In this session, we demonstrate an AI-powered e-commerce solution that uses vector similarity search with Python, the python-oracledb driver, and Oracle Database 26ai. The database hosts a catalog of product images represented as vector embeddings. When a user provides a new image, the system queries the database to retrieve the most visually similar items. You’ll learn how to generate image embeddings using AI models, store them as native vectors in Oracle Database, and leverage built-in AI vector search capabilities to power image-based product discovery, recommendations, and personalization.