As enterprises move from dashboards to autonomous agents on structured data, Trust3 AI centralizes access governance once and enforces it natively across Unity Catalog, AWS Lake Formation, Snowflake, and every query engine
SAN FRANCISCO, June 16, 2026 /PRNewswire/ — Trust3 AI today announced the latest release of its centralized data access governance platform at the Databricks Data + AI Summit, expanding support for federated catalog governance and multi-engine policy enforcement as enterprises prepare their data estates for agentic AI.
The 2026 Summit puts agentic AI on structured data at the center of the conversation. That shift raises the stakes for governance: when autonomous agents – not just analysts – query the lakehouse, every access decision must be correct, consistent, and auditable across each catalog and engine an agent can reach. Most organizations still administer policy separately in each system, which does not scale and leaves gaps the moment a new engine or agent is added.
Trust3 AI addresses this with a single policy administration point (PAP) that delegates enforcement to native catalogs and engines, so one set of policies is authored centrally and applied everywhere it needs to live.
Centralized policy, native enforcement, federated catalogs
Large enterprises increasingly run more than one catalog. Trust3 AI lets organizations standardize on a single point of policy administration while delegating enforcement to native systems such as Unity Catalog and AWS Lake Formation – including newer patterns where one catalog acts as primary and another is federated beneath it. A Fortune 500 financial software company uses this model to run fine-grained access control (FGAC) at enterprise scale across Lake Formation and Unity Catalog from one administration layer – a level of FGAC that is not practical to operate catalog-by-catalog.
Governance that propagates to every engine
Modern lakehouses built on open formats like Apache Iceberg are routinely queried by multiple engines. Access policy does not automatically follow data across those engines, and that gap is exactly where exposure occurs. Trust3 AI propagates a single policy set across engines including Databricks/Unity Catalog, Snowflake, AWS Lake Formation, Dremio, Spark, and EMR. A cloud enterprise-applications provider relies on Trust3 AI to keep one consistent policy in force across an Iceberg lakehouse served by several query engines, rather than re-implementing rules in each.
Dynamic policies that collapse policy sprawl
Static, role-by-role policies multiply uncontrollably at scale. Trust3 AI‘s attribute-based access control (ABAC) lets teams express intent dynamically, cutting the number of policies they manage by an order of magnitude or more. A global advertising and media network replaced roughly 2,000 catalog policies with about 20 dynamic policies, and a Fortune 50 media and telecommunications company reports a comparable ~100x reduction while applying identical enforcement across 8+ connectors on both Unity Catalog enabled and non-Unity Catalog clusters, including Databricks Spark and Spark on Kubernetes.
Day-zero coverage for new platforms
Because policy lives in one place, onboarding a new platform inherits existing governance immediately. As the same advertising and media network added Snowflake, centralized administration cascaded the same enforcement to Snowflake from day zero – no rebuild required.
Beyond native catalog limits: data products and purpose-based access
For organizations hitting role explosion in cloud warehouses, Trust3 AI introduces governed data products with multiple subscriptions and purpose-based access control at the governance layer – instead of bespoke workarounds inside each native catalog. A leading healthcare analytics organization uses Trust3 AI‘s data products to manage entitlements and purpose-based access that native warehouse capabilities alone could not sustain. Other enterprises are extending this toward frictionless, end-to-end access provisioning that eliminates manual steps and incorporates data products defined in tools such as Microsoft Purview.
Centralized governance across hybrid estates
Trust3 AI customers operate a single policy administration point across heterogeneous stacks – combinations spanning Unity Catalog, Starburst, Snowflake, SQL Server, Lake Formation, and EMR – and pair access control with capabilities such as format-preserving encryption to protect sensitive data while keeping it usable, with reported productivity gains of up to 10x.
“The lakehouse was supposed to make data accessible. What it didn’t come with was a way to govern that access consistently across every engine and catalog in your stack. That’s exactly why we built Trust3 AI to solve — and with agentic AI arriving on structured data, the need has never been more urgent.” said Don Bosco Durai, Co-founder & CTO, Trust3 AI.
At Databricks Data + AI Summit 2026
Trust3 AI is at the Databricks Data + AI Summit, June 15–18 in San Francisco. Stop by our coffee truck at 3rd and Howard, Monday through Wednesday, 9 AM – 5 PM, to meet the team and learn more about centralized policy administration, federated catalog governance, and multi-engine enforcement.
About Trust3 AI
Trust3 AI provides a trust and governance layer for agentic AI giving security and platform teams visibility into the agents and MCP tools operating in their environment, runtime validation of agent behavior, and an attestable audit trail of agent decisions across their data estate. Trust3 AI is part of the Databricks startup accelerator.
SOURCE Trust3 AI
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