GenDev Is Here: Build Enterprise-Grade AI Apps Faster
AI no longer feels distant. It's practical, useful, and ready for enterprise AppDev-if you have the right stack. Oracle has announced new generative AI enhancements to Autonomous Database that make building mission-critical applications simpler and faster on Oracle Database 23ai.
This is GenDev: an AI-centric development approach that lets your team focus on functionality rather than infrastructure. Expect faster delivery, natural language interfaces, and smarter use of your existing data.
Build AI-Powered Apps Without Friction
Developers can now connect large language models to enterprise data with fewer moving parts and clearer guardrails. The goal: ship applications your users can trust, backed by your actual data and context.
Bridge AI and Private Data with Select AI + RAG
LLMs trained on public data don't know your business. Retrieval Augmented Generation (RAG) fixes that by feeding relevant facts from your Oracle databases into each response.
- Use built-in AI pipelines to declaratively create and populate vector stores from corporate data.
- Extend SQL to blend vector store content into natural language queries.
- Give prompts enterprise context so results are accurate, consistent, and auditable.
Want a quick primer on RAG? See a concise overview here: Retrieval-Augmented Generation.
Go Beyond Documents with Graph RAG + Graph Studio
Relationships matter. Graph RAG uses document and graph embeddings to reflect how entities, people, and processes connect-so answers carry nuance, not just facts.
- Use Graph Studio (no code required) to build Operational Property Graph models in minutes.
- Enrich retrieval with graph context for better entity disambiguation and reasoning.
Streamline Data Workflows for GenAI
Smart Data Loading
Data Studio guides loading and enrichment end-to-end. It detects languages, extracts content, flags PII, performs sentiment analysis, and surfaces key phrases-so your downstream pipelines run cleaner.
Visual GenAI Pipelines
- Build text and image embedding pipelines visually-store results in a high-performance vector store.
- Query vectors using natural language to speed up exploration and QA.
Synthetic Data for Safer Dev/Test
Skip production snapshots. Generate realistic test data with LLMs, paired with a metadata-only clone of your schema. In a few clicks, spin up a populated, safe environment for development and QA.
Use the AI Stack You Prefer
Autonomous Database keeps your options open. Use OCI Generative AI or connect to providers such as OpenAI, Azure OpenAI, Cohere, Google Gemini, Anthropic Claude, or models available through Hugging Face-then build with simple Select AI APIs.
ONNX Models for Efficient Embeddings
Bring ONNX-formatted models into Autonomous Database to generate embeddings efficiently for Vector Search. This reduces glue code and keeps data closer to compute.
GPU Acceleration for Python in OML Notebooks
- One-click GPU activation by setting your notebook service level to "gpu".
- Speed up embedding generation, deep learning training, and inference with GPU-optimized Python packages.
- Workflows remain seamless-CPU and GPU operations live side by side.
Develop Anywhere: Online or Local
Use Autonomous Database for Developers or the new Developers Container Image to build even if you're offline. Spin up quickly, prototype freely, and upgrade to production when ready.
- Predictable pricing with a fixed-shape serverless instance.
- Full GenDev feature set for experiments, POCs, and iterative development.
- Familiar built-in tools, optimized for developer speed.
Practical Ways to Get Started
- Stand up a dev instance with Autonomous Database for Developers.
- Load core domain data via Data Studio and enable vector embeddings.
- Wire up Select AI with your preferred LLM and start with a simple RAG use case (FAQ, support, or search).
- Add Graph RAG where relationships matter: fraud, supply chain, customer 360, or access control.
- Use synthetic data to populate realistic dev/test environments without touching production.
- Shift compute-heavy Python tasks to GPUs in OML Notebooks for faster iteration.
Where to Learn More
- Explore Oracle Autonomous Database: Product overview
- Try Oracle Free Tier: Get started
Level Up Your Team's AI Skills
If you're building AI-backed products and want structured learning for developers and product teams, browse these resources: AI courses by job role.
Bottom Line
GenDev with Oracle Database 23ai makes enterprise AI development straightforward: connect LLMs to your data, reason over relationships, automate data prep, and scale with flexible infrastructure. Less glue work, more shipped features.
Future Product Disclaimer
The preceding is intended to outline general product direction. It is for information purposes only, not part of any contract. It is not a commitment to deliver any material, code, or functionality. Do not rely on it for purchasing decisions. The development, release, timing, and pricing of any features or functionality described for Oracle's products may change at the sole discretion of Oracle Corporation.
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