Traditional databases (SQL) store data in tables and rows. They are great for "What is the price of product X?" but terrible at "Find me products similar to this image." This is where Vector Databases come in.
What is a Vector? In AI, every piece of text or image is converted into a long list of numbers called an embedding.
The Geometry of Meaning: In a vector space, similar concepts are mathematically close to each other. "King" and "Queen" live in the same neighborhood; "Apple" (the fruit) and "iPhone" live in different ones.
Why it matters: Vector search allows Vecsai to perform Semantic Search. It enables the system to "feel" the similarity between data points, acting as the long-term memory for the AI models we run via Ollama.