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AI Agent Environment

Deploy Autonomous AI Agents on Isolated VMs

Run OpenClaw AI agents with browser automation, messaging bridges to Signal, Telegram, WhatsApp, and Discord — on dedicated VMs with optional GPU for local model inference.

TL;DR

  • →Pre-installed — Node.js 22, Chromium, OpenClaw, Docker, and NVIDIA drivers ready to go
  • →CPU or GPU mode — use hosted API providers or run local models with vLLM on a dedicated GPU
  • →Messaging bridges — connect agents to Signal, Telegram, WhatsApp, and Discord out of the box
  • →Hardware-isolated — VFIO GPU passthrough and WireGuard encryption for full security

What Is OpenClaw?

OpenClaw is a headless AI agent framework that runs as a Node.js daemon. It can browse the web, interact with messaging platforms, execute code, and perform complex multi-step tasks autonomously. Think of it as an always-on AI assistant that lives on a server instead of in a browser tab.

The challenge with running AI agents is that they need a persistent, isolated environment — they need to maintain browser sessions, handle incoming messages, and stay online 24/7. Running this on your laptop isn't practical. Running it in a shared container isn't secure. That's where VectorLay's OpenClaw environment comes in.

Why Run AI Agents on VectorLay?

True isolation. Each agent runs in its own virtual machine — not a container. VFIO GPU passthrough means your GPU is exclusively yours. No shared kernel, no container escapes, no noisy neighbors.
Always on. VMs run 24/7 with automatic failover. If the underlying node goes down, your agent is migrated to a healthy node automatically. No babysitting required.
Optional GPU. Run agents in CPU mode using hosted API providers like Claude, OpenAI, or Gemini. Or switch to GPU mode and run models locally with vLLM — keeping all data on your own hardware.
Encrypted networking. All traffic between your VM and the VectorLay network travels over WireGuard. SSH access is proxied through a secure tunnel. Your agent's communications stay private.

Two Deployment Modes

The OpenClaw environment supports two deployment configurations, depending on whether you want to use hosted AI providers or run models locally:

CPU MODE

Hosted Providers

Uses external API providers (Claude, OpenAI, Gemini, etc.) for model inference. The VM only needs CPU and RAM — no GPU required.

  • Lower cost per hour
  • Simpler setup
  • Best for agents that primarily browse and message
GPU MODE

Local Inference

Runs models locally using vLLM on a dedicated GPU (RTX 3090 or 4090). All inference stays on your VM — no data sent to external APIs.

  • Full data privacy
  • No per-token API costs
  • Best for sensitive data or high-volume agents

What's Included

Node.js 22

Latest LTS runtime for the OpenClaw daemon and any custom scripts you want to run.

Chromium

Headless browser for web automation, scraping, and interacting with web applications.

OpenClaw

The AI agent framework, pre-installed and ready to configure with your API keys and messaging bridges.

Docker + NVIDIA Drivers

Docker engine and NVIDIA container toolkit for running vLLM or any other GPU-accelerated container.

Messaging Platform Support

OpenClaw agents can connect to multiple messaging platforms simultaneously, acting as an always-available AI assistant across your communication channels:

PlatformBridge TypeFeatures
TelegramBot APIText, images, inline keyboards, group chats
DiscordBot APIText channels, DMs, slash commands, embeds
SignalSignal CLIEnd-to-end encrypted messaging, group chats
WhatsAppWeb bridgeText, media, groups via web automation

Security and Isolation

AI agents handle sensitive data — API keys, messaging credentials, browsing sessions. VectorLay's VM-level isolation provides stronger security guarantees than container-based platforms:

VFIO GPU passthrough — the GPU is exclusively assigned to your VM at the hardware level. No shared drivers, no side-channel attacks.
WireGuard encryption — all network traffic between your VM and the VectorLay infrastructure is encrypted in transit.
Separate kernel — unlike containers, your VM has its own kernel. A vulnerability in one VM cannot affect another.

Full deployment guide

For a step-by-step walkthrough including messaging bridge setup, local model configuration, and running OpenClaw as a daemon, read the full tutorial:

Deploy an OpenClaw AI Agent on VectorLay in Minutes

Deploy your AI agent today

Launch an always-on AI agent on a dedicated, isolated VM. Pre-installed software, optional GPU, and automatic failover. Pay by the hour, no commitments.

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