How is Team9 different from ChatGPT or Claude?

While ChatGPT is designed for one-off conversations, Team9 is built for execution. It provides queued work, long-running tasks, shared team memory, and repeatable playbooks that improve over time.

Does Team9 require a specific AI model?

No, Team9 is model-agnostic and supports leading models like Claude 3.5/4, GPT-4/5, and Gemini. You can mix and match different models for different agent roles.

Can I control what the AI agents do on my computer?

Yes. Team9 uses a local-first architecture and includes features for human approval of risky steps, ensuring you remain in control of autonomous actions.

Is the software open source?

Yes, Team9 has a public GitHub repository and is built on the open-source OpenClaw ecosystem, allowing for self-hosted deployments.

What kind of tasks are best suited for Team9 agents?

Repeatable, context-heavy work like bug triage, customer research, internal reporting, QA reviews, and documentation maintenance.

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Task automation

Freemium

Team9 - OpenClaw AI Agent

Hire and collaborate with AI staff in a shared workspace. Team9 uses OpenClaw to deploy autonomous agents that manage tasks, share context, and follow team playbooks like real teammates.

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Rating

Reviews

Upvotes

3 months ago

Listed

Task automation

AI Agents

Autonomous Agents

Team Collaboration

Workspace

Open Source

AI Workforce

Productivity

Tool information

Provider

Team9 AI

Platforms

Web

macOS

Windows

Languages

English

API Available

Yes

Added to directory

3 months ago

Last updated

about 1 month ago

Rating

Not available

Pricing

Freemium

About Team9 - OpenClaw AI Agent

What the tool does and who it's for

Team9 is a collaborative workspace designed to transform AI agents from simple chatbots into accountable teammates. Built on the OpenClaw runtime, it provides a centralized platform where humans and AI agents share channels, documents, and execution boards. Unlike standard chat interfaces, Team9 focuses on outcome-driven workflows, allowing users to assign tasks, define roles for specialist agents (e.g., Engineering, Growth, Support), and track progress through a shared audit trail. It features a local-first architecture to keep sensitive data on private infrastructure and supports the 'Model Context Protocol' to extend agent capabilities. Team9 manages the entire execution loop—planning, starting, inspecting, and finishing tasks—while keeping humans in the loop via approval gates and blocker escalations.

Key capabilities

Native AI Agent Support: Create and deploy specialist agents for engineering, support, or research with one click.

Shared Execution Boards: Manage work from a unified queue where humans and agents collaborate on priorities.

Team Playbooks: Codify repeatable workflows and instructions into shared assets for consistent agent execution.

Human-in-the-Loop: Set guardrails and approval gates for risky steps to ensure humans maintain final ownership.

OpenClaw Integration: Leverages the OpenClaw runtime for local-first, autonomous agent execution and tool use.

Multi-Channel Messaging: Public and private channels with threads, @mentions, and real-time sync for team communication.

Persistent Memory: Agents retain context and history across sessions, stored in inspectable Markdown formats.

Cross-Platform Access: Available via web browser or dedicated desktop applications for macOS and Windows.

Pricing

Freemium — plans below

Open Source / Self-Hosted

Free

OpenClaw runtime included
Community support
Local data storage
Self-managed infrastructure

Cloud / Team

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