Uploaded July 2026 | Updated September 2026, 2 weeks ago
Enterprise applications are rapidly evolving with agentic AI, but every AI-driven action depends on one critical foundation: secure access to data.
In this AskTOM session, Paul Parkinson will show how Oracle Deep Data Security helps Java developers and security architects enforce application-level data authorization directly inside Oracle AI Database. With Oracle AI Database 26ai, Deep Data Security provides a strategic framework for protecting enterprise data across cloud and on-premises environments.
This session will combine architecture guidance with hands-on demonstrations and source code examples, including Java integration patterns with OIM, Microsoft Entra ID, Spring Boot, APIs, SPIs, auditing, tracing, transactions, messaging, and other areas relevant to secure agentic AI application development.
Whether you are creating new AI-enabled applications or strengthening existing Java systems, this webinar will help you understand how to design secure, scalable, enterprise-ready data access for the next generation of applications.
Check out the links at github.com/oradbsec/AskTomDBSecurity
Here is a guide to the recording:
01:13 Announcements
04:07 Oracle Deep Data Security - Core Concepts
13:52 Resources for learning more about Oracle Deep Data Security
15:32 Deep Data Security for a Java Developer
28:25 Oracle Deep Data Security with Spring Boot and Entra ID Demo
43:26 Rich admits his ignorance
44:44 Related Agentic AI JDBC topics
47:18 ADK - Google Agent Dev Kit
50:28 Available Resources
Enterprise applications are rapidly evolving with agentic AI, but every AI-driven action depends on one critical foundation: secure access to data.
In this AskTOM session, Paul Parkinson will show how Oracle Deep Data Security helps Java developers and security architects enforce application-level data authorization directly inside Oracle AI Database. With Oracle AI Database 26ai, Deep Data Security provides a strategic framework for protecting enterprise data across cloud and on-premises environments.
This session will combine architecture guidance with hands-on demonstrations and source code examples, including Java integration patterns with OIM, Microsoft Entra ID, Spring Boot, APIs, SPIs, auditing, tracing, transactions, messaging, and other areas relevant to secure agentic AI application development.
Whether you are creating new AI-enabled applications or strengthening existing Java systems, this webinar will help you understand how to design secure, scalable, enterprise-ready data access for the next generation of applications.
Check out the links at github.com/oradbsec/AskTomDBSecurity
Here is a guide to the recording:
01:13 Announcements
04:07 Oracle Deep Data Security - Core Concepts
13:52 Resources for learning more about Oracle Deep Data Security
15:32 Deep Data Security for a Java Developer
28:25 Oracle Deep Data Security with Spring Boot and Entra ID Demo
43:26 Rich admits his ignorance
44:44 Related Agentic AI JDBC topics
47:18 ADK - Google Agent Dev Kit
50:28 Available Resources
