Welcome to Oiy AI
Simple, container-level elastic GPU compute. Deploy, scale, and pay for usage.
Oiy AI is a simple, easy-to-use container-level elastic GPU computing service. Bring a container image, set a command and environment, choose GPU resources, and run. Scale resources through one workflow, scale idle compute to zero, and pay for usage.
The workflow is Docker-like: image, command, environment, and a persistent mount. Learn how elastic containers work, then deploy your first service.
01 / Run your first service ↗
Move from a verified account to a configured workspace.
02 / Choose your compute ↗
Understand GPU profiles, CPU resources, and placement.
03 / Keep your work ↗
Learn what persists, what is billed, and what deletion removes.
04 / Build with your tools ↗
Use the HTTP API, Python SDK, CLI, or an MCP client.
How the pieces fit
A service is an elastic container workload with a resource allocation, a persistent workspace, optional HTTP access, and a lifecycle you control. A volume stores the files you want to keep. A template is a reusable starting configuration.
You select a region tier (Standard or Low-price) separately from geography (North America, Oceania, or Automatic). The live catalog determines which combinations can actually be deployed.
A practical learning path
- Complete the quickstart.
- Read about service lifecycle, compute, and storage.
- Configure HTTP endpoints and idle sleep.
- Automate through the API, Python SDK, or MCP server.
Read the preview boundaries before planning a production dependency.