Here is an example of a typical RAG-based application that utilizes vector embedding of text data. Instead of performing vectorization on the application side, we use the semantic search feature for text data provided by Fujitsu Enterprise Postgres.
Use different algorithms and models to extract text from different data in your organization.
Store the text data in Fujitsu Enterprise Postgres. To use the semantic search function in text, declaratively define the vector representation to be used for the stored textual knowledge data. This automatically creates the vector data necessary for semantic search.
The text semantic search feature returns text that is semantically similar to the text you are searching for. No conversion to vector representation is required on the application side.
