Evolving Agent Complexity: Building Multi-Agent Systems With Mosaic AI
Overview
Experience | In Person |
---|---|
Type | Breakout |
Track | Artificial Intelligence |
Industry | Financial Services |
Technologies | MLFlow, Mosaic AI, Unity Catalog |
Skill Level | Intermediate |
Duration | 40 min |
This session dives into building multi-agent systems on the Mosaic AI Platform, exploring the techniques, architectures and lessons learned from experiences building Greenlight’s real-world agent applications. This presentation is well suited for executives, product managers and engineers alike, breaking down AI Agents into easy-to-understand concepts, while presenting an architecture for building complex systems.
We’ll examine the core components of generative AI Agents and different ways to assemble them into agents, including different prompting and reasoning techniques. We’ll cover how the Mosaic AI Platform has enabled our small team to build, deploy and monitor our AI Agents, touching on vector search, feature and model serving endpoints, and the evaluation framework. Finally, we’ll discuss the pros and cons of building a multi-agent system consisting of specialized agents vs. a single large agent for Greenlight’s AI Assistant, and the challenges we encountered.
Session Speakers
Tim Mullins
/Staff Machine Learning Engineer
Greenlight Financial Technology
Shanduojiao Jiang
/Machine Learning Engineer
Greenlight Financial Technology