Scale AI into production

Getting an AI application into production is only part of the journey. As organizations move beyond their first applications, the challenges shift. It’s no longer one graph behind one application. It’s dozens of workloads across teams, tenants, and environments; availability expectations that come with production status; data spread across warehouses that were never going to move; and individual graphs that keep growing. The capabilities below address each of those dimensions, helping teams scale AI into production without adding unnecessary infrastructure and complexity along the way. Agents are only as good as the context they reason over, and most of that context sits in warehouses and lakehouses that were never built to serve it in graph shape. The traditional answer, ETL it into a graph, creates pipelines to maintain, a second copy of governed data, and a second system of record that drifts from the first. For a lot of data, especially data that is too large, too governed, or too operational to move, that trade-off kills the project before it starts. Virtual Graph, currently in public preview for every Aura customer and moving to General Availability in a couple of months, lets you create and query a knowledge graph directly…