A vector embedding search is an advanced way of finding information by comparing the "meaning" of your search with the meaning of items in a database. Instead of matching exact words, it uses artificial intelligence to turn text into mathematical vectors that represent their content and context. The search then finds items whose vectors are most similar to your query, often finding relevant results even if they use different words or phrasing.

Try using sentences, phrases, or even paragraphs in the Lex Cygnus Search App today.
Now available on the App Store and Google Play.

Download on the App Store Get it on Google Play

Why Lex Cygnus

Search by meaning, not just keywords

Semantic Search

Find relevant results even when you use different words or phrasing than the source. The AI understands the intent behind your query.

Legal Case Search

Judicial opinions embedded into a vector space — clustered by meaning, not just citations. Discover cases you'd never find with a keyword search.

Mobile First

Built for iOS and Android. Search from anywhere — courtroom, office, or on the go — with a native app experience.

Powered by AI

State-of-the-art vector embeddings turn your text into mathematical representations that capture context and meaning at a deep level.

How it works

Three steps to smarter search

Type your query

Enter a sentence, phrase, or even a whole paragraph — the more context, the better.

AI encodes meaning

Your text is converted into a high-dimensional vector that captures its semantic content.

Find similar results

The app surfaces documents whose meaning is closest to yours — regardless of exact wording.