What is Cua?
Learn about Cua, the open-source platform for building computer-use agents
Cua is an open-source platform for building, deploying, and managing computer-use agents. It provides everything you need to create AI agents that can interact with desktop environments just like a human would—clicking, typing, navigating, and completing tasks autonomously.
The Cua Stack
Cua consists of three main components:
1. Desktop Sandboxes
Isolated virtual environments where your agents can safely execute tasks. Cua supports:
- Cloud Sandboxes - Managed Linux, Windows, and macOS environments hosted by Cua
- Local Sandboxes - Docker containers, QEMU VMs, macOS VMs via Lume, or Windows Sandbox on your own machine
2. Computer Framework
A unified SDK for controlling desktop environments programmatically:
- Take screenshots and observe the screen
- Simulate mouse clicks, movements, and scrolling
- Type text and press keyboard shortcuts
- Works identically across all sandbox types
3. Agent Framework
Tools for building AI agents that understand and interact with GUIs:
- 100+ vision-language model options through Cua VLM Router or direct provider access
- Pre-built agent loops optimized for computer-use tasks
- Composable architecture for combining grounding and planning models
- Built-in telemetry for monitoring agent performance
Why Cua?
Traditional automation tools require you to write explicit scripts for every action. Cua agents can:
- Understand visual context - See what's on screen and make decisions
- Adapt to changes - Handle UI variations without breaking
- Complete complex tasks - Chain multiple actions to achieve goals
- Work across applications - Navigate between different programs seamlessly
Use Cases
Cua is ideal for:
- Workflow automation - Automate repetitive tasks across any application
- Testing - Run end-to-end tests that interact with real UIs
- Data extraction - Scrape information from applications that don't have APIs
- RPA (Robotic Process Automation) - Enterprise automation with AI understanding
- Benchmarks - Evaluate computer-use agents on standardized tasks (OSWorld, ScreenSpot, etc.)
- RL/Gym Environments - Train reinforcement learning agents with desktop environments as Gym-compatible envs
- Research - Build and evaluate computer-use AI agents
Getting Started
Ready to build your first agent? Continue to Set Up a Sandbox to set up your environment and run your first automation.
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