Oracle Pushes Unified Database to Give AI Agents Business Context
Generic AI models lack knowledge of a company's operations, customers and financial metrics. Oracle is positioning its converged database platform as the solution, embedding AI agents with enterprise data to execute real transactions.
Off-the-shelf AI models can generate SQL queries, yet they remain ignorant of how a particular organization manages orders, tracks customers or calculates revenue. Oracle Database is now attempting to equip AI agents with the business intelligence needed to resolve bottlenecks in order processing and other workflows.
This evolution introduces fresh challenges around system complexity, vendor dependency and data safety when AI agents gain the ability to modify live business transactions. Oracle's proposed solution centers on a unified database architecture that consolidates vectors, graphs, documents and transactional data within a single system, according to Hasan Rizvi, executive vice president of product and research, database engineering, at Oracle.
If you ask a generic AI assistant, you get a generic answer. If you ask an AI assistant that knows your business, you get a much better answer. Where is the stock? How can I fix the transaction? How can I expedite the delivery?
Hasan Rizvi, Oracle
Rizvi shared these remarks during an exclusive conversation with theCUBE Research's Dave Vellante at Oracle AI World, broadcast through theCUBE, SiliconANGLE Media's livestreaming platform. The discussion centered on database convergence strategies and the protective measures required for AI agents operating within enterprise systems.
Convergence over specialized databases
Artificial intelligence enables teams to rapidly deploy applications and associated data infrastructure, turning data fragmentation into a widespread organizational challenge. While some argue for purpose-built databases tailored to specific workloads, Rizvi contends that novel data types constructed within Oracle's engine automatically inherit decades of proven reliability, protection and performance characteristics.
We've been working on this engine for 40 years, which is highly available, highly secure, highly scalable, highly performant. If you build a new data type or a new workload in the same engine, you get all that benefit, multiple decades' worth of investment.
Hasan Rizvi, Oracle
Flexibility represents the complementary element of Oracle's strategy. The platform operates in on-premises environments, via Oracle Cloud@Customer and across multiple public cloud providers. During the conference, Oracle announced expanded support for Iceberg within its Autonomous AI Lakehouse offering, Rizvi noted.
Security emerges as the domain where AI introduces the most significant risk elevation. Oracle's Deep Data Security mechanism establishes access controls at the database layer itself, ensuring that user identity accompanies every transaction initiated by an AI agent or automatically generated application.
https://www.youtube.com/embed/QABxptzK5WA?feature=oembed
Before, it took a lot of time and effort to find vulnerabilities to exploit them. Now, with AI, it's made it very easy to reverse engineer fixes for attackers to attack.
Hasan Rizvi, Oracle