AI Is Changing How Applications Get Built
Oracle has introduced an AI-first application development stack designed to let developers spend more time on what the app should do and less time wrestling with complex data plumbing. Built on Oracle Database 23ai, this approach brings AI-native capabilities into the heart of the database so teams can build robust applications that work hand in hand with modern AI. It also streamlines how data gets integrated, using natural language interfaces and human-friendly data standards to move from idea to implementation with fewer handoffs and fewer hurdles.
Generative Development, Explained
Generative development (GenDev) marks a shift in how enterprises plan, build, and ship software. Instead of stitching together separate tools and custom glue code, GenDev draws on capabilities in Oracle Database 23ai—such as JSON Relational Duality Views and AI Vector Search—to simplify the hard parts. Developers can assemble modular components quickly while still meeting enterprise requirements around scalability, reliability, and security. The result: faster iteration, cleaner architecture, and less friction from prototype to production.
What Developers Get, Right Away
With Oracle Autonomous Database as the foundation, the development experience comes with features aimed squarely at productivity. A notable example is Select AI with retrieval-augmented generation (RAG). By grounding large language model responses in relevant data, it reduces the odds of incorrect or off-target answers and helps queries return results that track more closely to the source. In practical terms, that means fewer custom pipelines to design and fewer experts needed just to wrangle AI output—the system shoulders more of the load.
Use the Large Language Models You Prefer
Organizations can plug advanced large language models such as Google Gemini and Anthropic Claude into their applications. Because Oracle provides multiple integration points, teams have room to choose what fits their use case, their standards, and their pace. That flexibility helps companies make the most of generative AI without boxing themselves into a single path.
GPU Power, Without the Headaches
Oracle’s infrastructure now supports NVIDIA GPUs to accelerate AI-related workloads. The aim is straightforward: speed up the heavy lifting and reduce the operational hassle of managing GPU resources on your own. Developers can keep their focus on building features while the platform handles the performance layer underneath.
Data Workflows, Simplified
New data management enhancements make it easier to prepare, load, and organize data. Using intuitive, visual tools—including drag-and-drop flows—developers can assemble AI pipelines that include both text and image vector embeddings. Those same tools make common tasks feel lighter: adjust a step, swap a component, or rerun a pipeline, and move on. Folding AI models into existing workflows becomes more straightforward and less brittle.
No-Code Property Graphs for Faster Prototypes
Teams can now create Operational Property Graph models without writing code, using self-service tools built into Oracle Database 23ai. This encourages collaboration between developers, data engineers, and analysts, and it shortens the time from a rough idea to a working prototype. Iterate, test, refine—then repeat, with fewer blockers in the way.
Predictable, Cost-Effective Options for Teams of Any Size
Oracle Autonomous Database for Developers offers advanced capabilities at a predictable, cost-effective rate. The hourly pricing makes it possible to build, test, and then move to production without a large up-front commitment. That predictability also helps smaller teams adopt state-of-the-art database services and grow on their own timeline.
About Oracle
Oracle provides comprehensive suites of applications and secure, autonomous infrastructure in the Oracle Cloud ecosystem. To learn more about Oracle and explore their offerings, visit oracle.com.
Frequently Asked Questions
What does “generative development” (GenDev) mean in this context?
GenDev is Oracle’s approach to building applications with AI woven into the core. It uses capabilities in Oracle Database 23ai so developers can focus on functionality while the platform streamlines data handling and AI integration.
Which Oracle Database 23ai features help speed up development?
Key features include JSON Relational Duality Views and AI Vector Search. Together, they make it easier to model data, work with modern AI patterns, and build modular applications that meet enterprise standards.
How does Select AI with RAG improve accuracy?
Select AI with retrieval-augmented generation grounds model outputs in relevant data. That reduces the risk of incorrect responses and cuts down on the need to handcraft complex AI pipelines.
Can I bring my preferred LLMs and use GPUs?
Yes. You can integrate large language models such as Google Gemini and Anthropic Claude, and you can tap NVIDIA GPUs to accelerate AI-heavy tasks while easing resource management.
How is Oracle Autonomous Database for Developers priced?
It’s offered at a predictable hourly rate, giving teams a cost-effective path from development to full production without high up-front costs.
