Semantic Search Engine

Embeddings

Semantic Search EngineSemantic Search

Semantic Search Engine is a search system based on embeddings and cosine similarity that understands query intent rather than keywords.

A semantic search engine is a search system based on embeddings and cosine similarity that understands the intent behind queries rather than just matching keywords.

For example, searching 'how to rank a law firm' returns articles about 'SEO for lawyers' and 'law firm online marketing' — even though the words don't overlap. Semantic search engines are built in Supabase with Edge Functions: the user enters a question, the Edge Function generates an embedding, searches the pgvector database, and returns results.

Semantic Search Engine represents the transition from one-time Colab analyses to production applications running 24/7. The model can detect connections humans might miss — for example, 'SemKRK' close to 'Search Conference 2018' because both relate to SEO conferences.

In practice, a semantic search engine for client websites is a great product to sell — it requires one-time configuration but provides continuous value.

Source: AI Semantic SEO Expert, Robert Niechciał (sensai.io)