OpenClawSelf-Hosting Guide

Self-Host OpenClaw on aFree VPS — Step by Step

You can self-host OpenClaw with Ollama for $0/month using Oracle Cloud's Always Free tier (4 ARM CPUs, 24 GB RAM, 200 GB storage). This guide walks you through the complete setup: from provisioning your server to running local AI models behind a secure HTTPS reverse proxy.

$0/month hosting
~45 min setup
8 steps
Beginner-friendly

What You'll Achieve

  • Your own private AI assistant on a free server
  • Runs Llama, Qwen, Gemma, DeepSeek & 100+ models
  • Oracle Cloud's permanent free tier — $0/month
  • Full data privacy — nothing leaves your server
  • No coding experience required
30–45 min Beginner-friendly 8 steps

Why Oracle Cloud Free Tier?

Oracle Cloud's Always Free tier offers the most generous free compute resources of any major cloud provider. With 24 GB of RAM, you can run 7B parameter models comfortably and even quantized 13B models — something impossible on AWS or Google Cloud free tiers which only offer 1 GB RAM.

4
ARM OCPUs
24 GB
RAM
200 GB
SSD Storage
10 TB
Monthly Transfer
2
VCNs
$0
Forever

Self-hosting is the cheap way to run OpenClaw. It's not the easy way.

The 8 steps below take 30–45 minutes when everything works, and a weekend when it doesn't. One thing worth knowing before you start. If you're doing this for yourself, self-hosting is genuinely the right call — it's free, you own it, and nobody's blocked if it falls over for a night. If you're doing it for a company, the server is the easy part. What decides whether any of it pays off is whether the job you point the agent at has KPIs and SOPs somebody has actually written down.

Should you build this yourself?8 questions · free, no email · it says “do it yourself” when that's the answer

Want AI agents that do real business work — sales, support, ops? That's what we actually do all day.

Book a Discovery Call

Before You Start

Make sure you have the following ready:

  • Credit/Debit CardFor Oracle Cloud identity verification (not charged)
  • Domain NameFor HTTPS access (free options: DuckDNS, No-IP, FreeDNS)
  • SSH ClientTerminal (Mac/Linux) or PuTTY (Windows)
  • Basic Terminal KnowledgeComfortable running commands and editing files
Step 1 of 8

Create Your Oracle Cloud Free Account

Oracle Cloud Infrastructure (OCI) offers an Always Free tier that includes ARM-based compute instances with up to 4 OCPUs and 24 GB of RAM — more than enough to run OpenClaw with local AI models. Unlike AWS or Google Cloud free tiers, Oracle's Always Free resources never expire.

What to do:

  • Go to cloud.oracle.com and click "Start for Free"
  • You'll need a valid credit card for identity verification (you won't be charged)
  • Select your home region carefully — free tier resources must be created here
  • Complete email verification and set up your tenancy
  • The free tier includes: 4 ARM OCPUs, 24 GB RAM, 200 GB block storage, 10 TB/month outbound data
Terminal
# Oracle Cloud Always Free Tier includes:
# ✓ 4 ARM Ampere A1 OCPUs (flexible allocation)
# ✓ 24 GB total RAM
# ✓ 200 GB block volume storage
# ✓ 10 TB/month outbound data transfer
# ✓ 2 Virtual Cloud Networks (VCNs)
# ✓ 1 Flexible Load Balancer (10 Mbps)
#
# Sign up at: https://cloud.oracle.com
#
# Important: Choose your home region wisely!
# Free tier resources can ONLY be created in your home region.
# Recommended: Pick a region close to you geographically.
Click anywhere to copy

Oracle Cloud setup taking a while?

Free-tier verification is where most people lose an hour: region selection, identity checks, and instance availability all fight you. If Oracle keeps refusing to give you a box, it is usually faster to switch providers than to keep retrying.

Step 2 of 8

Provision Your ARM Compute Instance

Create an ARM-based Ampere A1 instance with the maximum free tier allocation. ARM processors offer excellent performance per watt, and the 24 GB of RAM allows you to run 7B and even quantized 13B parameter AI models locally.

ARM instances on Oracle's free tier are in high demand. If provisioning fails, try again at off-peak hours (early morning UTC) or use a retry script. The instances are well worth the wait.

What to do:

  • Navigate to Compute → Instances → Create Instance
  • Choose "Ampere" (ARM) as the shape — select VM.Standard.A1.Flex
  • Allocate 4 OCPUs and 24 GB RAM (maximum free tier)
  • Select Ubuntu 22.04 or 24.04 as the OS image
  • Set boot volume to 100 GB (up to 200 GB free) and add your SSH public key
  • Configure VCN security list to allow ports 22 (SSH), 80 (HTTP), and 443 (HTTPS)
Terminal
# After creating your instance, note the public IP address.
# SSH into your new server:
ssh -i ~/.ssh/your-private-key ubuntu@YOUR_PUBLIC_IP

# First, update the system packages:
sudo apt update && sudo apt upgrade -y

# Set the hostname (optional, but helpful):
sudo hostnamectl set-hostname openclaw-server

# Create a swap file (important for handling memory spikes):
sudo fallocate -l 16G /swapfile
sudo chmod 600 /swapfile
sudo mkswap /swapfile
sudo swapon /swapfile

# Make swap permanent:
echo '/swapfile none swap sw 0 0' | sudo tee -a /etc/fstab

# Set swappiness to 10 (use RAM first, swap as fallback):
echo 'vm.swappiness=10' | sudo tee -a /etc/sysctl.conf
sudo sysctl -p

# Verify swap is active:
free -h
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Step 3 of 8

Secure Your Server

Before installing anything, lock down your server with essential security measures. This includes configuring the firewall, hardening SSH access, and installing intrusion prevention tools.

Ensure you have SSH key access working before disabling password authentication! If you lock yourself out, you'll need to use the Oracle Cloud console to access your instance.

What to do:

  • Configure UFW firewall to only allow SSH, HTTP, and HTTPS traffic
  • Disable password-based SSH authentication (use keys only)
  • Install Fail2Ban to block brute-force SSH attempts
  • Enable automatic security updates to stay patched
  • Disable root SSH login for additional security
Terminal
# Install security tools:
sudo apt install -y ufw fail2ban unattended-upgrades

# Configure UFW firewall:
sudo ufw default deny incoming
sudo ufw default allow outgoing
sudo ufw allow 22/tcp    # SSH
sudo ufw allow 80/tcp    # HTTP (for Let's Encrypt)
sudo ufw allow 443/tcp   # HTTPS
sudo ufw --force enable

# Verify firewall status:
sudo ufw status verbose

# Configure Fail2Ban for SSH protection:
sudo tee /etc/fail2ban/jail.local > /dev/null << 'EOF'
[sshd]
enabled = true
port = ssh
filter = sshd
logpath = /var/log/auth.log
maxretry = 3
bantime = 3600
findtime = 600
EOF

sudo systemctl enable fail2ban
sudo systemctl start fail2ban

# Harden SSH configuration:
sudo sed -i 's/#PasswordAuthentication yes/PasswordAuthentication no/' /etc/ssh/sshd_config
sudo sed -i 's/PermitRootLogin yes/PermitRootLogin no/' /etc/ssh/sshd_config
sudo systemctl restart sshd

# Enable automatic security updates:
sudo dpkg-reconfigure -plow unattended-upgrades
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Security is the most critical part

A misconfigured VPS exposes your AI conversations and your API keys. Do not skip this step and come back to it later. Nobody comes back to it later.

Step 4 of 8

Install Docker & Docker Compose

Docker is the recommended way to deploy OpenClaw and Ollama. It provides isolation, easy updates, and reproducible deployments. Docker Compose v2 manages the multi-container setup with a single configuration file.

What to do:

  • Install Docker Engine using the official repository (not the Ubuntu snap package)
  • Docker Compose v2 is included with modern Docker Engine installations
  • Add your user to the docker group so you don't need sudo for every command
  • Verify the installation with a test container
Terminal
# Install Docker using the official convenience script:
curl -fsSL https://get.docker.com | sudo sh

# Add your user to the docker group:
sudo usermod -aG docker $USER

# Apply group changes (or log out and back in):
newgrp docker

# Verify Docker is installed and running:
docker --version
docker compose version

# Test with a hello-world container:
docker run --rm hello-world

# Enable Docker to start on boot:
sudo systemctl enable docker
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Docker giving you trouble?

ARM compatibility, memory limits and networking quirks all bite here. Check your architecture matches the image tag first — that is the cause about as often as everything else combined.

Step 5 of 8

Deploy OpenClaw with Docker Compose

This is the core step. You'll create a Docker Compose configuration that runs Ollama (the local AI model server) alongside the OpenClaw web interface. The setup uses named Docker volumes for persistent data storage.

What to do:

  • Create a project directory and Docker Compose configuration file
  • The compose file defines two services: Ollama (model server) and OpenClaw (web UI)
  • Ollama runs locally and handles AI model inference on your ARM CPU
  • OpenClaw connects to Ollama and provides a beautiful web interface
  • Data is stored in named Docker volumes that persist across container restarts
  • Generate a strong secret key for session encryption
Terminal
# Create project directory:
mkdir -p ~/openclaw && cd ~/openclaw

# Generate a secure secret key:
WEBUI_SECRET=$(openssl rand -base64 32)
echo "Your secret key: $WEBUI_SECRET"
echo "Save this somewhere safe!"

# Create the Docker Compose file:
cat > docker-compose.yml << 'COMPOSE'
services:
  ollama:
    image: ollama/ollama:latest
    container_name: ollama
    volumes:
      - ollama_data:/root/.ollama
    environment:
      - OLLAMA_HOST=0.0.0.0:11434
    restart: unless-stopped
    deploy:
      resources:
        reservations:
          memory: 4G

  openclaw:
    image: ghcr.io/open-webui/open-webui:main
    container_name: openclaw
    environment:
      - OLLAMA_BASE_URL=http://ollama:11434
      - WEBUI_SECRET_KEY=${WEBUI_SECRET_KEY}
      - ENABLE_SIGNUP=true
      - DEFAULT_USER_ROLE=pending
    volumes:
      - openclaw_data:/app/backend/data
    depends_on:
      - ollama
    ports:
      - "127.0.0.1:3000:8080"
    restart: unless-stopped

volumes:
  ollama_data:
  openclaw_data:
COMPOSE

# Create .env file with your secret key:
echo "WEBUI_SECRET_KEY=$WEBUI_SECRET" > .env

# Start the services:
docker compose up -d

# Check that both containers are running:
docker compose ps

# View logs to confirm startup:
docker compose logs -f --tail 50
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Step 6 of 8

Set Up Nginx Reverse Proxy & Free SSL

Nginx acts as a reverse proxy in front of OpenClaw, handling SSL termination, WebSocket connections (essential for streaming AI responses), and static asset caching. Let's Encrypt provides free, auto-renewing SSL certificates.

You MUST have a domain name pointed at your server's IP address before running certbot. DNS propagation typically takes 5-30 minutes. You can get a free subdomain from DuckDNS (duckdns.org), No-IP (noip.com), or FreeDNS (freedns.afraid.org).

What to do:

  • Install Nginx and Certbot (Let's Encrypt client)
  • Point your domain's DNS A record to your server's public IP
  • Configure Nginx with WebSocket support (critical for streaming responses)
  • Disable proxy buffering to prevent garbled AI responses
  • Obtain a free SSL certificate from Let's Encrypt
  • Set up automatic certificate renewal (certificates expire every 90 days)
Terminal
# Install Nginx and Certbot:
sudo apt install -y nginx certbot python3-certbot-nginx

# Create Nginx configuration:
sudo tee /etc/nginx/sites-available/openclaw > /dev/null << 'NGINX'
server {
    listen 80;
    server_name YOUR_DOMAIN;

    # Let's Encrypt verification
    location /.well-known/acme-challenge/ {
        root /var/www/html;
    }

    # Redirect all HTTP to HTTPS
    location / {
        return 301 https://$host$request_uri;
    }
}

server {
    listen 443 ssl;
    http2 on;
    server_name YOUR_DOMAIN;

    # SSL certificates (will be auto-configured by certbot)
    ssl_certificate /etc/letsencrypt/live/YOUR_DOMAIN/fullchain.pem;
    ssl_certificate_key /etc/letsencrypt/live/YOUR_DOMAIN/privkey.pem;
    ssl_protocols TLSv1.2 TLSv1.3;

    # WebSocket support & streaming (CRITICAL for OpenClaw)
    location / {
        proxy_pass http://127.0.0.1:3000;
        proxy_http_version 1.1;
        proxy_set_header Upgrade $http_upgrade;
        proxy_set_header Connection "upgrade";
        proxy_set_header Host $host;
        proxy_set_header X-Real-IP $remote_addr;
        proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
        proxy_set_header X-Forwarded-Proto $scheme;

        # IMPORTANT: Disable buffering for streaming responses
        proxy_buffering off;
        proxy_cache off;

        # Allow long-running model responses
        proxy_read_timeout 600s;
        proxy_send_timeout 600s;

        # Allow large file uploads (for RAG documents)
        client_max_body_size 50M;
    }

    # Cache static assets
    location ~* \.(css|jpg|jpeg|png|gif|ico|svg|woff|woff2|ttf|eot|js)$ {
        proxy_pass http://127.0.0.1:3000;
        proxy_http_version 1.1;
        proxy_set_header Host $host;
        expires 7d;
        add_header Cache-Control "public, immutable";
    }
}
NGINX

# Enable the site:
sudo ln -sf /etc/nginx/sites-available/openclaw /etc/nginx/sites-enabled/
sudo rm -f /etc/nginx/sites-enabled/default

# Test Nginx configuration:
sudo nginx -t

# Start Nginx:
sudo systemctl restart nginx

# Obtain SSL certificate (replace YOUR_DOMAIN and YOUR_EMAIL):
sudo certbot --nginx -d YOUR_DOMAIN --non-interactive --agree-tos -m YOUR_EMAIL

# Verify auto-renewal is enabled:
sudo certbot renew --dry-run

# Test your setup — visit https://YOUR_DOMAIN in your browser!
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Step 7 of 8

Download AI Models

With Ollama running, pull your first AI models. Start with a lightweight model for testing, then add larger models based on your available RAM. With 24 GB RAM on Oracle's free tier, you can comfortably run 8B models and quantized 12B–13B models.

What to do:

  • Use 'docker exec' to run Ollama commands inside the container
  • Start with Llama 3.2 3B (lightweight, fast, great for testing)
  • Add Llama 3.1 8B for general-purpose use (best quality-to-size ratio)
  • Try Qwen 3 or Gemma 3 for variety and multilingual support
  • Use Q4_K_M quantization for the best speed/quality tradeoff on ARM
  • Each 7B-8B model uses approximately 4-5 GB of disk space
Terminal
# Pull your first model (lightweight, great for testing):
docker exec -it ollama ollama pull llama3.2:3b

# Pull the recommended general-purpose model:
docker exec -it ollama ollama pull llama3.1:8b

# Optional: Pull additional models based on your needs:
docker exec -it ollama ollama pull qwen3:8b          # Multilingual + thinking mode
docker exec -it ollama ollama pull gemma3:4b          # Google's efficient model
docker exec -it ollama ollama pull phi4-mini          # Microsoft's compact model
docker exec -it ollama ollama pull deepseek-r1:8b     # Reasoning model

# List all downloaded models:
docker exec -it ollama ollama list

# Test a model with a quick prompt:
docker exec -it ollama ollama run llama3.1:8b "What is 2+2? Answer briefly."

# Check which models are loaded in memory:
docker exec -it ollama ollama ps

# Remove a model you no longer need:
# docker exec -it ollama ollama rm model-name
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Step 8 of 8

Configure & Optimize OpenClaw

Access your OpenClaw instance through the browser, create your admin account, configure performance settings, and optimize the deployment for the free tier hardware. The first account you create automatically becomes the administrator.

What to do:

  • Visit https://YOUR_DOMAIN in your browser
  • Create your admin account (first signup gets admin privileges)
  • Disable public signups after creating your account
  • Configure performance settings for ARM + limited resources
  • Enable caching to speed up model and page loading
  • Set up task models to use lightweight models for background tasks
Terminal
# After creating your admin account in the browser,
# optimize OpenClaw for free tier hardware.

# Stop the services temporarily:
cd ~/openclaw
docker compose down

# Update docker-compose.yml with production optimizations:
cat > docker-compose.yml << 'COMPOSE'
services:
  ollama:
    image: ollama/ollama:latest
    container_name: ollama
    volumes:
      - ollama_data:/root/.ollama
    environment:
      - OLLAMA_HOST=0.0.0.0:11434
      - OLLAMA_FLASH_ATTENTION=1
      - OLLAMA_NUM_PARALLEL=2
    restart: unless-stopped
    deploy:
      resources:
        reservations:
          memory: 4G
        limits:
          memory: 20G

  openclaw:
    image: ghcr.io/open-webui/open-webui:main
    container_name: openclaw
    environment:
      - OLLAMA_BASE_URL=http://ollama:11434
      - WEBUI_SECRET_KEY=${WEBUI_SECRET_KEY}
      - ENABLE_SIGNUP=false
      - DEFAULT_USER_ROLE=pending
      - WEBUI_AUTH=true
      - WEBUI_SESSION_COOKIE_SECURE=true
      - WEBUI_SESSION_COOKIE_SAME_SITE=lax
      # Performance optimizations
      - ENABLE_REALTIME_CHAT_SAVE=false
      - ENABLE_BASE_MODELS_CACHE=true
      - AUDIO_STT_ENGINE=webapi
      - ENABLE_AUTOCOMPLETE_GENERATION=false
    volumes:
      - openclaw_data:/app/backend/data
    depends_on:
      - ollama
    ports:
      - "127.0.0.1:3000:8080"
    restart: unless-stopped

volumes:
  ollama_data:
  openclaw_data:
COMPOSE

# Restart with optimized configuration:
docker compose up -d

# Verify both services are healthy:
docker compose ps
docker compose logs --tail 20
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A note on what we sell, and what we'd rather you do

OpenClaw installs are no longer the work we lead with. This guide is the whole thing, free, and if you want a simple automation running without touching a server at all, n8n, Make and Zapier will get you there faster than we would. We do still run the OpenClaw setup service for people who want it done for them. The work we care about starts after “it runs on a box” and turns into who owns the agent, what it's measured on, and what happens when it's wrong.

Model Guide

Recommended AI Models for Free Tier

With 24 GB RAM, here are the models that work best on CPU-only ARM hardware.

ModelSizeRAM NeededSpeed
Llama 3.21B, 3B2–4 GBFast
Llama 3.1Recommended8B8 GBMedium
Qwen 38B8 GBMedium
Gemma 34B, 12B4–10 GBMedium
DeepSeek R18B8 GBMedium
Phi-4 Mini3.8B4 GBFast

All models are free and open source. Browse the full catalog at ollama.com/library

Optimization

Performance Tips for Free Tier

Squeeze maximum performance from your free Oracle Cloud instance.

Use Browser Speech-to-Text

Set AUDIO_STT_ENGINE=webapi to offload speech recognition to the browser, saving server RAM.

Enable Model Caching

Set ENABLE_BASE_MODELS_CACHE=true for near-instant page loads when switching between models.

Disable Real-time Chat Save

Set ENABLE_REALTIME_CHAT_SAVE=false to batch database writes and prevent I/O bottlenecks.

Use Flash Attention

Set OLLAMA_FLASH_ATTENTION=1 for improved inference speed and memory efficiency on ARM.

Q4_K_M Quantization

Use Q4_K_M or Q5_K_M quantized models for the best speed/quality tradeoff on CPU-only systems.

Lightweight Task Models

Use small models (Llama 3.2 1B or 3B) for background tasks like title generation and tagging.

This guide is right for you if you're the only one who touches it

Solo, one instance, one user — self-hosting is genuinely the correct call: it's free, you own it, and if it goes down for a night nobody's blocked. The moment a team depends on this deployment, the math changes — uptime, patching, and access control become someone's job, not a hobby. Our honest self-host-vs-managed comparison walks through exactly where that line sits. Once you're past it the question stops being which server and becomes who owns this when it breaks at 2am. That's the problem Agentic OS solves — agents that sit in your org chart with a named human manager, not a box somebody has to remember to patch. Not sure you're there yet? The readiness scorecard takes five minutes and never asks for your email.

Critical

Security Checklist

Do not skip these. A misconfigured OpenClaw instance can expose your data and server. For an in-depth security guide, read our OpenClaw Security Hardening Guide.

Click each item as you complete it:

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Help

Troubleshooting

Common issues and their solutions.

Frequently Asked Questions

Everything you need to know about self-hosting OpenClaw for free.

Yes. Oracle Cloud's Always Free resources do not expire and do not require payment. However, idle instances (CPU utilization below 20% at the 95th percentile over a 7-day period) may be reclaimed. Running OpenClaw with occasional usage typically keeps instances active. You can also upgrade to Pay As You Go (PAYG) at no cost — you won't be charged as long as usage stays within Always Free limits, and your instances become exempt from reclamation.
Yes. Ollama supports CPU-only inference, and ARM Ampere processors (used in Oracle's free tier) handle quantized models surprisingly well. You can run 7B parameter models at 5-10 tokens per second and quantized 13B models at 2-5 tokens per second. This is fast enough for personal use, though not suitable for high-concurrency production workloads.
Self-hosting gives you complete data privacy (nothing leaves your server), zero per-token costs, and no rate limits. The tradeoff is that local models are smaller and less capable than the latest cloud models like GPT-4o or Claude Opus. Many users combine both: local models for everyday tasks and privacy-sensitive work, with API access for complex tasks. OpenClaw supports both approaches.
We do, but it stopped being the work we lead with. Hardly anyone was asking, so we quit promoting it and published the whole method here for free. If you want an automation running without babysitting a server at all, n8n, Make or Zapier will get you there faster than hiring anyone. The paid OpenClaw setup service is still open if you'd rather hand the box over. Our focus is agent work for companies: Agentic OS, where agents sit in your org chart with a named human manager, and Company Second Brain, an AI knowledge base over what your team already knows.
Yes. OpenClaw supports any OpenAI-compatible API endpoint. You can add OpenAI (GPT-4o, GPT-4o-mini), Anthropic (Claude), Google (Gemini), Groq, and many others through the admin settings. This gives you the best of both worlds: free local models for everyday use and premium cloud models when you need maximum capability.
Updating is simple with Docker. Run: docker compose pull && docker compose up -d. This pulls the latest images and restarts the containers. Your data is stored in Docker volumes, so updates don't affect your conversations, settings, or downloaded models. We recommend updating at least monthly to get security patches and new features.
With proper hardening (as outlined in this guide), yes — for personal and small team use. For enterprise deployments handling sensitive data, PII, or requiring compliance (SOC 2, HIPAA, GDPR), we recommend our professional setup service which implements our RAK security framework, penetration testing, and compliance-ready configuration. See our OpenClaw Security Hardening Guide for the full security picture.
Oracle may reclaim Always Free instances that are idle for 7+ consecutive days (CPU utilization below 20% at the 95th percentile). The simplest prevention is to upgrade to Pay As You Go (free — you won't be charged within Always Free limits), which makes your instances exempt from reclamation. Alternatively, normal OpenClaw usage (even occasional) is typically sufficient to stay above the threshold. Keep regular backups of your Docker volumes as a safety net.
The useful test isn't budget or headcount, it's whether the work is defined. If a role has KPIs somebody actually wrote down and SOPs somebody actually wrote down, and the work is mostly digital, an agent will very likely do that work better, or at least take a chunk of it off. If neither exists yet, no amount of money spent on setup helps: you'd be automating something nobody has agreed on. Write the SOP first, then decide.

Keeping OpenClaw Updated

OpenClaw and Ollama are actively developed with frequent updates, security patches, and new features. Updating is simple with Docker:

Terminal
# Pull latest images and restart:
cd ~/openclaw
docker compose pull
docker compose up -d

# Check running versions:
docker compose ps

# View update logs:
docker compose logs --tail 20

Your conversations, settings, and downloaded models are stored in Docker volumes and persist across updates.

🦞

You've got it running. Now the harder question.

If this box is for you, you're done — go build something. Read the hardening guide and grab some agent skills. If it's for a company, the interesting problems start now, and none of them are technical.

DON'T HIRE US YET
One workflow, one motivated person
  • Build it in n8n, Make or Zapier
  • Cheaper and faster than any agency
  • Come back when it's repeatable and breaking
Check which one you are
WHERE WE'RE ACTUALLY USEFUL
A role, not a script
  • The role has KPIs somebody wrote down
  • It has SOPs, and the work is mostly digital
  • Somebody senior will own the outcome
Agentic OS

You just gave yourself an AI agent. Imagine your whole company running this way.

Self-hosting OpenClaw is exactly what we do for businesses — at production scale. We build custom agents that qualify leads, answer customers, and clear ops busywork, then install the operating model where your team owns the judgment and agents own the grind. 100+ agents deployed, first one live in ~4 weeks. Wondering what changes when ten people share one deployment? Read OpenClaw for teams: what a real business deployment involves.

Written by Cognio Labs

Experts in AI agent deployment and security

This guide is updated regularly to reflect the latest OpenClaw versions, security patches, and best practices. Last updated August 12, 2026.