Cua.ai

Cua is the definitive framework for developing, deploying, and scaling computer-use AI agents (CUAs). It solves the fundamental complexity and security risks associated with agents that interact directly with the operating system by providing secure, containerized sandboxes. Cua empowers developers and enterprises to build robust, screen-reading AI automation across macOS, Windows, and Linux applications, ensuring production-ready performance and unmatched security.

Key Features

Cua provides a unified interface and comprehensive tooling, allowing you to move beyond simple scripting to deploy fully autonomous AI assistants that perceive and control any application using vision-language models (VLMs).

🛡️ Secure Containerized Execution

Traditional agent setups risk compromising your host machine. Cua eliminates this threat by running all automation within isolated environments, leveraging local sandboxes on Apple Silicon, Docker containers, or cloud-powered virtual machines. This guarantees enhanced security and privacy, allowing agents to manipulate complex applications like Photoshop or Amazon Seller Central without affecting your primary operating system.

🌍 Cross-Platform Automation Framework

Develop once and deploy across the major operating systems your business relies on. Cua supports native virtualization for macOS, along with managed Linux and Windows cloud environments. This capability is crucial for organizations needing to automate processes that span multiple platforms and proprietary software.

⚙️ Unified Agent SDK and Tooling

The Cua Agent SDK simplifies the entire development lifecycle. You gain access to structured outputs, multi-turn conversation handling, trajectory tracing, and built-in budget management. This allows developers to focus on agent logic, knowing that complex infrastructure, LLM integration (via liteLLM), and environment setup are managed automatically.

🧠 Integrated Benchmarking and RL Training

Move from concept to reliable production deployment with data-driven insights. Cua includes a comprehensive benchmark suite to measure agent performance against standardized tasks, helping you identify and resolve bottlenecks. Furthermore, built-in tools for Reinforcement Learning (RL) training allow you to automatically optimize agent behavior through trial and feedback, dramatically accelerating iteration cycles.

Use Cases

Cua agents are designed to handle multi-step, complex workflows that require visual perception and precise interaction across standard applications—tasks previously only manageable by human operators.

1. Automated Creative Asset Repurposing: Deploy an agent to manage complex graphic design tasks. For instance, an agent can open an image in Photoshop, use the "Select People" feature, isolate a subject, move the subject to a new background image, and save the final output under a new filename—all without needing specialized API access to Photoshop’s internal tools.

2. E-commerce Listing and Inventory Management: Automate the exhaustive process of listing new products on platforms like Amazon Seller Central. An agent can launch a browser, navigate the complex Seller Central interface, input product details, handle dimension and pricing fields, manage required certifications, and submit the listing, ensuring all mandatory fields are correctly populated.

3. Enterprise Robotic Process Automation (RPA) at Scale: Organizations can use Cua’s cloud sandboxes to run thousands of concurrent automation tasks—such as processing invoices across legacy Windows software, extracting data from PDF documents on Linux servers, or managing internal ticketing systems—without requiring constant infrastructure oversight or manual intervention.

Why Choose Cua?

When building robust computer-use agents, Cua offers functional advantages that ensure scalability, security, and developer efficiency.

• Security by Design: Unlike agents that run directly on your host machine and risk unintended actions (like deleting files or installing malware), Cua's containerization ensures that even if an agent misbehaves, it is instantly contained and isolated, protecting your critical data and system stability.

• Performance Optimized for Apple Silicon: Cua has been engineered to leverage the power and efficiency of Apple M-series chips for local development environments, providing blazing-fast performance for agent testing and iteration.

• Managed Cloud & VLM Inference: Cua Cloud handles infrastructure management and resource scaling, allowing you to run unlimited sandboxes via a simple API. You also get access to over 100 vision-language models (VLMs) from top providers through a single API key, complete with smart auto-routing to balance performance and cost for every task.

• Commitment to Open Source: The core Agent SDK, Computer SDK, and virtualization components are open source, fostering community contribution and allowing for transparent inspection and integration into existing developer stacks.

Conclusion

Cua provides the secure, scalable, and sophisticated infrastructure required to move computer-use AI agents from research prototypes to reliable, production-ready automation tools. If you are serious about deploying autonomous agents that can truly interact with any application, Cua offers the stability and control you need.

Explore the documentation today to learn how Cua can transform your automation workflows.