Oracle announced Deep Trust AI Architecture on Monday, a blueprint for putting security policies and business rules into the systems that AI agents and AI-generated applications use, rather than leaving those safeguards to each application.
Introduced at Oracle AI World in Las Vegas, the architecture brings together capabilities across Oracle AI Database, Oracle Autonomous AI Database and Oracle APEX AI Application Generator. The company described four areas of control: the software platform, the data itself, access to data and application development.
At the database level, Oracle Deep Data Security lets organizations define end-user access rules that apply to each SQL request. Oracle said identity is checked through a signed token from a corporate directory, while SQL Assertions enforce business rules such as an employee’s spending limit.
Deep Trust Data APIs provide access to logical business objects, including purchase orders, instead of allowing unrestricted SQL access. The intent is to limit agents and applications to the information and operations needed for a task.
For natural-language questions, Oracle’s Deep NL2SQL combines business terminology and practices with information about how data is organized. The company said its feedback and verification tools let users correct answers while validating changes before adding them to a corporate knowledge base.
On application development, Oracle APEX AI Application Generator translates descriptions into APEXlang, a declarative application-definition language. Oracle’s APEX runtime then executes those definitions, rather than asking companies to run large volumes of AI-generated execution code.
Oracle also pointed to automated patching and encryption in Autonomous AI Database as part of the underlying platform. The company says the architecture is designed to reduce risk; its October 26 announcement describes a blueprint and product capabilities, not an independent guarantee that AI systems cannot fail.
JBizNews Desk | Las Vegas
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