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Description

E2B is an open-source runtime that provides a secure environment for executing AI-generated code within isolated cloud sandboxes. This platform allows developers to enhance their AI applications and agents with code interpretation features, enabling the safe execution of dynamic code snippets in a regulated setting. Supporting a variety of programming languages like Python and JavaScript, E2B offers software development kits (SDKs) for easy integration into existing projects. It employs Firecracker microVMs to guarantee strong security and isolation during code execution. Developers have the flexibility to implement E2B on their own infrastructure or take advantage of the available cloud service. The platform is crafted to be agnostic to large language models, ensuring compatibility with numerous options, including OpenAI, Llama, Anthropic, and Mistral. Among its key features are quick sandbox initialization, customizable execution environments, and the capability to manage long-running sessions lasting up to 24 hours. With E2B, developers can confidently run AI-generated code while maintaining high standards of security and efficiency.

Description

Boat delivers robust cloud-based virtual machines and persistent sandboxes specifically designed for managing long-lasting AI agents, empowering users to effortlessly create thousands of cloud instances equipped with web browsers and persistent storage while alleviating the burden of infrastructure management. Each sandbox functions as a comprehensive Ubuntu Linux virtual machine, providing SSH and SCP access, Docker compatibility, dedicated IPv4 or IPv6 addresses, a smooth 60 fps virtual desktop, and rapid disk-level forking capabilities from snapshots. Pre-installed tools such as Docker, VS Code, Chrome, Ghostty, GitHub CLI, Rust, Node.js, and Bun allow users to execute any development language, tool, or workflow seamlessly. Boat is compatible with various agents including Claude Code, Codex, and OpenCode, and it offers functionalities to prompt, observe, and manage agent environments remotely via its command-line interface, HTTP API, and SDKs available in both Python and TypeScript. Users can run commands, transfer files, and monitor agent communications, while also hosting applications accessible through public HTTPS links and utilizing integrated desktops and web browsers for enhanced productivity. This comprehensive solution not only simplifies the management of AI agents but also fosters a more efficient development experience for users across diverse projects.