E2BSecure cloud sandboxes for running AI-generated code and autonomous agents

4.5 (4)

Reviewed by Daniel Nikulshyn·Updated May 2026

Developer Tools Cloud Sandbox AI Agents Code Execution Open Source Python SDK JavaScript SDK Infrastructure

Overview

E2B provides isolated cloud environments designed specifically for executing code produced by large language models and AI agents. Each sandbox spins up quickly, giving developers a safe, ephemeral runtime where untrusted or experimental code can run without risking the host system. The platform is aimed at teams building agentic applications, code interpreters, data analysis assistants, and developer tools that need to execute arbitrary code at scale. SDKs in Python and JavaScript make it straightforward to integrate sandboxes into existing AI workflows, while customizable templates let teams preconfigure dependencies and tooling. E2B is open source at its core, with managed cloud infrastructure available for production use, making it suitable for both prototyping and large-scale deployments.

Key features

Isolated cloud sandbox environments
SDKs for Python and JavaScript
Custom environment templates
File system and process access
Long-running session support
Designed for AI agents and code interpreters

Pricing

Model: Free
Category: Model Serving
Rating: 4.5 / 5 (4)

Use cases

Run LLM-generated code safely

Execute code produced by large language models inside isolated cloud sandboxes, protecting host systems from untrusted or experimental output.

Power autonomous AI agents

Give agentic applications a secure runtime with file system and process access, enabling them to perform multi-step tasks over long-running sessions.

Build a code interpreter feature

Integrate E2B via the Python or JavaScript SDK to add a ChatGPT-style code interpreter to your product for data analysis and computation.

Preconfigured dev environments

Use custom templates to spin up sandboxes with specific dependencies and tooling, standardizing runtimes across AI-powered developer tools.

Pros & Cons

Pros

Strong isolation for running untrusted AI code
Fast sandbox startup times
Python and JavaScript SDKs available
Open source with managed cloud option
Customizable environment templates

Cons

Requires developer knowledge to integrate
Usage-based pricing can scale with heavy workloads
Limited value outside AI/agent use cases

Reviews

4.5

Average from 4 ratings.

Fatima Zahra

Apr 8, 2026

Solid for our team

We rolled this out across the team last quarter and strong isolation for running untrusted AI code. Custom environment templates fits neatly into how we already work, and designed for AI agents and code interpreters removed a step we used to do by hand. but it has held up under daily use.

Elena Rossi

Nov 9, 2025

Use it every day

Honestly didn't expect to like it this much. Isolated cloud sandbox environments is exactly what I needed, and strong isolation for running untrusted AI code. I do wish limited value outside AI/agent use cases, but I reach for it almost every day now and it just clicks.

Jamal Carter

Jul 30, 2025

Solid for our team

We rolled this out across the team last quarter and open source with managed cloud option. Designed for AI agents and code interpreters fits neatly into how we already work, and designed for AI agents and code interpreters removed a step we used to do by hand. Limited value outside AI/agent use cases, which is the main caveat, but it has held up under daily use.

Diego Fernández

Jun 15, 2025

Compared a few options

Evaluated this against two competitors. Where it wins: file system and process access and fast sandbox startup times. Where it lags: limited value outside AI/agent use cases. On balance the feature set — especially custom environment templates — justifies the 4 stars for our use case.