OpenClaw is a serious AI agent, but the way most people run it is the problem. There are 40,000+ OpenClaw instances exposed on the public internet right now, almost all of them sitting on default “one-click” configurations with open ports, default passwords, and no patch routine.
That setup works for five minutes of testing. It does not work for an agent that’s reading your inbox, writing to your database, or moving money through your automations.
Hardened, not just installed
Managed OpenClaw is a manual, hardened deployment of the OpenClaw agent on dedicated infrastructure I configure and maintain.
- Zero exposed ports. OpenClaw binds to localhost. External traffic comes through a Pangolin proxy with identity-aware access rules.
- Sandboxed execution. The agent runs in its own container with strict network segmentation between services.
- Reproducible builds. Pinned versions, tested in staging before they touch your live instance.
- Client-owned storage. Conversation logs, memory, and encrypted backups live in storage buckets you control.
You bring your own LLM API key (OpenAI, Anthropic, whatever you prefer), and I handle the layer underneath: hosting, network, patching, backups, restore drills.
This tier is the entry point. If you want the full agency stack with a private chat interface, workflow automation through n8n, a structured database in Baserow, and a unified LLM gateway with budget caps across providers, see the Managed AI Suite at 199€/mo. If you’re going further and orchestrating an autonomous company on top of that stack, Managed Paperclip Hosting is the control-plane tier above this one. For more depth on the open-source tooling behind these tiers, browse my open-source solutions writeups.
To get this deployed cleanly on infrastructure I run end-to-end, apply for Access and we’ll size the box on the discovery call.