Trust3 AI, founded by the creators of Apache Ranger, today extended its agent security controls to the Databricks Unity AI Gateway. Announced from San Francisco, the integration enables Trust3 AI to secure agents on the Databricks Unity AI Gateway, controlling both what an agent can do and what data it can reach with build-time controls enforced at runtime and every decision logged.
Companies putting agents into production govern them one platform at a time. Each platform ships a harness and gateway for its own traffic, so policy lives inside each platform and nowhere above them. Every platform has its own gateway that only knows its own traffic. Trust3 AI now enforces one agent policy across Databricks, in addition to Azure, Snowflake, and AWS gateways. Trust3 AI sits above the platforms and provides the security control plane that reconciles and enforces unified enterprise policies across all of them. The platform brings a unified metadata and policy graph and applies the same controls across multiple gateways.
The Unity AI Gateway governs AI traffic inside Databricks including agent activity, model requests, tool calls, and inference logging. Trust3 AI sits above it and adds Purpose-Based Access Control that builds policies from an agent's declared purpose and context, then enforces them inside the Unity AI Gateway through gateway plugins. Full Visibility and Monitoring discovers and profiles every agent configured on the gateway and collects gateway traces to monitor token budgets, scope drift, and other signals. Continuous Posture and Runtime Enforcement continuously assesses each agent's security posture expressed as a Trust Score, where build-time configuration factors into what the agent is permitted to do. Audit-Ready Records ensure every agent decision leaves a record an auditor can retrieve on request.
"Every platform is shipping a gateway for its own agents and traffic, and that is the right thing for a platform to do," said Balaji Ganesan, Co-founder and CEO of Trust3 AI. "But no enterprise runs just one platform. Your agents cross Databricks and a number of other systems. We built the security control plane that sits above the platforms so unified enterprise policies can be reconciled and enforced across all of them."
A gateway typically asks whether a request is allowed by checking authentication, endpoint permission, and rate limits. An agent can pass all three and still reach data outside the scope of its task because the gateway evaluates the request without context. Trust3 AI addresses this by checking purpose and context at the gateway chokepoint.
"We weren't putting agents anywhere near sensitive client data until we could answer two questions: what is this agent allowed to do, and what data did it touch," said the Chief Information Security Officer of a global investment management firm. "Trust3 AI gave us the answer to both, at the gateway, which acts as the chokepoint."
Databricks is one instance of a broader pattern, with Trust3 AI extending to agent frameworks and coding clients enterprises run alongside gateways. Enforcement happens at each gateway while policy stays consistent across the board.
About Trust3 AI
Trust3 AI is the security control plane for enterprise AI agents and data. The platform applies purpose-based access control across agent actions and the data agents reach, from build time to runtime. Trust3 AI connects to any agentic framework and governs agents across clouds, platforms, and AI gateways including Databricks, Microsoft, and Snowflake environments. Enterprises use it to discover every agent, observe every decision, and secure every action. Trust3 AI is a Databricks Built On Partner, a member of the NVIDIA Inception program, and a member of the Snowflake Startup Accelerator.
