Semantic Search

This article defines vector databases and explains how they store and retrieve unstructured data using mathematical embeddings to power modern artificial intelligence applications for startups.

This article explains semantic search optimization for founders, contrasting it with traditional keyword SEO and highlighting how to build long-term authority through context, intent, and structured entity relationships.

Embeddings translate data into numbers to capture meaning, enabling startups to build smarter search and recommendation features without needing a data science degree.