Vector Search Demo: Turning Unstructured Text into Queryable Knowledge

In a recent demonstration during a Memgraph Community Call, Josip Mrden, Head of Solutions at Memgraph, showcased the company's innovative use of vector search capabilities to transform unstructured data into queryable knowledge. Highlighting the potential for educational tools and intelligent information retrieval applications, Mrden built an interactive Q&A app and an automatic pub quiz generator using Memgraph's graph database and vector search technology. The demo, initially a side project, utilized a tech stack including Streamlit, OpenAI, and LLMs, to effectively connect unstructured and structured data, enabling fast prototyping and creating interactive learning experiences. Memgraph combines graph and vector search functionalities, offering a unified platform that enhances performance, hierarchical knowledge composition, and reduces complexity, making it a compelling choice for GraphRAG applications. Future improvements to the system include role-based access controls, multi-tenancy, and expanded data ingestion capabilities.