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About
E2B (short for "Environment to Build") is an enterprise AI agent cloud platform that gives AI agents access to secure, sandboxed virtual computers equipped with real-world tools for executing code and running complex agentic workflows. Rather than letting AI agents run code directly on production infrastructure, E2B spins up isolated sandbox environments in milliseconds, providing a safe execution layer between LLMs and the real world. Built for developers and enterprises building frontier AI applications, E2B supports a wide range of agent types including deep research agents, computer use agents, background agents, automation agents, and reinforcement learning pipelines. Its sandbox environments are open-source at their core and designed for reliability, security, and scalability. E2B is used by 88% of Fortune 100 companies and has powered notable deployments including Perplexity's advanced data analysis feature (shipped in just one week), Hugging Face's DeepSeek-R1 replication experiments, and Manus's virtual computer agents. The platform also supports secure Model Context Protocol (MCP) servers, making it a comprehensive infrastructure layer for the modern AI agent stack. Developers can get started for free via a straightforward API and SDK, with enterprise-grade options for larger workloads. A dedicated startup program is also available for early-stage companies building agentic products.
Key Features
- Secure AI Sandboxes: Spin up isolated, secure cloud environments in milliseconds so AI agents can execute code safely without touching production infrastructure.
- Real-World Tool Access: Sandboxes come equipped with real OS-level tools, file systems, and internet access, enabling agents to perform genuine compute tasks.
- Broad Agent Type Support: Supports deep research agents, computer use agents, background agents, automation agents, and reinforcement learning pipelines out of the box.
- Secure MCP Servers: Run Model Context Protocol (MCP) servers inside secure sandboxes, providing a safe layer for tool-calling and external integrations.
- Open-Source Core: The sandbox runtime is open-source, giving developers full transparency and the ability to audit, customize, or self-host the environment.
Use Cases
- Running AI-generated code safely in isolated sandboxes to prevent damage to production systems during autonomous agent workflows.
- Building deep research agents that need to browse the web, run scripts, and analyze data in a secure, ephemeral environment.
- Powering computer use agents that require access to a full virtual desktop or operating system to complete complex multi-step tasks.
- Deploying background and automation agents that execute long-running tasks asynchronously without occupying user-facing infrastructure.
- Enabling reinforcement learning pipelines where AI models need repeatable, disposable execution environments to train and evaluate actions.
Pros
- Enterprise-Proven at Scale: Used by 88% of Fortune 100 companies and trusted by leading AI labs like Perplexity, Hugging Face, and Groq for production-grade agentic workloads.
- Fast Time-to-Value: Perplexity shipped advanced data analysis in just one week using E2B, demonstrating how quickly teams can integrate and deploy with the platform.
- Strong Security Isolation: Each sandbox is fully isolated, preventing agents from accessing or damaging host systems, making it safe for untrusted or LLM-generated code execution.
- Free Tier Available: Developers can start for free with a straightforward API and SDK, lowering the barrier to experimentation and prototyping.
Cons
- Cost at Scale: Running many concurrent sandboxes for high-volume production workloads can become expensive; pricing details require checking the pricing page for specifics.
- Developer-Focused Onboarding: The platform is primarily geared toward developers and engineers; non-technical users may find setup and integration challenging without coding knowledge.
- Cloud Dependency: The managed service relies on E2B's cloud infrastructure; teams requiring full on-premises deployment may need additional configuration or enterprise agreements.
Frequently Asked Questions
What is an E2B sandbox?
An E2B sandbox is a secure, isolated virtual computer that spins up in the cloud in milliseconds. It gives AI agents a safe environment to execute code, use real-world tools, and interact with the file system without risking production infrastructure.
Who uses E2B?
E2B is used by developers, AI startups, and large enterprises—including 88% of Fortune 100 companies. Notable customers include Perplexity, Hugging Face, Manus, Groq, and Lindy.
Is E2B open-source?
Yes, E2B's sandbox runtime is open-source. Developers can inspect the code, contribute, or self-host the environment for full control over their infrastructure.
What agent types does E2B support?
E2B supports deep research agents, computer use agents, automation agents, background agents, reinforcement learning pipelines, and secure Model Context Protocol (MCP) servers.
How do I get started with E2B?
You can sign up and start for free on e2b.dev. E2B provides an API and SDK for integration, along with comprehensive documentation, a cookbook of examples, and a startup program for early-stage companies.
