Building Enterprise-Grade GenAI Apps with MLflow and Vector Search (repeat)

This session is repeated.

Generative AI is rapidly transforming the way we work and do business. For the enterprise, it presents both significant opportunities and challenges. The rapid adoption of AI is essential for staying ahead of the competition. Protecting and preserving intellectual property and proprietary data is equally important. Generative AI applications provide the biggest advantage when allowed to retrieve and learn from proprietary data. This presents enterprise software developers with the architectural challenge of setting up guardrails around generative AI deployments. Databricks is uniquely positioned to address this challenge with Unity Catalog as the universal governance layer. Corning builds LangChain-based AI agents to interface with structured (generative BI) and unstructured (augmented information retrieval) proprietary data. We discuss how Corning uses MLflow and Databricks Vector Search to deploy generative AI APIs under the governance of Unity Catalog.