1. AI Database
  2. Private AI Services Container

Oracle Private AI Services Container

The Oracle Private AI Services Container gives Oracle AI Database customers a private, air-gap-capable, OpenAI-style inference layer that keeps embedding work off the database server while still fitting naturally into Oracle-native workflows. Protect Oracle AI Database performance and keep AI inference inside your security boundary.

Why Oracle Private AI Services Container?

  • Database Offload

    Offload expensive AI computation, such as vector embedding generation or vector index creation. This computation offload can free up compute resources on the Oracle AI Database server.

    Offload

  • Data Privacy

    Your AI data never leaves your realm. You do not need to send your AI data to a 3rd party.  Do not give away your business data for convenience.

    Privacy

  • Secure AI Infrastructure

    Secure local AI services are enabled by applying security best practices and leveraging industry-standard technologies.

    Secure

  • Simple Web Services

    Developers use the popular OpenAI API REST protocol for AI operations. Existing OpenAI SDK clients can use the Private AI Services Container.

    REST API

Key Features of Oracle Private AI Services Container

 

Air Gap Enabled

The Private AI Services Container is a set of web services which are designed to be deployed in your data center. There is no dependency on public clouds or the internet. This design enables the container to run in air gapped environments.

REST APIs

The web services are implemented as a set of REST APIs. These REST APIs implement the OpenAI API to enable common AI operations. Existing OpenAI SDK clients can work with the container, you just need to change the REST endpoint and API key.

Security

All REST traffic is secured with TLS 1.3. Passwords are encrypted and kept in a PKCS12 keystore. Authentication and authorization use API keys. Enforcing mode SE Linux is supported. User data is not stored in the container.

Embedding Models

Six popular embedding models ship with the container. This means that customers can have a system that can be deployed without the extra effort of creating and download other embedding models. If needed, customers can also create and download additional embedding models.

Performance

The Vector Embedding Service uses the ONNX Runtime with multi-threading, enabling better throughput and lower latency on multi-core CPUs. The Vector Index Service uses GPUs to accelerate the creation of vector indexes.

Containerized

Podman, Kubernetes or OpenShift can be used to manage the container. For small deployments, Podman can be used. For larger deployments, Kubernetes or OpenShift can be used.

Available Services

Remote CPU offload

The Private AI Services Container Vector Embedding Service generates vector embeddings

The vectors are created on a container which runs on a remote Linux machine.  This architecture offloads the CPU cost of creating vectors from Oracle AI Database server

The container is a REST server which implements the OpenAI API protocol to create vectors for the /v1/embeddings endpoint

The endpoint, API Key and model name determine the type of vectors that will be created

REST clients include Oracle AI Database 26ai, OpenAI API clients, Postman and curl

Remote GPU Offload

The Private AI Services Container Vector Index Service enables In-Memory Neighbor Graph Vector Indexes to be created faster by using GPU offload

The vector index is created on a container which runs on a remote Linux machine with a GPU.  This architecture offloads the CPU cost of creating vectors from the Oracle AI Database server

The SQL syntax for CREATE VECTOR INDEX can be used to define the REST endpoint and credential for the Private AI Services Container

Most modern NVIDIA GPUs are supported on the Private AI Services Container for vector index offload

Download, Install and Configure the Container

Download the Container

You need to download the container from the Private AI Services Container page on Oracle Container Registry.

To download the container, you need to:

  • Sign-in using your (free) Oracle Account
  • Accept the license for the Private AI Services Container
  • If needed, create an authentication token for Podman
  • Login to Oracle Container Registry using Podman
  • Use Podman to pull the container image from Oracle Container Registry

The details of downloading the container are covered in the documentation.


Install and Configure

Once the container is downloaded, the recommended way to install the Private AI Services Container with Podman is via the install scripts embedded in the container.

The steps to extract the install scripts from the container are covered in the documentation.

The install scripts are used to install and configure the container for secure deployments with HTTP/SSL, API Keys and an encrypted Keystore.

If you want to deploy the Embedding Service container to Kubernetes or OpenShift, use the Oracle Database Operator for Kubernetes via YAML rather than the install scripts.


March 24, 2026

Getting Started with Oracle Private AI Services Container

Doug Hood, Product Manager, Oracle

Following our recent announcement that the Oracle Private AI Services Container is now available on Oracle Container Registry, it’s time to move from “what’s new” to “how it works”. In this post we’ll walk through installing, configuring, and using the container in your own environment.

Link to Blog

Featured Private AI Services Container Blogs

Additional Resources