From Pixels to Knowledge: Transforming Images into Knowledge Graphs for Semantic GraphRAG Search

Understanding and searching image data is a major challenge in AI-driven systems. EBCONT and Memgraph teamed up to build a powerful visual search pipeline that combines computer vision, vector embeddings, and knowledge graphs. The result? A system that can interpret images, store them semantically, and answer questions like “Is there a yellow car in the dataset?” — all in real time.

Join Dino Duranovic (EBCONT) and Ante Javor (Memgraph) as they demonstrate how raw images can be transformed into structured graph data using CLIP, Gemini, and Memgraph’s vector search capabilities.

What You’ll Learn

• How to use CLIP and vector search for image-to-image and text-to-image retrieval
• Why graphs are essential for adding context and structure to visual data
• How GraphRAG enables relevance expansion and natural language Q&A
• Practical insights on building a GraphRAG-based visual search system