LAS VEGAS — Oracle Corp. launched its AI Data Platform on Tuesday, marking the company’s latest effort to help enterprises integrate generative artificial intelligence (AI) with their existing data infrastructure and business operations.
The platform aims to streamline the process of preparing enterprise data for AI applications by combining automated data ingestion, semantic enrichment, and vector indexing with built-in generative AI capabilities. The technology builds on Oracle’s existing cloud infrastructure, autonomous database services, and generative AI offerings.
“Oracle AI Data Platform enables customers to get their data ready for AI and then leverage AI to transform every business process,” said T.K. Anand, executive vice president at Oracle. He emphasized that the unified approach provides enterprises with “confidence, security, and agility” as they adopt AI technologies.
The platform is designed to serve dual purposes: Enabling business users to access real-time insights and deploy AI agents for task automation, while providing developers and data teams with tools to rapidly build and scale AI applications. The system incorporates NVIDIA Corp.’s accelerated computing infrastructure, allowing users to select the latest GPU generations for demanding workloads.
Alongside the platform launch, Oracle announced AI Database 26ai, which integrates AI directly into core data management functions. The update represents what Oracle calls its AI for Data vision, which embeds AI capabilities throughout the database stack, from vector search to application development and analytics.
Juan Loaiza, executive vice president of Oracle Database Technologies, said the approach “makes ‘AI for Data’ simple to learn and simple to use,” enabling customers to deploy AI insights across operational systems and analytic data lakes.
The database now supports dynamic agentic AI workflows that can combine private enterprise data with publicly available information to generate sophisticated responses and automated actions. Oracle emphasized the system’s flexibility, noting support for Apache Iceberg open table format, Model Context Protocol (MCP), leading large language models, agentic AI frameworks, and ONNX embedding models.
Oracle also introduced its Autonomous AI Lakehouse, combining the company’s autonomous database technology with the Apache Iceberg standard. The platform aims to eliminate traditional tradeoffs between data warehouses and data lakes while breaking down analytic silos.
Çetin Özbütün, executive vice president of Autonomous Database Technologies, highlighted that the lakehouse leverages Oracle’s autonomous database, which currently processes more than 48 billion queries per hour. “We are breaking down the data silos between analytic systems with Iceberg,” Özbütün said, “and enabling customers to access Iceberg data in any platform — operational or analytic — in the cloud or on-premises.”
A new Autonomous AI Database Catalog was also unveiled, described as a “catalog of catalogs” that unifies enterprise data and metadata across multiple platforms and clouds, simplifying data discovery and access.
Mitch Ashley, vice president/practice lead, DevOps and AppDev, at The Futurum Group, called the AI Data Platform the “big announcement of the show.”
“Essentially, their collapsing ingestion, enrichment, vector indexing, and orchestration into one governed stack, tackling the operational mess most companies have,” Ashley said. “And it’s a big swing on agentic with A2A, MCP, and Agent Hub for routing intent across agents. putting them in direct competition with Microsoft, AWS, and Anthropic. Their governance and open format story (Delta, Iceberg, Zero-ETL), along with multicloud orchestration, and vertical packaging for Fusion and NetSuite, and this starts to look like Oracle’s own data-driven orchestration layer for enterprise AI. It feels like Oracle finally has a sharper AI platform play.”
