Buying or registering an ENS name has always been a guessing game. You think of a word, try it, get told it's taken, think of another, repeat. The names that would actually suit your project — that you would never have guessed — stay hidden in a registry of millions of strings.
AI Search changes that. Describe what you want in plain English. The semantic index returns the closest matches across the full ENS registry — including names that share meaning rather than letters.
How it works
We index every registered .eth name as a vector embedding. When you type a query — "names that sound like a DeFi protocol", "Italian first names", "short food words" — we embed the query the same way and return the nearest neighbours. The result is a list of names that share meaning, not just spelling.
What it is good at
- Brand discovery. "Modern fintech names ending in -ly" returns dozens of plausible options you would never type into a checker manually.
- Concept clustering. "Names that feel like a wildlife conservation project" pulls a cohort of nature-themed handles across many lengths.
- Cross-language nudges. Query in English, get translations and cognates you might not have considered.
- Availability-aware. The result list is filterable by registration status, length, and digit/letter composition.
Try it
Open /find/search and paste a description of the name you wish existed. The semantic search runs against the live ENS index and most queries return in under a second.