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What you'll learn
What separates the 20% of agentic AI initiatives that pass governance review from the 80% that don't, and what it means for your evaluation criteria.
How structured scientific data and callable platform functions produce more consistent, traceable results than relying on probabilistic inference alone.
Why using the minimum AI necessary to reach the same result is a feature, not a limitation, and how it leads to more auditable, reproducible science.
What it looks like to build experiences with Luma Agent, query structured scientific data in context, and connect external AI tools through the MCP Server.
How Luma Agent connects to the tools and external AI systems your team already uses, without rebuilding scientific context from scratch each time.
Watch Luma Agent build an experience, query structured scientific data in context, and execute a workflow through the MCP Server, live and unrehearsed.
Your presenters

VP, Science & Technology, Dotmatics

Senior Product Manager, Dotmatics
Who should attend
Scientists and research teams in life sciences and pharma evaluating AI tools for production workflows
Scientific informatics and R&D IT leaders responsible for AI governance and data integrity in regulated environments
R&D directors and VP-level leaders who need agentic AI to move through governance review, not stall in it
Anyone whose team is already using or building with AI, and wants to understand the difference between analytical AI and production-ready agentic AI
Free to attend. 60 minutes. Watch Luma Agent reason through a complex scientific task in real time. Built on structured data your governance team can actually sign off on.