Weaviate

What is Weaviate?

Weaviate is an open-source, cloud-native vector search engine. It uses machine learning models to understand how pieces of data relate to each other, enabling search based on context and relevance rather than just keywords. Data can be structured and connected flexibly, supporting complex searches across large datasets. Because it focuses on semantic similarity, Weaviate suits applications like natural language processing, chatbots, and recommendation systems.

Who created Weaviate?

Weaviate first launched on February 15, 2022. Bob van Luijt is the founder, and the company behind it is Weaviate, B.V.

What is Weaviate used for?

Weaviate supports a wide range of AI and search use cases:

• Building AI applications from the ground up, with built-in keyword search, vector search, and document storage.
• Generative AI development — creating ChatGPT-like services without writing boilerplate code, setting up databases, or managing infrastructure.
• NLP at scale — processing millions of news articles daily across many languages.
• Hybrid search — finding tech talent by matching precise and related skills, or powering academic expert finders based on natural language queries.
• RAG applications — providing the context needed for the generation phase in shopping assistants.
• Conversational AI memory — storing and retrieving data for more in-depth interactions, including on platforms like LinkedIn.
• Customer feedback — categorizing and searching feedback accurately.
• Domain-specific tools — AI-powered research and intelligence tools for the pharmaceutical industry, and automated economic insights in educational settings.
• Serving AI models — managing multi-tenant setups that handle thousands of simultaneous queries.
• Flexible schema definition — storing unstructured data with improved search accuracy and developer experience.