Visier augments every Databricks deployment to provide a rich semantic layer for workforce data, built for the era when every major AI initiative runs through the lakehouse, ending years of logic debt for enterprise organizations worldwide VANCOUVER,

Databricks says new products LTAP and Lakehouse//RT unify transactional and analytical data for AI agents, delivering sub-100ms latency and no ETL pipelines.

Successful AI adoption depends less on models and technology than on workforce transformation, process redesign and organizational change.

The company added more details about AI Runtime, a serverless graphics processing unit for enterprise deep learning that has been in preview for the past two months. Databricks also announced Genie Code for ML and Genie Zero Ops for ML, an agent for running machine learning systems.

Shanku Niyogi of Databricks walks through the architecture behind Lakebase, LTAP and Lakehouse//RT – and renames an industry workaround in a relatable way that acknowledges the pain points experienced by data engineers.

LakeFusion MDM is now available as a Databricks App, letting customers install and deploy governed master data

By merging transactional and analytical workloads, LTAP promises fewer pipelines, lower costs, and better governance.