Releases

Oracle expanded guardrails to moderate image inputs and support version pinning.

Oracle announced B300 GPU availability and additional model options for U.S. government regions.

Oracle released production-grade enterprise agents within OCI Generative AI.

Oracle added private agent creation, lakehouse vectors and secure agent connectivity across its AI Database portfolio.

Oracle introduced an MCP server for secure agent access to Autonomous AI Database.

Oracle added native vector indexing and search over Apache Iceberg tables.

Oracle introduced a no-code system for building private agents in cloud or on-premises environments.

Oracle introduced a developer-focused vector database built on Autonomous AI Database.

Oracle announced new embedded agents across finance, HR, supply chain, sales, marketing and service.

Oracle introduced a marketplace for validated partner-built Fusion application agents.

Oracle expanded its AI infrastructure roadmap to multi-gigawatt clusters and hundreds of thousands of GPUs.

Oracle unveiled its resilient low-latency networking fabric for very large GPU clusters.

Oracle announced a multi-gigawatt AI supercluster architecture targeting up to 800,000 NVIDIA GPUs.

Oracle added an in-database framework for building agents grounded in enterprise data.

Oracle launched an Apache Iceberg-compatible autonomous lakehouse for AI and analytics across clouds.

Oracle released its AI-native flagship database generation with integrated agentic and vector capabilities.

Oracle opened beta access to Google Vertex AI through OCI Generative AI.

Oracle committed to operate and expand large-scale AI infrastructure for OpenAI's Stargate program.

Oracle launched tools to build, extend, test, deploy and manage agents for Fusion Applications.

Oracle disclosed a broad portfolio of embedded role-based agents across Fusion applications.

Oracle introduced a generative-AI clinical workflow and documentation agent.

Oracle released a managed retrieval-augmented generation and enterprise-agent service.

Oracle introduced a natural-language assistant for exploring and explaining enterprise analytics.

Oracle expanded its analytics platform with AI-generated insights and application-aware data models.

Oracle integrated HeatWave GenAI and vector processing with multicloud lakehouse data.

Oracle expanded AutoML with larger models, topic modeling, drift detection and improved anomaly detection.

Oracle expanded HeatWave from analytics and AutoML into an integrated generative-AI platform.

Oracle released automated in-database vector creation, storage and retrieval for HeatWave.

Oracle released in-database LLMs, automated vector storage and natural-language chat in HeatWave.

Oracle made its voice-first clinical assistant available for healthcare workflows.

Oracle announced a generative coding assistant optimized for Java, SQL and OCI development.

Oracle expanded natural-language-to-SQL and retrieval capabilities for Autonomous Database.

Oracle repositioned its flagship database around integrated AI for enterprise data.

Oracle released native vector generation, indexing and semantic similarity search alongside SQL.

Oracle released Database 23ai with integrated vector search and AI-focused developer capabilities.

Oracle introduced a cloud platform combining clinical, claims and operational data with analytics and AI.

Oracle expanded managed extraction and classification for documents within OCI AI Services.

OCI released dedicated clusters for fine-tuning and hosting foundation models.

Oracle made its managed generative-AI service generally available with Cohere and Meta Llama models.

Oracle began embedding generative-AI capabilities into Fusion Cloud application workflows.

Oracle introduced large RDMA-connected NVIDIA GPU clusters for distributed model training.

Oracle announced a voice-first generative-AI assistant for clinical documentation and workflows.

Oracle announced a managed generative-AI service developed with Cohere for enterprise use cases.

Oracle expanded bare-metal GPU instances and high-performance networking for large AI training workloads.

Oracle introduced a portfolio of managed AI APIs spanning language, speech, vision, anomaly detection and forecasting.

Oracle launched a managed collaborative environment for building, training and deploying machine-learning models.

Oracle launched a multi-skill enterprise digital assistant using natural-language understanding and machine learning.

Oracle released the first Autonomous Database cloud service, powered by machine-learning automation.

Oracle unveiled a self-driving database cloud using machine learning for tuning, patching, security and operations.

Oracle introduced the infrastructure platform that became OCI, later forming the base for its managed AI services and GPU cloud.