Xiaowen-Jiang

Xiaowen-Jiang / agent-enterprise

Public

Building Your Own AI Company

44
2
100% credibility
Found Mar 29, 2026 at 44 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Python
AI Summary

Agent Enterprise is a framework for building and managing hierarchical teams of AI agents that simulate a company structure, complete with HR, budgets, projects, and tools integration via a web UI and command-line interface.

How It Works

1
👀 Discover Agent Enterprise

You find this exciting project on GitHub that lets you run your own AI company, with smart agents as your employees.

2
💻 Set it up easily

Download and install everything on your computer in a few simple steps, no coding needed.

3
🔗 Connect your AI service

Link your favorite AI account so your agents can think, chat, and get work done.

4
🏢 Build your first team

Choose a ready team template like a small software company, and launch the web dashboard.

5
💬 Give tasks to your team

Chat with your CEO dashboard, assign projects, hire new agents, or watch them collaborate automatically.

6
✨ Watch the magic happen

See your AI employees delegate, code, research, and deliver results in real-time.

🎉 Your AI company thrives

You now have a full team of smart agents handling complex work, saving you time and effort.

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Star Growth

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AI-Generated Review

What is agent-enterprise?

Agent Enterprise lets you spin up an AI company where LLM agents act as employees in a full org chart—complete with managers delegating tasks, workers executing via tools like GitHub and filesystem access, budgets, HR actions (hire/fire/promote), and meetings. Built in Python with LiteLLM for 100+ LLM providers, FastAPI web UI, and MCP protocol for real-world tools, you play CEO: assign projects, approve spends, and watch everything stream live. Solves the chaos of single-agent setups by enforcing hierarchy and visibility for complex workflows like agent enterprise AI discovery.

Why is it gaining traction?

Stands out with CEO-level controls—no black-box agents: real-time streaming, per-agent budgets with cost tracking, and dynamic restructuring mid-run. Hooks developers with seed templates for instant small software companies or personal assistants, plus CLI for quick chats (`agent-enterprise chat`) and exportable YAML configs for sharing orgs. MCP integrations mean agents actually build GitHub apps, manage repos, or handle Gmail without custom glue code.

Who should use this?

AI researchers prototyping multi-agent hierarchies, indie devs building GitHub Copilot agents or portfolio projects from scratch, and startup founders simulating teams for tasks like code reviews or sprint planning. Ideal for those tired of flat agent swarms wanting structured collaboration without enterprise overhead.

Verdict

Promising alpha for agent enterprise experiments (44 stars, active dev, solid README/demos), but 1.0% credibility score flags early maturity—expect bugs in edge cases like long-running tasks. Try the small software company seed if you're into building your own AI house; skip for production. (198 words)

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