Trust3 AI Expands Centralized Governance Across Multi Engine Lakehouses

Trust3 AI announced the latest version of its centralized data access governance platform at the Databricks Data + AI Summit, expanding support for federated catalog governance and policy enforcement across multiple query engines, according to a press release.

The update enables enterprises to manage one set of access policies that apply consistently across systems including Unity Catalog, AWS Lake Formation, Snowflake, Dremio, Spark, and EMR. The platform provides a single policy administration point that delegates enforcement to native catalogs and engines, allowing organizations to maintain uniform governance as they add new platforms.

The new release also introduces dynamic attribute based access control to reduce policy sprawl and simplify management. Trust3 AI reports that some customers were able to replace thousands of static catalog policies with a small number of dynamic ones while maintaining identical enforcement across different environments.

By centralizing governance, Trust3 AI aims to help enterprises manage hybrid data estates that combine multiple catalogs and engines. The platform supports fine grained access control and integrates with tools such as Microsoft Purview to extend governed data products and purpose based access control across systems.

The announcement was made during the Databricks Data + AI Summit held in San Francisco from June 15 to 18, where Trust3 AI showcased its unified policy management approach for agentic AI workloads.