OpenClaw is powerful, but it's single-player by default. CatsAndClaws transforms it into a collaborative team platform. Create shared workspaces, visualize multi-agent fleets, and orchestrate workflows together in real-time.
Out of the box, OpenClaw is designed for a single developer running a single agent on a local machine.
We built the missing collaboration layer for OpenClaw. A true multi-user environment for AI-forward organizations.
Everything your team needs to scale AI operations safely and effectively.
Visualize your entire AI workforce on a shared 2D office map. See which agents are active, who is collaborating, and where tasks are flowing in real-time.
Create dedicated zones for different teams (Engineering, Marketing, Sales). Agents in the same zone share context and memory efficiently.
Multiple human users can log in, assign tasks, and monitor the same fleet of AI agents simultaneously. No more SSH key sharing.
Design complex workflows where a "Product Manager" agent delegates sub-tasks to "Developer" and "QA" agents automatically.
Isolated workspaces with their own memory and session stores ensure data privacy between different departments and projects.
One gateway for your entire organization. Connect Slack, Discord, and Telegram channels to specific agent teams flawlessly.
| Feature | Standard OpenClaw | CatsAndClaws for Teams |
|---|---|---|
| User Access | Single User (Local) | Multi-User (Cloud/Prem) |
| Workspace Visibility | Terminal / CLI | Shared Visual Dashboard |
| Agent Coordination | Manual Scripting | Drag-and-Drop Orchestration |
| Memory & Context | Single Shared Memory | Isolated per Team/Agent |
| Task Assignment | 1:1 Interaction | Team-Based Routing |
| Infrastructure | Self-Hosted / Laptop | Managed Enterprise Cloud |
Create a content factory where a "Strategist" agent briefs a "Writer" agent, who hands off to an "SEO" agent for review—all visible to your human team.
Deploy a "Support Bot" that triages tickets and escalates complex issues to a "Junior Dev" agent for initial code fixes.
Manage distinct AI agent fleets for different clients. Keep data completely isolated while your team manages everything from one dashboard.
Simulate user feedback with a swarm of "Persona Agents" testing your product features before launch.
Stop working in silos. Bring your team and your AI agents together in one shared, visual workspace.