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Weaviate uses GraphQL to provide user-friendly data interaction. Weaviate is an open-source vector search engine, and all searches (e.g. semantic, contextual) are done via its GraphQL API. We’ve put a lot of thought into the design of the GraphQL API, which results in good user and developer experience. In this talk, I will take you along in the journey of how our GraphQL implementation was shaped according to user needs and software requirements, and show a demo of the current design for Weaviate. The demo will show how Weaviate’s GraphQL design enables semantic (vector) search in combination with scalar search through unstructured data. Machine learning models are used in the background, but with the current GraphQL design, users without a technical background can query the vector database easily. The newly released Question Answering module added on top of regular search together with a carefully designed API, shows how Weaviate enables machine learning-powered vector search without much user effort.