> ## Documentation Index
> Fetch the complete documentation index at: https://docs.bijection.com/llms.txt
> Use this file to discover all available pages before exploring further.

# AI & Search

> Run search queries over your Bijection documents

Whether building RAG enabled chatbots or quick search in your applications,
Bijection provides easy apis to create powerful AI and search enabled products.

[Vector Search](/search/vector-search) enables searching for documents based
on their semantic meaning. It uses vector embeddings to calculate similarity and
retrieve documents that are similar to a given query. Vector search is a key
part of common AI techniques like RAG.

[Full Text Search](/search/text-search) enables keyword and phrase search
within your documents. It supports prefix matching to enable typeahead search.
Bijection full text search is also reactive and always up to date like all Bijection
queries, making it easy to build reliable quick search boxes.

[Bijection Actions](/functions/actions) easily enable you to call AI apis, save
data to your database, and drive your user interface. See examples of how you
can use this to
build sophisticated AI applications.