Secure cloud sandboxes that let AI agents run untrusted code, install packages, and execute long-running tasks in isolated micro-VMs.
Secure cloud sandboxes that let AI agents run untrusted code, install packages, and execute long-running tasks in isolated micro-VMs.
E2B (Execute to Build) provides hosted, secure sandboxes designed specifically for AI agents and LLM-generated code. Each sandbox is a Firecracker micro-VM with its own filesystem, networking, and process tree, spun up in roughly 150 milliseconds. Agents can use the sandbox to run Python, JavaScript, or shell commands; install arbitrary packages; persist files; render plots; and stream stdout back to the calling model. The platform exposes both a Code Interpreter SDK (a drop-in equivalent to ChatGPT's tool with Jupyter kernel semantics) and a more general Desktop sandbox that ships with a virtual display for GUI tasks. Developers can build custom sandbox templates with their own dependencies, then ship them as reusable environments for agent fleets. Because each session is fully isolated and disposable, E2B is the default execution layer behind production agent products from Perplexity, Hugging Face, and various open-source agent frameworks. The company shipped a popular open-source release of Firebase-style logs/replays for agent runs, and the Python and TypeScript SDKs are heavily used in research codebases. Sandboxes can persist for up to 24 hours on paid plans and integrate cleanly with LangChain, LlamaIndex, and CrewAI tool definitions.
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E2B sets the gold standard for secure AI code execution with revolutionary Firecracker microVM technology, industry-leading performance, and comprehensive developer tooling. The lack of GPU support and ephemeral storage are notable limitations, but for secure general-purpose code execution by AI systems, E2B delivers unmatched security and performance.
secure AI sandboxes is a core E2B capability covered in the staged data and revised against the latest curl research available for this run.
Use Case:
Adding code interpreter features inside AI products.
virtual computers for agents is a core E2B capability covered in the staged data and revised against the latest curl research available for this run.
Use Case:
Running isolated research, data analysis, and file transformation workloads.
code interpreter infrastructure is a core E2B capability covered in the staged data and revised against the latest curl research available for this run.
Use Case:
Giving computer-use or background agents temporary virtual machines with quotas.
computer-use and background agents is a core E2B capability covered in the staged data and revised against the latest curl research available for this run.
Use Case:
Adding code interpreter features inside AI products.
Secure MCPs is a core E2B capability covered in the staged data and revised against the latest curl research available for this run.
Use Case:
Running isolated research, data analysis, and file transformation workloads.
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Through early 2026, E2B has expanded its Desktop sandbox offering to better support the wave of computer-use agents from Anthropic, OpenAI, and open-source projects, with improved VNC streaming and lower-latency input handling. The platform has deepened native integrations with the Anthropic Claude tool-use API and the Vercel AI SDK, and broadened its enterprise footprint with additional regions and SOC 2 Type II attestation. Custom template build times have been reduced, and per-second billing granularity plus larger memory tiers now make it viable for heavier data-analysis and ML inference workloads inside a sandbox.
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