Weaviate is an open-source, AI-native vector database that enables fast and semantic search and retrieval of unstructured information such as text, images, and more. By leveraging machine learning models, Weaviate's vector-based approach allows for highly relevant and context-aware search results, making it ideal for tasks like recommendation systems, Retrieval Augmented Generation (RAG) applications, and natural language search. A team from Weaviate evaluated Superblocks, a low-code platform, to build full-stack data applications that leverage Weaviate's vector search and RAG functionalities, and found it to be highly flexible, allowing them to bring together all their data sources and quickly deploy any type of solution. Superblocks has been shown to save time for data engineers like the one who quoted "Superblocks is a huge time saver for me - it allows me to focus on what I’m good at (i.e. data engineering) rather than having to design, develop, and deploy a user interface for my demos and apps."