Ripples: Exploring Communication Patterns in Organizational Multi-Agent Systems

Authors

Nabin Khanal (Purdue University), Qi Yang (Purdue University), Sizheng Cailean Chen (West Lafayette Junior Senior High School), Jasmine Tang (McGill University), Andralyn Yao (Stanford University), Justin Li (Carmel High School), Zhancheng Su (Carmel High School), Aaron Wang (University of British Columbia), Hannah Yanhua Zong (Purdue University ), Zhenyu Cheryl Qian (Purdue University), Yingjie Victor Chen (Purdue University), Jieqiong Zhao (Augusta University)

Abstract

Monitoring organizational multi-agent systems is challenging because people and AI agents coordinate asynchronously, and anomalous behaviors may emerge from interactions buried within large volumes of actions. We present Ripples, a visual analytics system for investigating communication and delegated tasks in organizational multi-agent systems. Five coordinated views support analysis from temporal patterns to detailed interactions among people, agents, files, and tasks. Using the 2026 VAST Challenge MC2 dataset, we demonstrate how Ripples reconstructs the workflow behind anomalous SaidIT posts, traces instruction files backward through chains of subordinate tasks, compares similar incidents, and identifies opportunities for intervention. By integrating temporal, communication, high-level task, and low-level action views, Ripples enables analysts to analyze task and communication chains behind anomalous behavior and supports targeted mitigation. Demo video available at: https://youtu.be/_C7vpAONsZQ.