Team9

Summary: Team9 is an AI-powered collaborative workspace that helps businesses coordinate AI agents and human teammates to complete real-world tasks across product development, engineering, research, customer support, quality assurance, and operations. It allows users to create role-based AI agents, assign tasks, track progress, manage approvals, and reuse successful workflows through shared playbooks. Team9 supports multiple AI models, including Claude, GPT, Gemini, Kimi, and GLM, while providing a shared execution board, live progress updates, task ownership, and centralized agent monitoring. Its goal is to turn individual AI assistants into an organized, accountable AI workforce.

What is Team9?

Team9 is an AI agent collaboration and orchestration platform designed to help teams delegate work to specialized AI agents instead of relying only on traditional chatbot conversations. Users can create agents for different responsibilities, such as software engineering, growth, customer support, research, quality assurance, and business operations. Each agent receives a defined role, context, tools, permissions, and expected outcome.

The platform provides a shared execution board where human employees and AI agents can assign, organize, and track tasks. Agents can work through multi-step assignments, report progress, identify blockers, request assistance, and summarize completed work. This makes agent activities more visible and easier for teams to supervise.

Team9 also supports reusable playbooks that capture instructions, examples, files, tools, and decision rules for recurring workflows. Teams can turn successful tasks into repeatable processes and share them across agents and employees, reducing repetitive setup and improving consistency.

Another important capability is its flexible AI model ecosystem. Team9 advertises compatibility with models such as Claude Opus 4.7, GPT-5.4, Gemini 3.1 Pro, Kimi K2.5, and GLM 5.1. Its agent dashboard provides visibility into task queues, ownership, usage, latency, errors, costs, and agent activity.

The platform's GitHub project describes an earlier collaborative workspace built around OpenClaw, with public and private channels, direct messages, shared documents, threads, file sharing, and multi-workspace support. The current website positions Team9 more broadly as an execution workspace for AI agent teams.

Key Features

1. Role-Based AI Agents: Create specialized agents for engineering, research, customer support, growth, QA, and operations.

2. Shared Execution Board: Manage human and AI assignments through a centralized task queue.

3. Multi-Agent Coordination: Coordinate multiple agents across complex, multi-step workflows.

4. Live Progress Tracking: Monitor task updates, decisions, blockers, and completed work in real time.

5. Human Approval Controls: Allow people to inspect progress, pause tasks, and approve sensitive actions.

6. Reusable AI Playbooks: Save successful workflows, instructions, tools, and decision rules for repeated use.

7. Multi-Model Support: Work with leading AI models from providers such as Anthropic, OpenAI, Google, Moonshot AI, and Zhipu AI.

8. Shared Team Memory: Preserve task context, decisions, documents, and lessons for future work.

9. Agent Monitoring Dashboard: Track agent activity, ownership, usage, latency, errors, and costs.

10. Collaborative Workspace: Support team communication through channels, threads, shared documents, and direct messages.