What's New for Oracle AI Data Platform Workbench

Here’s an overview of new features and enhancements in Oracle AI Data Platform Workbench.

Topics

For the latest Oracle AI Data Platform Workbench news, product updates, customer and partner stories, and market insights, see https://blogs.oracle.com/ai-data-platform/.

August 10, 2026

Feature Description
Preview: Track the relations of data artifacts through Lineage Lineage lets you visually trace the relationships between data artifacts in your AI Data Platform Workbench instance. You can choose a specific artifact and view upstream and downstream relations. See Lineage (Preview).

July 6, 2026

Feature Description
Create AI Agents to help develop and manage your data You can now create AI agents in AI Data Platform Workbench, either through the visual flow builder or through code. See AI Agents.
Power your Agents with AI Compute AI agents require specialized compute to power their tools and skills. You can create AI compute through Compute in your AI Data Platform Workbench instance. See AI Compute.
Store documents and search documents in Knowledge Bases Knowledge bases let your store and search documents in AI Data Platform Workbench, using Oracle Database 26ai Vector Search capability to store vector embeddings. AI agents can use these knowledge bases to perform semantic searches and retrieve relevant data and documents. See Knowledge Bases.

June 5, 2026

Feature Description
Connect to data in your AI Data Platform from your IDE The Oracle AI Data Platform (AIDP) Developer Extension is now available to install from the Microsoft Visual Studio Code marketplace. Browse workspaces and catalogs, remotely preview, compare, download and upload files, and more. See Oracle AI Data Platform (AIDP) Developer Extension.

May 1, 2026

Feature Description
Choose customer-managed key encryption When creating your AI Data Platform Workbench instance you can now choose to use Oracle-managed key encryption or use your organization's managed key encryption. See Storage Encryption Options.
Enable network source-based access control Create sets of defined IP addresses that you can reference in policies or authentication settings to control access. See Network Sources.
AI Data Platform Workbench REST API Reference Documentation for AI Data Platform Workbench REST APIs is now available. See REST API for Oracle AI Data Platform Workbench.
Preview: Manage credentials in with secrets and vault references The Credential Store provides a secure and centralized way to manage sensitive information such as authentication tokens and external credentials. Instead of embedding secrets directly in configurations or code, users can store and reuse them safely through their AI Data Platform Workbench. See About Credential Store.
Preview: Connect and manage your data in Git You can now manage your Git files entirely from within AI Data Platform Workbench, with utilities that allow you to push, pull, commit, and merge files as well as manage any merge conflicts that arise without having to leave the platform. See Git Integration (Preview).
Preview: Package and deploy bundles from Git folders Bundles allow you to package resources in a Git folder, like those requires for jobs or agents, and deploy those packages across workspaces and environments to share those resources. See Bundles and CI/CD (Preview)
Preview: Run and iterate experiments to build models based on your data Experiments in AI Data Platform Workbench provide means for data scientists, machine-learning engineers, and managers to collaborate in the development of models. See Experiments (Preview).
Preview: Create and train machine-learning models Machine-learning models in AI Data Platform Workbench enable you to build optimized models through performance analysis, collaboration, and analysis of experimental conditions like hyper-parameters, input datasets, and feature engineering. See Models (Preview).
Preview: Administration Settings Administration settings let manage your linked Git accounts. See Administration Settings (Preview).