Generic to Genius: How to Enrich Agents With Third-Party Data

Building context-rich AI agents shouldn't require months of data engineering. Most developers spend more time wrestling with gated data sets, brittle scraping scripts, and countless hours finding, cleaning, and structuring data than actually building intelligence. Even when agents are built, there is no easy way to share them across teams, leading to duplicated effort organization-wide.

This hands-on lab shows you how to spin up an agent in minutes and enrich it with properly licensed, AI-ready data from multiple sources. You'll unify structured data through pre-built semantic views from trusted providers and layer in publisher-quality external knowledge via Cortex Knowledge Extensions (CKEs) — no data engineering required. Then you'll share the agent so other teams can immediately be empowered with expert intelligence — all with enterprise-grade security and compliance in place.

In this lab, you'll learn how to:
 

• Quickly deploy an agent and enrich it by unifying structured and unstructured data sources
• Connect shared semantic views with pre-built, governed data models from trusted providers
• Layer in external, AI-ready content using Cortex Knowledge Extensions
• Share the agent across your organization for instant reusability

This lab is perfect for: Developers, data engineers, and AI engineers who want to build production-ready agents quickly by leveraging pre-built data products instead of starting from scratch.