Oracle Corporation (NYSE:ORCL) introduced a range of new artificial intelligence features for its Oracle AI Database platform aimed at helping enterprises develop and deploy AI-driven applications that can interact with live business data.
The announcement was made during the Oracle AI World Tour event held in London on March 24, 2026. Among the updates is the Oracle Autonomous AI Vector Database, which delivers vector database functionality combined with enterprise-level security and scalability.
Oracle also revealed the Oracle AI Database Private Agent Factory, a tool that allows business users to create AI agents through a no-code interface. These agents can run in containers across public cloud environments or within on-premises infrastructure. The platform also includes several ready-made AI agents designed for tasks such as database knowledge queries, structured data analysis and research.
In addition, the company launched Deep Data Security, a system that introduces user-specific access controls within the database to prevent unauthorized data access. The framework allows different categories of users — such as sales staff or executives — to access only the information they are permitted to view.
Another new capability, the Private AI Services Container, enables organizations to run AI models in a private environment without sharing data with external providers. Oracle Trusted Answer Search offers an approach to AI-driven question answering by linking user queries to previously generated reports instead of relying entirely on large language models.
Further updates include Oracle Vectors on Ice, which enables support for vector data stored in Apache Iceberg tables, and the Autonomous AI Database MCP Server, which allows external AI agents to interact with the platform.
“The next wave of enterprise AI will be defined by customers’ ability to use AI in business-critical production systems,” said Juan Loaiza, executive vice president of Oracle Database Technologies.
Oracle said the new capabilities are available across its cloud, hybrid and on-premises deployment options. The company added that the features are designed to integrate with existing enterprise data systems without requiring data migration or additional infrastructure.