en.Wedoany.com Report on Mar 25th, Oracle recently announced new Agent AI innovation capabilities for its Oracle AI Database, designed to help customers quickly build, deploy, and scale secure Agent AI applications for production workloads. The Oracle AI Database co-designs Agent AI with data within operational databases and analytical lakehouses, enabling AI agents to securely access real-time enterprise data regardless of its storage location, and to utilize business data with large language models to provide insights. Customers can flexibly choose AI models, agent frameworks, open data formats, and deployment platforms. Customers running on Oracle Exadata can also benefit from Exadata-powered AI search, accelerating queries and supporting large-scale agent workloads.
Juan Loaiza, Executive Vice President of Oracle Database Technology, stated: "The next wave of enterprise AI will be defined by customers' ability to securely use AI in critical production systems to drive innovation and enhance productivity. With the Oracle AI Database, customers aren't just storing data; they are activating data for AI. By architecting AI and data together, we help customers quickly build and manage Agent AI applications that can securely query real-time enterprise data, are highly robust, and suitable for mainstream cloud and on-premises environments."
New features include the Oracle Autonomous AI Vector Database, which offers the simplicity of a vector database alongside the full capabilities of the Oracle AI Database, enabling developers to rapidly build vector-driven applications. The Oracle AI Database Private Agent Factory allows business analysts to build and deploy data-driven agents without code while maintaining data security. The Oracle Unified In-Memory Core supports storing AI agent context in a single system for low-latency inference.
To minimize AI data risks, Oracle Deep Data Security enforces end-user-specific access rules within the database, protecting against new threats like prompt injection. The Oracle Private AI Service Container enables customers to run private instances of AI models, avoiding data sharing. Oracle Trusted Answer Search uses AI vector search to match questions with reports, reducing the risk of large language model hallucinations.
Through open standards and frameworks, the Oracle AI Database supports customers in choosing AI models and agent frameworks and building applications using open data formats. Oracle Vectors on Ice provides native support for vector data in Apache Iceberg tables, enabling unified search across databases and data lakes. The Oracle Autonomous AI Database MCP Server allows external agents to securely access database functionality.
Steven Dickens, CEO of HyperFRAME Research, commented: "In the era of Agent AI, the unified in-memory core is crucial for maintaining context across data types. Only the Oracle AI Database provides this within a single engine, with high availability and security, enabling inference on real-time business data. Organizations leveraging Oracle gain an advantage in scalable AI deployments."
Customers and developers can now leverage the new Agent AI capabilities of the Oracle AI Database to develop and deploy Agent AI applications without moving data or learning new skills. Oracle offers a suite of integrated applications and infrastructure within Oracle Cloud.
