Large Language Models (LLMs) are rapidly reshaping how companies build AI-driven products, with organizations across every industry integrating LLMs into their workflows. But as adoption accelerates, a critical challenge has emerged: how do you gain visibility into what these models are actually doing in production?
Join AWS and Lumigo as we explore the growing need for LLM observability, from tracking prompt inputs and responses to debugging failures and monitoring performance across chains and agents. We’ll explore the most common observability needs teams face when deploying LLM-based workflows and discuss why traditional tools fall short.
You'll discover how Lumigo, an AI-powered observability platform originally designed for distributed cloud applications, has evolved for monitoring LLM workflows. Its native full-payload data capture capabilities make it uniquely suited to track complete prompt-response cycles, giving you deep insight into your AI applications. We’ll wrap up with a live demo showing how you can gain end-to-end visibility into your LLM pipelines in minutes.
What you’ll learn: