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Oxygen OS is the operating system for AI transformation. Oxygen has three components: Data Infrastructure, World Model, and Agentic Intelligence. With Oxygen, organizations can build a digital twin of their operations and deploy custom Applications and Agents that power complex workflows and decisions. Oxygen establishes a structured workflow for agents, involving agent creation, prompt testing, and production deployment. banner Specifically, this process is implemented as follows:
  • Agent Configuration: Define agents using .agentic.yml files that specify their instructions. Agents are provided tools to generate SQL, execute semantic queries, and execute procedures.
  • Procedure Development: Create .procedure.yml files to orchestrate multi-step processes. Use retrieve: include and exclude to control how these procedures are retrieved by agents that have access to them.
  • Testing Framework: Add test cases directly to .agentic.yml or .procedure.yml files. Execute tests using the oxy test command.
You can interact with all components — agents, procedures, and data — through the web interface launched by oxy start. Oxygen is also CLI-native, so every operation can be run from the terminal, making it easy to integrate with coding tools like Claude Code and CI/CD pipelines.

Who should read what?

The documentation is split into two audiences: End users — data analysts, business users, and developers who use Oxy to query data, build agents, and create workflows. Start here:

Quickstart

Install Oxy and run your first query in minutes

Core Concepts

Agentic workflows, semantic layer, data apps

Basic Oxy commands

CLI reference for running and testing agents
Operators — DevOps engineers, platform teams, and self-hosters who deploy and configure the Oxy server. Start here:

Deployment Overview

Deploy Oxy on cloud, Docker, or Kubernetes

Deployment Modes

Multi-workspace vs single-workspace mode

Authentication

Magic link, Google OAuth, Okta SSO

GitHub App Setup

Enable GitHub workspace import