Agent Sandbox

Agent Sandbox is an execution environment designed for building and deploying AI agents that can safely run Python and Bash code in production. It provides a secure sandbox API that isolates untrusted code, enabling developers to offload computation, automation tasks, and tool-using behaviors from LLMs without exposing core infrastructure. The platform focuses on giving AI agents controlled access to a real runtime while preserving security, observability, and reproducibility.

Key capabilities include sandboxed execution of Python and Bash with resource limits, ephemeral and persistent file storage, and controlled dependency installation via package managers. Agent Sandbox supports generating and storing artifacts—such as logs, reports, datasets, and model outputs—that can be retrieved or consumed by downstream systems. Its API-centric design makes it straightforward to integrate with existing LLM workflows, orchestration frameworks, and agent libraries. Built-in isolation, environment management, and execution logging help teams manage risk, debug failures, and maintain compliance when running arbitrary code from AI agents.