E2B
Secure cloud sandboxes for running AI-generated code safely.
About E2B
E2B is an open-source infrastructure platform that provides secure, isolated cloud environments for AI agents and applications to execute code. The platform runs on Firecracker microVMs and allows developers to securely execute AI-generated code in Python, JavaScript, Ruby, and C++ without exposing their infrastructure to risk. E2B is designed specifically for enterprise-grade agentic workflows and is used by 94% of Fortune 100 companies. The platform supports various use cases including deep research agents, data analysis, coding agents, and computer use applications. One limitation is that custom advanced features and self-hosted deployments require enterprise agreements, which may not be suitable for smaller organizations or individual developers with limited budgets.
At a glance
- Company
- FoundryLabs, Inc.
- Platforms
- Web, API, Node.js, Python
- API
- Available
- Integrations
- OpenAI, Anthropic, Mistral, Llama, LangChain, LangGraph, Vercel, Firecrawl
- Last verified
- June 2026
Who It's For
- •Enterprise companies building AI agents and agentic applications
- •AI startups developing code-executing AI systems
- •Development teams needing secure code execution environments
- •Researchers using reinforcement learning and model training
- •Organizations requiring compliance and security-focused AI infrastructure
How It Works
- 1Sandboxes are powered by Firecracker, a lightweight microVM designed to run untrusted workflows securely
- 2When code is executed, it runs in an isolated environment completely separated from other sandboxes
- 3Sandboxes can start in 80ms with no cold starts for optimal performance
- 4The platform provides full system customization through template creation or package installation
- 5Sandboxes can run for up to 24 hours for extended agentic workflows
How to Use E2B
- 1Install the E2B SDK for your preferred language (Node.js, Python, etc.)
- 2Create a sandbox instance using the SDK (e.g., Sandbox.create())
- 3Execute code within the sandbox using methods like runCode()
- 4Access outputs, files, and error inspection from the sandbox execution
- 5Customize sandbox templates or install packages for specific requirements
Key Features
- •LLM-agnostic compatibility with OpenAI, Anthropic, Mistral, Llama, and custom models
- •Support for multiple programming languages: Python, JavaScript, Ruby, C++
- •80ms startup time with no cold starts
- •Up to 24-hour long-running sessions
- •Package installation and system library customization
- •Terminal access for executing commands
- •Browser support for web-based workflows
- •Error inspection and debugging tools
- •File save and upload capabilities
- •BYOC (Bring Your Own Cloud) deployment options for AWS, GCP, Azure
Use Cases
- •Deep research agents that conduct time-consuming research on large datasets
- •AI data analysis and visualization with secure data exploration
- •Coding agents that execute code, use I/O, access the internet, and run terminal commands
- •Computer use applications providing secure virtual computers for LLMs
- •Reinforcement learning with thousands of concurrent sandboxes for reward function evaluation
Pros & Cons
Advantages
- •Used by 94% of Fortune 100 companies, demonstrating enterprise-grade reliability and trust
- •Industry-leading 80ms startup time with no cold starts enables real-time agentic workflows
- •Complete LLM agnosticism allows seamless integration with any AI model without vendor lock-in
- •Firecracker-based microVM isolation provides superior security for running untrusted AI-generated code
Disadvantages
- •Self-hosted and on-premises deployments require enterprise agreements, limiting accessibility for smaller teams
- •Advanced customization features like BYOC are restricted to Pro tier or higher plans
- •Limited public information about pricing for different tiers may require contacting sales
Alternatives
See all E2B alternatives →- Beam Cloud
- AirOps
- AWS Lambda
- Docker containers with custom sandboxing
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Frequently Asked Questions
What is E2B?
E2B is an open-source infrastructure platform that provides secure, isolated cloud environments for AI agents and applications to execute code. The platform runs on Firecracker microVMs and allows developers to securely execute AI-generated code in Python, JavaScript, Ruby, and C++ without exposing their infrastructure to risk.
How much does E2B cost?
E2B uses custom pricing — contact the vendor for a quote.
Is E2B free?
E2B is a paid tool and does not offer a free plan.
What are the best E2B alternatives?
Popular E2B alternatives include Beam Cloud, AirOps, AWS Lambda.
What is E2B used for?
E2B is commonly used for Deep research agents that conduct time-consuming research on large datasets, AI data analysis and visualization with secure data exploration, Coding agents that execute code, use I/O, access the internet, and run terminal commands.
Does E2B have an API?
Yes, E2B offers an API for developers.
What platforms does E2B support?
E2B is available on Web, API, Node.js, Python.
Information Accuracy
Please note: While we regularly update all tool information including descriptions, features, pricing, and other details, this information may change over time as tools evolve and update their offerings. For the most current and accurate information, we recommend visiting the official website directly. Our goal is to provide you with comprehensive and up-to-date information to help you make informed decisions.