backed by Redis, together with some sneaky and caching and prefetching.
My next plans are to enhance this by searching the app stores for similarly named apps, and also checking for relevant trademarks, since I find myself doing that a lot manually. And I would like to add more advance name generation controls, like choosing prefix words matching parts of speech and using n-gram word models to generate phrase suggestions.
If you can provide lots of names fast, you should definitly show that your users. Dont let them click over hundreds of sites with a small amount of names.
Just one thought about usefullness with your design. Give the user the option to mark/remember names. If the user finds a good name at the first page, there is a good chance that the user can not remeber the name from page 1 on page 10.
Make sense now, but maybe you should reduce the clicks(on the desktop) for the "1. open modal -> 2. save/buy click -> 3. close modal" action. There is enough space to the left and right side of the names.
This is great, and the trademark would be an awesome addition! I also often use namechk to validate socials right after I find a good .com... maybe you can link to them (note: i’m not affiliate)
Thanks! You can request access to zone files from the domain authorities. I take the raw zone file and load it into a series of Bloom filters backed by Redis. There are a lot of domains to check against, and a probabilistic data structure is the only way to store it in memory, which you need for performance. This has the small caveat that the tool will accidentally think a domain is not available about 0.1% of the time. However, it shouldn't ever report domains as available when they are not. So that works quite well for a tool like this.
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[ 3.0 ms ] story [ 48.3 ms ] threadIt considers 100k+ names in milliseconds and shows you the best for which [name].com is available. Sure, tools like this exist, but I don't know of any that come close in terms of speed.
I used an n-gram predictive model, trained on an English word corpus to generate the suggestions. For ridiculous performance, I used a Bloom filter backed by Redis, together with some sneaky and caching and prefetching.
My next plans are to enhance this by searching the app stores for similarly named apps, and also checking for relevant trademarks, since I find myself doing that a lot manually. And I would like to add more advance name generation controls, like choosing prefix words matching parts of speech and using n-gram word models to generate phrase suggestions.
Thanks for checking it out!