Building data agents enterprise can actually trust

Building Data Agents Enterprises Can Actually Trust
Private Executive AI Forum · Palo Alto
Everyone is building AI agents. Far fewer are building data agents that can reason reliably over enterprise data — where information is fragmented, always changing, and missing critical context.
The hard part isn't picking the LLM. It's everything underneath: semantic layers, knowledge graphs, governance, identity, evaluation. Get those wrong and agents produce answers that sound convincing but are wrong — the most dangerous failure mode in production AI.
Join Jerry Xi, AI Platform Architect at Oracle, for a candid discussion on what it really takes to deploy trustworthy data agents at scale. Jerry has built AI infrastructure at Oracle, Meta, Lyft, and Box, and founded the MLOps platform DataTron.
What we'll cover
Why the semantic layer — not text-to-SQL — is the real differentiator
How to architect a production-grade data agent stack
How leading teams measure trust, catch hallucinations, and validate outputs
Operational lessons from running enterprise AI at scale
Speakers
Jerry Xi — AI Platform Architect, Generative AI & ML Infrastructure, Oracle (Keynote)
Rahul Choudhry — Leader, Data Science & Machine Learning, First American Title
Murray Newlands — Founder, Open Future Forum (Host)
Who should attend
Chief AI and Data Officers, CTOs and VP Engineering, AI platform and infrastructure leaders, enterprise architects, and founders building AI and data platforms.
Hosted by Open Future Forum, Agentic Fabriq, and HG Insights