E2B

E2B is an open-source infrastructure platform built by FoundryLabs, Inc. that provides secure, isolated sandboxes for running AI-generated code in the cloud. The core platform is licensed under Apache 2.0 and powers everything from short code snippets to fully autonomous AI agents running for up to 24 hours. E2B raised a $21M Series A and the company reports over 1 billion sandboxes started and 7 million monthly downloads across its SDKs.

What It Is

E2B provides on-demand Linux microVM sandboxes that AI agents can use to safely execute code, process data, browse the web, manage files, and run terminal commands. Each sandbox is powered by Firecracker, the same microVM technology used by AWS Lambda, ensuring full isolation between workloads. Developers integrate E2B through Python or JavaScript/TypeScript SDKs in just a few lines of code, and sandboxes in the same region as the client start in under 200 milliseconds with no cold starts.

Architecture: Firecracker-Backed Isolation

The security model is built around Firecracker microVMs, which provide hardware-level isolation for untrusted, LLM-generated code. Key architectural properties include:

• Full isolation: Each sandbox runs in its own microVM, preventing cross-contamination between workloads
• Custom templates: Developers can define sandbox environments using custom templates, pre-installing packages and system libraries
• Concurrent scale: The platform supports tens of thousands of concurrent sandboxes, enabling use cases like reinforcement learning reward function evaluation
• Session length: Sandboxes run from a few seconds up to 24 hours (24-hour sessions available on Pro and above)
• Deployment flexibility: Supports BYOC (Bring Your Own Cloud) on AWS, GCP, or Azure, on-premises, and self-hosted deployments via Terraform

Use Cases and Agent Workflows

E2B is designed for a range of agentic workflows:

• Deep research agents: Long-running agents that conduct research on large datasets
• AI data analysis and visualization: Connecting data to isolated sandboxes for secure chart generation
• Coding agents: Executing AI-generated Python, JavaScript, Ruby, C++, and more with internet access and file I/O
• Vibe coding / AI app runtimes: Using sandboxes as code runtimes for AI-generated applications (supports any language and framework)
• Reinforcement learning: Running thousands of concurrent sandboxes to evaluate reward functions
• Computer use agents: Desktop Sandbox provides a full virtual Linux desktop for LLM-driven computer use

LLM and Framework Integrations

E2B is LLM-agnostic and ships with cookbook examples for a wide range of providers and frameworks:

• LLM providers: OpenAI (GPT-4o, o1), Anthropic (Claude), Mistral (Codestral), Meta (Llama 3), Groq, Fireworks AI, Together AI, IBM WatsonX, Ollama
• Agent frameworks: LangChain, LangGraph, LlamaIndex, Autogen, Vercel AI SDK
• Languages: Python (e2b-code-interpreter) and JavaScript/TypeScript (@e2b/code-interpreter)

Update: CLI v2.13.3 and Active Development

The GitHub repository (12,900+ stars, 965 forks) shows active development with the latest release being @e2b/cli@2.13.3, published on July 15, 2026. The project is maintained under the Apache License 2.0 by FoundryLabs, Inc. and accepts community contributions. Self-hosting is supported on AWS and GCP via Terraform, with Azure support listed as in progress.

Enterprise Adoption Signals

The E2B enterprise page states the platform is used by companies across Fortune 100 and hypergrowth AI startups. Published case studies on the E2B website include Hugging Face (Open R1 replication), Manus (virtual computer for agents), Groq (compound AI systems), Lindy (AI workflow automation), Perplexity (advanced data analysis shipped in one week), and Genspark. The platform offers US and EU regions for data residency compliance, role-based access control, SLA guarantees, and an enterprise security trust page.