Oracle Announces Deep Trust AI Architecture to Help Enterprises Innovate with Confidence

New architecture helps organizations reduce risk as AI adoption expands by embedding trust into four critical layers of the technology stack 

LAS VEGAS, Oct. 26, 2026 /PRNewswire/ -- Oracle AI World -- Oracle today announced its Deep Trust AI Architecture, a blueprint that makes trust a built-in property of the enterprise technology stack rather than a responsibility left to every AI agent and application. Bringing together proven capabilities across Oracle AI Database, Oracle Autonomous AI Database, and Oracle APEX AI Application Generator, the architecture enforces security, privacy, business rules, and trusted application generation, helping enterprises accelerate AI innovation while reducing risk.

As organizations deploy more AI agents and AI-generated applications onto existing architectures, they face growing challenges in protecting sensitive information, enforcing business rules, getting accurate answers to business questions, and maintaining control over how AI interacts with enterprise systems. Oracle Deep Trust AI Architecture helps organizations address these challenges by embedding trust where it cannot be bypassed or compromised by AI models, deep within the four critical layers of the enterprise technology stack: software platform, data, data access, and application development. Much like Oracle's popular Maximum Availability Architecture (MAA), this blueprint helps organizations realize AI's productivity and innovation benefits without relying on each application or agent to completely and correctly implement all the needed safeguards.   

"AI models can now enable amazing productivity and innovation. However, enterprises can't realize these benefits if they can't trust what AI generates. AI trust is the biggest challenge we face today," said Juan Loaiza, executive vice president, AI Database Technologies, Oracle. "With Oracle Deep Trust AI Architecture, we are building trust into the underlying software platform, data, data access, and application development layers. This enables organizations to put AI to work while maintaining control over the information and actions that AI agents and AI-generated applications can take."

Protecting enterprise data through the underlying software platform 
AI is helping attackers find new vulnerabilities and reverse engineer published vulnerabilities faster than ever, making complete and timely patching essential. Oracle Autonomous AI Database helps eliminate manual patching by automatically applying security updates across the database engine, operating system, storage, and firmware before the software updates are made public. With rolling patching, updates proceed in stages while applications keep running without disruption. In addition, always-on encryption protects data at rest and in motion, with transparent decryption for authorized users and applications. Oracle Autonomous AI Database is available across leading hyperscalers, and on-premises through Oracle Cloud@Customer.

While Autonomous AI Database is Oracle's flagship offering, Oracle is also helping customers secure their cloud co-managed and on-premises systems by providing leading security and patching tools for free or highly discounted through the end of February 2027.

Enforcing security and business rules at the data source
When access policies and business rules are enforced only in application code, AI-generated applications may implement them incorrectly, and agents accessing databases directly—such as through an MCP server or natural language to SQL—may bypass them entirely. Oracle Deep Data Security enables organizations to define end-user access rules directly in Oracle AI Database and enforce them on every SQL request. The database itself verifies the user's identity from a cryptographically signed token issued by the corporate directory and determines what the user is allowed to access. Identity management is complemented by Oracle SQL Assertions that enforce business rules in the database—for example, not allowing charges that are above an employee's spending limit—preventing invalid updates, actions, or conflicting changes regardless of which application, end-user, or agent submits them. 

Governing how AI agents and applications access data
Oracle Deep Trust Data APIs provide controlled read and write access to logical business objects, such as purchase orders. In contrast to allowing arbitrary SQL access, applications and agents only work with the objects needed for a task, while the database enforces the rules governing what they can see and change.

For business users asking questions in natural language, Oracle Deep NL2SQL helps AI better understand the request by providing context that combines business knowledge, including an organization's terminology, practices, and metrics, with data knowledge that describes how information is defined and organized. Continuous Feedback Learning enables users to correct inaccurate responses, while Knowledge Change Verification helps ensure corrections are validated before being incorporated into the corporate knowledge base. Together, these capabilities help AI interpret business questions more accurately than traditional NL2SQL solutions and generate SQL that reflects an organization's data and business context.

Building AI-generated applications on a trusted execution engine
Oracle APEX AI Application Generator enables AI coding agents to translate natural-language application descriptions into APEXlang, an open, declarative application definition language. Oracle APEX executes those definitions in its centralized runtime engine which provides enterprise-grade security, scalability, and availability while simplifying ongoing application maintenance and updates. Because AI generates only the application definition, not the code that runs it, organizations can build and evolve applications without having to trust, secure, and maintain huge volumes of AI-generated execution code. Developers can use familiar development environments and tools, including VS Code, Oracle APEX, or any AI coding agent such as Codex.

Just as Oracle's well-known Maximum Availability Architecture gave enterprises a blueprint for keeping mission-critical systems running, Deep Trust AI Architecture gives them a blueprint for putting AI to work on their most important data. Because security, privacy, and business rules are enforced by the platform, the data, and the application runtime, every new agent and application inherits those protections from day one, so organizations can scale AI without scaling risk.

"The enterprise AI race is entering a new phase, and Oracle is shifting the competitive battleground from model intelligence to architectural trust," said Steven Dickens, CEO, HyperFRAME Research. "While much of the industry is still grappling with securing AI agents and governing access to enterprise data, Oracle is addressing these challenges at the source. With Deep Data Security enforcing policies directly in the database and Deep NL2SQL bringing business context, continuous learning, and verification to AI-generated answers, Oracle is fundamentally changing the equation for enterprise AI. What sets the Deep Trust AI Architecture apart is its unified approach to embedding trust into how AI accesses, understands, and acts on enterprise data. Oracle is raising the industry bar by unifying intelligence, security, and governance at the foundation of the agentic enterprise, empowering organizations to innovate faster, scale AI with confidence, and deliver more trusted business outcomes."

Additional Resources

• Read the technical blog about Oracle Deep Trust AI Architecture
• Read what industry analysts are saying about Oracle Deep Trust AI Architecture

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SOURCE Oracle