Data and Content Foundations: Preparing the Enterprise for RAG Performance

RECORDED WEBCAST

Most enterprise AI tasks do not require deep information architecture. Copilot, ChatGPT Enterprise, and similar tools work well for a wide range of use cases, particularly where vocabulary is consistent, ambiguity is low, and the cost of being wrong is manageable.

The question is knowing when that stops being true.

When your organization has tens of thousands of documents across dozens of repositories, some of that content is fine as-is. Some of it is actively undermining AI performance. And some of it needs structural engineering before AI can retrieve it accurately. The problem is that most organizations have no systematic way to tell the difference.

This session covers how to evaluate the entire content ecosystem, prioritize where poor quality content creates the highest risk, identify what needs to be updated first, and make those changes at scale. We will walk through content scoring frameworks, triage processes, and the automation approaches required when the content landscape runs into the hundreds of thousands or millions of documents. With examples that apply to manufacturing, life sciences, insurance, and financial services.

This webinar is part of Earley’s 7-part AI Readiness Webinar Series. View the full series overview →