Learn how to configure and use the Juvare AI Assistant (JAI) to find, summarize, and interpret information from WebEOC boards using natural-language questions. This session will cover selecting the right board views as data sources, defining useful topics, applying row- and column-level visibility controls, and demonstrating practical operational use cases. We will also discuss how JAI honors existing WebEOC permissions and how administrators can use analytics and conversation logs to understand adoption.
