How to Decipher User Uncertainty with GenAI and Vector Search

User expectations are sky-high, while at the same time users have difficulty articulating their complex needs in a simple search bar on a website. This talk dives into leveraging generative AI and vector search to transform vague user queries into results the user actually wanted, even if they did not know initially what they clearly wanted. We will explore why traditional search methods fall short in grasping user intent and address the common problems users face with ambiguous search queries.

Learn how GenAI generates embeddings to capture the context and semantics of queries, and how vector search optimizes these embeddings using Couchbase. This talk though is not only about the theory. In the talk you will be shown practical examples of how to generate embeddings, and how to set up vector indexes.

See how these advanced search capabilities can transform user interaction and, as a result, business outcomes, making user uncertainty into certainty with GenAI and vector search.