Oracle has introduced new agentic artificial intelligence features for its AI Database and launched Fusion Agentic Applications, extending its push to embed AI more deeply into business data and enterprise software.
The database update is aimed at customers building AI agents that work directly with operational and analytical data. The Fusion launch targets business users in finance, human resources, supply chain and customer management. The new software is designed to let organisations run AI-driven processes inside existing systems rather than through separate tools.
Database update
Oracle has added tools to help customers build and run agentic AI applications without moving data into external systems. The approach combines AI and data in the same environment across operational databases and analytic lakehouses, allowing AI agents to access real-time enterprise data where it already sits.
Among the additions is Oracle Autonomous AI Vector Database, which gives developers and data scientists a way to build vector-based applications through application programming interfaces and a web interface. The product is currently in limited availability and can be accessed through Oracle’s cloud free tier or a lower-cost developer tier, with an upgrade path to the broader Autonomous AI Database.
Oracle also introduced AI Database Private Agent Factory, a no-code tool for building and deploying data-driven AI agents and workflows in public clouds or on-premises environments. It is intended to let customers create and manage agents without sharing data with third parties. It includes pre-built agents for database knowledge, structured data analysis and deeper data research.
Another new component, Oracle Unified Memory Core, is designed to hold AI agent context in a single system across vector, JSON, graph, relational, text, spatial and columnar data. Oracle said this should reduce latency and remove the need for external synchronisation across different data stores.
Security focus
Oracle framed much of the database launch around security and data control. New features include Oracle Deep Data Security, which applies end-user-specific access rules inside the database so users, and AI agents acting on their behalf, can only see the data they are authorised to view.
The feature is intended to counter risks such as prompt injection and unintended data exposure by putting access controls at the database level rather than in application code. Oracle also launched Oracle Private AI Services Container, which lets customers run private instances of AI models in public cloud, private cloud or on-premises environments, including air-gapped settings.
Oracle Trusted Answer Search was presented as another safeguard. Rather than relying on a large language model to generate an answer directly, the tool matches user questions to previously created reports using vector search in an effort to reduce hallucinated or inaccurate responses.
Oracle also added features aimed at open standards and interoperability. Oracle Vectors on Ice supports vector data stored in Apache Iceberg tables, while Oracle Autonomous AI Database MCP Server is intended to give external AI agents and clients secure access to the database without bespoke integration work.
“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 of Oracle Database Technologies at 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.”
Steven Dickens, an analyst at HyperFRAME Research, said Oracle’s use of a single system for multiple data types addressed a core issue in agentic AI deployments.
“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 Dickens, CEO and principal analyst at 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. Organisations without this foundation will struggle with fragmented, unreliable agents, while those leveraging Oracle gain a decisive edge in scalable AI deployment.”
Applications layer
Alongside the database changes, Oracle launched Fusion Agentic Applications, which it described as a new class of enterprise applications built into Oracle Fusion Cloud Applications. The software uses groups of specialised AI agents to make and execute decisions inside business processes while drawing on enterprise data, workflows, approval structures and permissions.
Oracle said the applications differ from AI assistants and add-on tools because they sit inside the transactional system itself, allowing them to act in real time with governance controls already in place. They are designed to progress routine work within guardrails and refer exceptions or trade-offs to people when human judgement is needed.
There are 22 Fusion Agentic Applications available at launch. Oracle highlighted examples including a Workforce Operations Agentic Application for scheduling and payroll issues, a Design-to-Source Workspace Agentic Application for sourcing and engineering decisions, a Cross-Sell Program Workspace Agentic Application for sales teams and a Collectors Workspace Agentic Application for cash collection.
“The way work gets done no longer matches the speed, complexity, or expectations of modern business as too much time is spent managing processes instead of driving outcomes,” said Steve Miranda, executive vice president of applications development at Oracle.
“With Fusion Agentic Applications, we are moving enterprise software beyond passive systems of record and providing our customers with applications that can reason, decide, and act in pursuit of defined business objectives. This is a huge step forward for the industry and will help our customers achieve faster outcomes, focus their valuable time on strategic activities, and redefine how work works.”
Industry analysts said the announcement points to a broader shift from AI assistants to software that can execute multi-step work inside core business systems.
“The introduction of Oracle Fusion Agentic Applications represents a meaningful shift in enterprise software by moving beyond task automation to outcome-driven execution on the journey to an autonomous enterprise,” said Mark Smith, chief AI and software analyst at ISG.
“As organisations look to scale automation across their business, having a platform that can coordinate agents across functions while keeping security and approvals inside the application suite will be an important differentiator.”