SENTINEL RUN is a containment-first AI execution platform designed to make autonomous agents safer and more useful. Traditional AI assistants can generate code and explain how to perform tasks, but executing AI-generated code introduces serious risks, including unauthorized filesystem access, network misuse, exposed credentials and uncontrolled resource consumption. SENTINEL RUN addresses this challenge through a centralized orchestration layer powered by Vultr. Users submit a task, and an AI agent generates the required Python code using Vultr Serverless Inference. The execution controller dispatches that code into a fresh, isolated Docker container with restricted filesystem access, disabled networking, memory limits, CPU limits and execution timeouts. After execution, the platform captures real logs, checks exit codes, verifies generated artifacts and returns downloadable results to the user. Failed executions can enter a bounded repair cycle using captured error information. Our initial use case focuses on intelligent CSV analysis, automated reporting and chart generation. SENTINEL RUN demonstrates a key principle for the future of AI: autonomous agents should not only be intelligent; they should operate within enforceable boundaries, produce verifiable results and remain accountable for their actions.
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