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• New agentic AI capabilities designed for business data accelerate enterprise innovation and help defend enterprises from AI-era threats;
• Available on all platforms from multicloud to on-premises.
Oracle AI Database architects agentic AI and data together across operational databases and analytic lakehouses. It enables AI agents to securely access real-time enterprise data wherever it resides and easily use business data with LLMs trained on public data to provide business insights. Customers can choose AI models, agentic frameworks, open data formats, and deployment platforms. In addition, customers running on Oracle Exadata further benefit from Exadata Powered AI Search, which enables agentic AI at the highest scale with accelerated AI queries for high-volume, multi-step agentic workloads.
“The next wave of enterprise AI will be defined by customers’ ability to use AI in business-critical production systems to safely deliver breakthrough innovations, insights, and productivity,” said Juan Loaiza, executive vice president, Oracle Database Technologies, Oracle. “With Oracle AI Database, customers don’t just store data, they activate it for AI. By architecting AI and data together, we help customers quickly build and manage agentic AI applications that can securely query and act on real-enterprise data with stock exchange-level robustness in every leading cloud and on-premises.”
Innovate faster with AI designed for data
With agentic AI capabilities architected for data, Oracle AI Database helps eliminate the need to build and maintain data-movement pipelines that add complexity and security risk, and may produce worse outcomes. New capabilities include:
• Oracle Autonomous AI Vector Database provides the simplicity of a vector database with the full power of Oracle AI Database. It enables developers and data scientists to quickly and easily build vector-powered applications using intuitive APIs and an easy-to-use web interface. Built on top of Oracle Autonomous AI Database, it combines an easy-to-use developer experience with enterprise-grade security, reliability, and scalability. Currently in limited availability, Autonomous AI Vector Database is accessible through either the Oracle Cloud free tier, or a developer tier with low-cost pricing. Customers can seamlessly upgrade with one click to the full power of Oracle Autonomous AI Database when their requirements grow, with full support for graph, spatial, JSON, relational, text, and parallel SQL eliminating the need for separate databases and complex cross-database agentic workflows.
• Oracle AI Database Private Agent Factory enables business analysts and domain experts to rapidly build and safely deploy data-driven agents and workflows. The AI Database Private Agent Factory provides a no-code AI agent builder that runs as a container in public clouds or on-premises, maintaining data security by enabling customers to build, deploy, and manage AI agents without having to share data with third parties. AI Database Private Agent Factory includes multiple pre-built AI agents specialized for data, including a Database Knowledge Agent, a Structured Data Analysis Agent, and a Deep Data Research Agent. Other approaches rely on external agent orchestration or must make calls to different types of databases. Oracle has simplified agentic AI for business users by architecting it into its AI Database, providing consistency and simplicity with enterprise-grade security, resiliency and scalability for every agentic workload.
• Oracle Unified Memory Core lets users store context for AI agents in a single system. It uniquely enables low-latency reasoning across vector, JSON, graph, relational, text, spatial, and columnar data in one converged engine, with consistent transactions and security.
Minimize AI data risk
Oracle AI Database helps customers safeguard data from external attacks, insider misuse, accidental disclosure, and unintended exposure to LLMs across multicloud, hybrid, and on-premises environments. New capabilities include:
• Oracle Deep Data Security implements powerful end-user-specific data access rules in the database. Each end-user or AI agent acting on behalf of an end-user can only see the data that the end-user is allowed to see. It can implement sophisticated persona and function-based rules. For example, what parts of a customer account specific sales reps, finance reps, shipping clerks, executives, support reps, and customer relatives are allowed to see. This provides unique end-user data security capabilities to protect against new AI-era threats, such as prompt injection, using declarative, database-native controls that implement least-privilege access. By centralizing and decoupling security from application code, it enables customers to easily determine who can see what data and continuously update access rules as new threats emerge, and it effectively provides guardrails for agents working within Oracle AI Database. Security at the source of the data the database offers superior protection when AI agents directly access data on behalf of end-users.
• Oracle Private AI Services Container enables customers with stringent security requirements to run private instances of AI models while avoiding sharing of data with third-party AI providers, or sending data outside of their firewall. In addition, it helps mitigate performance bottlenecks by allowing customers to securely offload compute-intensive AI tasks, such as vector embedding generation, outside the database, helping keep all data secure within their environment. The container can be deployed in the public cloud, on private clouds, or on-premises, including in air-gapped environments.
• Oracle Trusted Answer Search provides enterprises with an accurate, testable, and deterministic way to use AI to provide answers to end-users. Instead of directly using an LLM to answer an end-user question, Trusted Answer Search uses AI Vector Search to match the question to a previously created report. This helps mitigate the risk that probabilistic LLMs may occasionally hallucinate or misunderstand a query.
End AI data lock-in with open standards and frameworks
Running in all leading cloud providers, in hybrid deployments, and available on-premises, Oracle AI Database gives customers the flexibility to choose the AI model and application-tier agentic framework that best fits their needs. They can build, deploy, and run agentic AI applications using open standards and data formats. New capabilities include:
• Oracle Vectors on Ice provides customers with native support for vector data that is stored in Apache Iceberg tables. AI Vector Search can read vector data directly from Iceberg tables, create vector indexes to accelerate vector search, and automatically update these indexes as the underlying vector data changes. Oracle Vectors on Ice allows AI search on data lake data and enables unified search across business data in the database and vectors stored in a data lake. This enables customers to achieve unified intelligence across databases and data lakes.
• Oracle Autonomous AI Database MCP Server enables external AI agents and MCP clients to securely access Autonomous AI Database and its capabilities without custom integration code or manual security administration. It complements the Oracle SQLcl MCP Server for Oracle AI Database, available via the Oracle SQL Developer VS Code extension.
“In the era of agentic AI, a unified memory core is essential for agents to maintain context across diverse data types, such as vector, JSON, graph, columnar, spatial, text, and relational, without the latency or staleness of external syncing,” said Steven Dickens, CEO and principal analyst, HyperFRAME Research. “Only Oracle AI Database delivers this in a single, mission-critical engine with concurrent transactional and analytical processing, high availability, and ironclad security, enabling real-time reasoning over live business data. Organizations without this foundation will struggle with fragmented, unreliable agents, while those leveraging Oracle gain a decisive edge in scalable AI deployment.”
Customers and developers can leverage the new agentic AI capabilities for Oracle AI Database now, to start developing and deploying game-changing agentic AI applications without moving data, learning new skills, or struggling with database scalability and the lack of agentic AI security guard rails. Learn more details about the latest AI innovations in this Oracle AI Database Agentic AI announcement blog.
About Oracle
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