Deploy a Production-Ready NVIDIA AI-Q Blueprint on Oracle Cloud Infrastructure

2026-06-26 · Source: NVIDIA Technical Blog · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Cloud Computing & IT Infrastructure, Software Development & Engineering · Depth: Intermediate, medium

Summary

The NVIDIA AI-Q Blueprint, an open-source reference for long-horizon AI agents built on LangChain Deep Agents and the NVIDIA NeMo Agent Toolkit, can now be deployed as a production-ready solution on Oracle Cloud Infrastructure (OCI). This guide details deploying AI-Q 2.0, which supports multi-turn chat and complex tasks using an intent router and sub-agents like Shallow Research and Deep Agents. The deployment leverages Terraform to provision OCI resources, including an OKE cluster, Load Balancer, and Vault, and Helm to install the AI-Q backend (FastAPI), frontend (Next.js), and an in-cluster PostgreSQL database on OKE. Prerequisites include OCI tenancy access, NGC and Tavily API keys, and local tools like Terraform 1.5+, kubectl 1.28+, and Helm 3.x+. The process takes 20-25 minutes, resulting in a functional AI-Q endpoint.

Key takeaway

For platform engineers or AI developers seeking to deploy advanced multi-agent AI systems, you can quickly establish a production-ready NVIDIA AI-Q 2.0 environment on Oracle Cloud Infrastructure. This blueprint provides a robust, extensible framework for long-horizon agents, leveraging familiar tools like Terraform and Helm for infrastructure and application management. You should ensure proper OCI service limits and API key configuration to streamline deployment and consider scaling down resources to manage costs between experiments.

Key insights

NVIDIA AI-Q 2.0 offers a production-ready multi-agent AI system deployable on OCI using standard infrastructure-as-code tools.

Principles

• Multi-agent architectures enhance AI task complexity.
• Separate infrastructure from application deployment.
• Extensibility through YAML config and plugin systems.

Method

Deploy AI-Q 2.0 on OCI by configuring Terraform variables, applying Terraform to create OCI infrastructure, then configuring kubectl and Helm to install the AI-Q chart from NGC.

In practice

• Use Terraform for OCI resource provisioning.
• Employ Helm for Kubernetes workload deployment.
• Configure NGC and Tavily API keys for agent functionality.

Topics

• NVIDIA AI-Q Blueprint
• Oracle Cloud Infrastructure
• Multi-Agent Systems
• Terraform
• Helm
• Kubernetes
• LangChain Deep Agents

Code references

• NVIDIA/NeMo-Agent-Toolkit
• oracle-samples/ai-q
• oracle-samples/ai-q

Best for: AI Engineer, MLOps Engineer, Software Engineer

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Editorial summary, takeaway, and curation by AIssential. Original article published by NVIDIA Technical Blog.