# Vector Search

## Overview

**Vector search** enhances the search experience by finding results based on **meaning**, not just exact keywords. It helps users discover relevant content even when traditional keyword search fails. Unlike keyword search, which relies on exact word matches, vector search represents text as **high-dimensional vectors** (also known as **embeddings**) that capture context and semantics. This allows the system to present results that align with the **intent** of the query, even when different words, synonyms, or natural phrasing are used.

### **How does it work?**

* **Text is converted into vectors**:\
  Both the user query and the searchable content are transformed into high-dimensional numeric representations called **vectors**. These vectors capture the **meaning** of the text.
* **Similarity is measured**:\
  The system compares vectors and returns the results most similar to the query using a proprietary similarity metric.

### **Privacy & Technology Note**

Powered by advanced **vector-based language understanding** but **does not rely on generally available  AI** or **LLMs (large language models)**.\
All processing happens **on our servers**; **your data never leaves our infrastructure**.

## **When Vector Search Helps**

Vector search is especially valuable when:

* You want results that match **intent**, not just exact keywords.
* Queries are written in **natural language**, such as full sentences or questions.
* Users often search with **synonyms, related terms, or varied terminology**.
* Queries may contain **typos, spelling errors, or other mistakes**.
* Queries may include **mixed languages**.

### **Pros and Cons**

**Pros:**

* Finds relevant results even with vague, unstructured, or error-prone queries.
* Handles synonyms and paraphrases automatically.
* Great for exploratory or conversational search experiences.

**Cons:**

* Results can be less explainable.
* Accuracy and relevance may require some fine-tuning.

Vector search is available in two modes:

* [Fallback Vector Search](/docs/modules/vector-search/fallback-vector-search.md) – used when keyword search returns no results.
* [Hybrid Search](/docs/modules/vector-search/hybrid-search.md) – combines keyword and vector search for broader coverage.

## Suggest

For all setups where Vector Search is enabled and active, vector search will also be automatically active in Suggest. This will ensure similar results in Suggest as in the product search.


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