Speaker
Description
We present a suite of applications for an agentic chatbot to enhance workflows in the LHCb Real-Time Analysis (RTA). The first presented use case allows experiment operators to request, via natural language on the Mattermost platform, the automated generation of monitoring plots—such as trigger rate or detector temperature versus time—from live or historical subsystem data. This functionality extends to providing streamlined access to operational databases and efficient retrieval of operational knowledge. Another presented use case is the "problem finder," a feature that checks whether an LHCb data taking run encountered any issues or anomalies. These applications are components of the "LHCb Brain," an intelligent assistant for the entire collaboration. This work represents a significant step towards AI-integrated experiment operations, enhancing the efficiency and analytical capabilities of its operators.