Weaviate + Box RAG recipe with Weaviate Query Agent

A newly released demo from the BoxDev team showcases an end-to-end Retrieval-Augmented Generation (RAG) workflow using Box and Weaviate, highlighting how to embed Box content into a Weaviate vector database and leverage its Query Agent to answer user questions with AI-driven search capabilities. Box is described as a leading platform for intelligent content management, allowing secure file storage and collaboration, while Weaviate is an open-source vector database designed for fast, scalable, AI-powered search. The RAG solution combines vector search with a language model to provide context-aware answers from the user's data. Users are guided through setting up a Box developer token and a Weaviate Cloud cluster, followed by downloading and executing the demo recipe, which includes preloaded financial reports for testing, with options to expand and customize data and queries. The integration of Box's content management and Weaviate's search capabilities illustrates how modern tools can enhance data accessibility and intelligence, encouraging feedback and exploration of additional features and agents.

Use this post, company, and trend context to find content marketing opportunities, perform competitive analysis, or address product feature gaps via the Plushcap MCP server or the Plushcap API.