Ship Better Models:
A New ML Workflow with a Context Layer and Agents

On-demand Webinar

Give every model - and every AI agent - consistent, governed features and data.

Better ML models start with a context layer: shared feature definitions that standardize the data and logic behind production decisions. In this session, we’ll show how that same layer becomes the foundation for AI agents that can investigate model behavior, uncover missed opportunities, and run controlled experiments using the trusted context your ML teams already rely on.

We'll demonstrate how to:

• Define and organize the features and real-time signals used by ML models
• Build an ML data agent that retrieves and applies shared feature definitions
• Continuously improve ML models with agentic suggestions
• Reduce duplicated logic across data science, ML engineering, and agent teams

Who should watch:

• ML engineers and data scientists building production ML systems
• Data platform and engineering teams standardizing business logic
• Product and platform leaders looking to unify ML and agent development