Building a search proof of concept requires a different mindset than building a production system. This article shares practical OpenSearch tips for rapid prototyping, including vector embeddings, kNN search, hybrid search, indexing strategies, and UI considerations drawn from real-world experimentation.
Traditional search works well when users are looking for specific items. But workflows centered around building cohesive environments, such as set design and scene construction, introduce a different kind of retrieval problem. This article explores how OpenSearch, vector embeddings, and multimodal retrieval techniques were used to experiment with scene-oriented discovery and cohesive item selection.
Search governance adds structure, but it’s only part of the system. As shopper behavior, product catalogs, and business priorities constantly change, search needs to go beyond decisioning and continuously adapt. Governance, control, and optimization work together to keep results aligned with shopper behavior.
This article discusses how Model Context Protocol (MCP) expands AI chatbot capabilities with live data, actionable tools, and smarter workflows to improve customer interactions.
