Multi-Agent System Patterns: Architectures for Next-Generation AI Solutions

The evolution of generative AI has brought forth sophisticated multi-agent systems (MAS) that can tackle complex tasks through distributed intelligence and collaborative problem-solving. These systems represent a paradigm shift from traditional single-agent AI implementations to coordinated networks of specialized agents working in concert. As companies continue their digital transformation journeys, understanding the fundamental patterns of multi-agent architectures becomes crucial for designing robust, efficient, and scalable AI solutions. This workshop examines the core patterns in multi-agent systems—Parallel, Sequential, Loop, Router, Aggregator, Network, and Hierarchical—with specific applications in the financial services domain. We’ll explore how these architectures can revolutionize workloads across financial services through enhanced reasoning, planning, and collaborative intelligence. Expected outcomes:

• Learn how to build agentic systems using multi-agent collaboration
• Understand the different types of agentic collaboration patterns and their applications
• Gain practical knowledge of implementing multi-agent architectures that enhance decision-making capabilities in financial services
• Discover strategies for deploying scalable multi-agent systems that address complex financial workflows