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What is nexora-ai-platform?

lb08111/nexora-ai-platform — explained in plain English

Analysis updated 2026-05-18

33PythonAudience · ops devopsComplexity · 4/5Setup · hard

In one sentence

An enterprise workspace for sharing AI agents across a team with access control, approval workflows, and full audit logging.

Mindmap

mindmap
  root((repo))
    What it does
      Shared AI agents
      Access control
      Audit trails
    Tech stack
      Python
      React
      FastAPI
      PostgreSQL
    Use cases
      Manage team AI access
      Track token usage
      Approve new tools
    Audience
      IT admins
      Operations teams

Code map

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filefunction / class

What do people build with it?

USE CASE 1

Give a team controlled access to shared AI agents with per-user permissions.

USE CASE 2

Track who used which agent, model, and how many tokens they consumed.

USE CASE 3

Require admin approval before new tools or skills are installed.

USE CASE 4

Keep a full audit log of chats, tool calls, and config changes for compliance.

What is it built with?

PythonReactViteFastAPIPostgreSQL

How does it compare?

lb08111/nexora-ai-platform410979729/scope-recallarahim3/mlx-dspark
Stars333333
LanguagePythonPythonPython
Setup difficultyhardmoderateeasy
Complexity4/53/53/5
Audienceops devopsdeveloperdeveloper

Figures from each repo's GitHub metadata at analysis time.

How do you get it running?

Difficulty · hard Time to first run · 1h+

Requires PostgreSQL 16 plus a running QwenPaw core to layer the enterprise features on top of.

So what is it?

Nexora AI Platform is an enterprise workspace where multiple team members can share AI agents under controlled access and with full audit trails. It is built on top of QwenPaw, an open-source multi-agent framework, and adds the access control, governance, and usage tracking layers that organizations need before deploying AI tools internally. The base QwenPaw layer includes AI agents that hold conversations, run scheduled tasks, connect to messaging platforms such as DingTalk, Feishu, WeChat, Discord, Telegram, Slack, and others, and call external tools or custom skills. Agents can use cloud AI providers including OpenAI, DeepSeek, and Claude, or run models locally through tools like Ollama or LM Studio. A built-in code editor with a file tree, tabbed interface, and diff review is also included. Nexora adds enterprise features on top: a two-role system with admin and operator accounts, per-user agent grants that control which AI agents each person can access, an approval workflow for installing new tools or skills that flags high-risk actions for admin review, and a full audit log stored in PostgreSQL that records authentication events, chat messages, tool calls, and configuration changes. Token usage per user, agent, and model is tracked and shown in a dashboard. The architecture keeps Nexora-specific code in separate directories from the upstream QwenPaw core so that core updates can be merged without conflict. The frontend is built with React and Vite. The backend runs on FastAPI with PostgreSQL 16 for all enterprise data storage. The README describes the platform as a central hub connecting intelligent agents with the people and tools that run a business, under controlled governance. The full README is longer than what was shown.

Copy-paste prompts

Prompt 1
Walk me through how Nexora AI Platform's admin and operator roles differ.
Prompt 2
Explain how the approval workflow for new tools works in this project.
Prompt 3
Show me how the audit log is stored and what events it captures.
Prompt 4
Help me set up FastAPI and PostgreSQL locally to run Nexora AI Platform.
Prompt 5
Describe how Nexora keeps its code separate from the upstream QwenPaw core.

Frequently asked questions

What is nexora-ai-platform?

An enterprise workspace for sharing AI agents across a team with access control, approval workflows, and full audit logging.

What language is nexora-ai-platform written in?

Mainly Python. The stack also includes Python, React, Vite.

How hard is nexora-ai-platform to set up?

Setup difficulty is rated hard, with roughly 1h+ to a first successful run.

Who is nexora-ai-platform for?

Mainly ops devops.

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