Understanding RAG Pipelines
Vectorzie RAG Pipeline enable you to quickly and easily build vector search indexes from unstructured data sources like documents, PDFs, and knowledge bases. This feature integrates directly with your own database, giving you complete ownership and control over your data. By converting unstructured data into vector embeddings and storing them in your vector database, the RAG Pipeline enables fast, real-time retrieval of relevant information.
With the RAG Pipeline feature, your vector indexes can be fully populated within minutes, allowing you to quickly transform your unstructured data into a searchable format. The setup process is streamlined and efficient, so you can begin querying your data almost immediately, without the need for complex configurations or long delays.
The RAG Pipeline feature provides high observability and real-time visibility into how your data is processed and indexed. As changes occur in your unstructured data sources, these updates are reflected in the vector indexes to ensure that they remain synchronized. This ensures that your vector indexes are always up to date with the latest changes in your data, providing confidence in the accuracy and relevance of the information retrieved.
