Deploying generative AI in the enterprise requires more than just fine‑tuning a model — it demands a reliable data backbone, scalable orchestration, and secure integration into business workflows. In this session, we’ll explore how combining Databricks’ lakehouse platform with Azure AI Foundry provides an end‑to‑end foundation for bringing LLM‑driven applications to life.

We’ll begin with how Databricks can prepare and govern trusted data in Delta Lake, enabling robust data pipelines that feed directly into AI training and retrieval‑augmented generation workflows. From there, we’ll show how Azure AI Foundry operationalizes those models — managing deployment, guardrails, evaluation, and integration into enterprise systems.

Attendees will leave with a reference architecture demonstrating how to link data engineering + model development + secure AI deployment across Databricks and Azure, enabling agentic AI applications that are both cost‑efficient and enterprise‑ready.