E2B is a developer-first platform that allows users to create cloud-based AI agents that run in secure, persistent, and programmable environments. Unlike traditional LLM-based agents limited to text outputs or static actions, E2B gives developers access to a full sandboxed runtime where agents can execute real code, access the internet, and interact with files—just like a human developer would on a cloud computer.
Built for scalability, speed, and control, E2B eliminates infrastructure complexity by offering fully managed, ephemeral compute environments tailored for AI agent execution. This allows builders to focus on developing advanced, task-oriented AI agents without having to manage hosting, networking, or storage infrastructure.
E2B is ideal for developers building devtools, automation agents, copilots, and AI-native SaaS products that need real computing power in the background.
Features
E2B provides a unique runtime infrastructure that empowers developers to build more capable, intelligent AI agents.
The core feature is the ephemeral agent runtime, a sandboxed cloud environment where AI agents can execute real-world code. These environments are isolated, customizable, and destroyable, providing a secure place for agents to interact with code, data, and external services.
Each environment comes with a virtual file system, giving agents the ability to read, write, and manage files. This is particularly useful for agents that generate scripts, edit documents, or perform data transformations.
The network access feature allows agents to send HTTP requests, fetch external resources, or interact with APIs, enabling more complex workflows such as web scraping, data syncing, or third-party integrations.
E2B supports terminal access and shell commands, allowing agents to run command-line tools, execute build processes, or test code in real time.
The platform provides language bindings in TypeScript and Python, making it easy to spin up environments and interact with them programmatically. Agents can be defined using simple SDK calls and extended with custom logic.
Each environment is ephemeral and stateless by default, which enhances security and performance. Developers can choose to persist state when necessary.
E2B environments are lightweight and fast to boot—typically in under 300 milliseconds—allowing for real-time responsiveness in applications and agent frameworks.
The platform is infrastructure-agnostic, meaning developers don’t have to deal with provisioning virtual machines or containers. Everything is abstracted into a single API layer.
How It Works
Developers integrate E2B into their application using its SDKs and APIs. When an agent is initialized, E2B spins up a fresh runtime in the cloud—a virtual sandbox where the agent can perform actions just like a local developer.
Inside this runtime, the agent can write files, execute commands, call APIs, and interact with external systems. The developer controls what code the agent runs and how long the environment lasts.
Each runtime is securely isolated and can be shut down or re-initialized as needed. These environments are perfect for short-lived, task-specific executions, such as running a build, checking a repo, or generating code.
E2B is fully programmable. Developers can script the creation of environments, send commands, read outputs, and respond to agent activity in real time. This opens the door for building dynamic applications like intelligent IDE plugins, AI engineering copilots, and backend automation tools.
Because the platform handles all the infrastructure behind the scenes, teams don’t need to manage cloud resources, VM provisioning, or container orchestration. E2B handles the runtime, file system, and networking seamlessly.
Use Cases
E2B enables a wide variety of developer-centric and AI agent-based use cases.
Engineering teams can use E2B to build AI developer assistants that write, test, and run code in real time. Agents can automatically scaffold projects, generate config files, or debug issues using shell access and language tools.
Product builders create AI-native devtools where agents interact with codebases, run tests, or execute commands on demand. This enables products like automated QA bots, project generators, or command-line copilots.
SaaS startups use E2B to power workflow automation agents that can call APIs, process files, or execute backend scripts. These agents perform tasks like report generation, PDF processing, or automated deployments.
Researchers and developers use the platform to test autonomous AI agents that need an execution environment to complete tasks like data cleaning, code compilation, or simulation.
In internal tooling, E2B supports the creation of AI operations agents that manage tasks across cloud systems, perform log analysis, or interact with CI/CD systems.
Pricing
As of July 2025, E2B offers a usage-based pricing model. While specific plan details are not publicly listed on the homepage, developers can get started with a free tier and scale based on runtime usage.
The pricing is designed to align with developer activity and compute time. Users pay for what they consume, including the number of environment spins, duration of sessions, and network usage.
To get detailed pricing or request a quote for high-scale or enterprise use, developers are encouraged to contact the team via the official contact form or check the documentation for updates.
Strengths
E2B stands out in the crowded AI tooling market by offering actual execution environments—not just API wrappers or hosted endpoints. This gives developers the ability to create much more capable and realistic AI agents.
Its developer-first design, with TypeScript and Python support, fits seamlessly into modern AI stacks and developer workflows.
The platform’s fast boot times and secure isolation model allow real-time applications without compromising on safety or scalability.
E2B abstracts away cloud complexity, which means developers can focus entirely on logic and interaction rather than managing infrastructure.
The flexibility of the virtual file system, shell access, and network communication allows for near-human levels of task execution by agents.
E2B’s open and programmable interface makes it well-suited for integration with existing AI agent frameworks like LangChain, OpenAgents, or custom LLM orchestrators.
Drawbacks
E2B’s focus on cloud-based code execution may not suit all projects, especially those where local or offline execution is a priority.
While the SDKs are powerful, developers need to understand how to safely manage code execution and sandbox behavior, particularly when handling third-party input.
The platform is still evolving, and while its core features are stable, some advanced capabilities like persistent state management or deep framework integrations may be limited or require workarounds.
Pricing information is not fully transparent on the homepage, which may require some exploration before budgeting for production-scale use.
Since E2B is optimized for short-lived environments, it may not be ideal for long-running or persistent agents that require extended sessions or background processes.
Comparison with Other Tools
Compared to platforms like Replit or Codesandbox, E2B is not a collaborative IDE—it is a backend infrastructure platform for AI agents. The emphasis is on programmatic control and sandboxed runtime environments, not user-facing coding UIs.
In contrast with traditional cloud services like AWS Lambda or Google Cloud Functions, E2B is specialized for agent use cases and offers a developer-centric API tailored for interactive code execution, not just event-based triggers.
Compared to AI agent orchestration tools like LangChain, E2B is a lower-level infrastructure component. It complements these tools by providing the execution environment that agents can run code in, rather than handling orchestration logic or LLM integration.
Unlike tools that only support read-only or static operations from agents, E2B allows agents to execute live shell commands, edit files, call APIs, and manipulate data in real-time—making them more autonomous and useful in practice.
Customer Reviews and Testimonials
While E2B is a relatively new entrant in the developer tools space, early adopters have praised it for its powerful API, fast runtime performance, and ability to enable real-world agent applications.
Feedback from open-source contributors and developers in the AI agent community highlights E2B’s role in bridging the gap between large language models and actionable task execution.
Community members have shared examples of building agents that scaffold projects, run security scans, fetch web data, and test code—all enabled by E2B’s secure environments.
The E2B team is active in the developer ecosystem, with ongoing support, Discord community involvement, and transparent product updates through their changelog and GitHub.
Conclusion
E2B is a forward-thinking platform that provides AI agents with real execution environments in the cloud. By removing the limitations of static tools and offering programmable, secure runtimes, E2B unlocks a new class of intelligent, autonomous agents that can actually complete developer tasks.
Whether you’re building an AI devtool, a workflow automation assistant, or an LLM-powered copilot, E2B gives you the power to move beyond static responses and into true agentic action. With its simple APIs, fast runtimes, and flexible architecture, E2B is positioned to be a foundational layer for the next generation of AI-native software.
