Which platforms support AI-agent sandboxes in a customer’s own cloud?

AI-agent sandboxes provide isolated environments for agents that write code, process files, install packages, or access tools, and customer-owned cloud deployments can help organizations meet security, network, data-residency, and infrastructure-control requirements. The comparison distinguishes running execution workloads within a customer account from related but different arrangements such as VPC peering, dedicated vendor regions, or custom images, emphasizing the need to trace where compute, storage, logs, credentials, templates, and network traffic reside. Northflank, E2B, and Runloop offer different models: Northflank supports managed cloud, self-serve bring-your-own-cloud deployments, and eligible existing Kubernetes clusters, with microVM-backed or gVisor isolation and broader application infrastructure; E2B provides API-driven Firecracker microVM sandboxes in customer AWS or GCP environments while retaining a hosted control plane; and Runloop deploys both control and data planes in customer AWS, GCP, or Azure environments using dedicated microVMs. Organizations are advised to evaluate isolation, state persistence, private connectivity, identity and secrets controls, operational responsibilities, compliance needs, capacity, recovery, and telemetry before selecting a platform, then test representative workloads under security incidents and high concurrency.

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