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<h1 align="center"> <img src="./docs/images/avernet-readme-header.png" alt="Avernet" width="70%" /> </h1><p align="center"><strong>Avernet is an open-source infrastructure layer for building and operating persistent, coordinated, multi-agent systems at organizational scale.</strong></p><p align="center">Where agents live, connect, coordinate, execute, and evolve together.</p><p align="center"> <a href="LICENSE"><img src="https://img.shields.io/badge/License-Apache%202.0-blue.svg" alt="License" /></a> <a href="README.zh-CN.md"><img src="https://img.shields.io/badge/README-zh--CN-green.svg" alt="README zh-CN" /></a> </p><p align="center"> <a href="#quick-start">Quick Start</a> | <a href="#capabilities--status">Capabilities & Status</a> | <a href="#demo">Demo</a> | <a href="#why-avernet">Why Avernet</a> | <a href="#architecture">Architecture</a> | <a href="#integration">Integration</a> | <a href="#documentation">Docs</a> </p>

Overview

Avernet provides the infrastructure needed to run persistent, coordinated, and heterogeneous agent systems across applications, runtimes, and human-agent workflows.

It is built for teams that need to:

• run multiple agents together, not just isolated single-agent demos
• connect heterogeneous runtimes, plugins, and bot platforms
• support shared context, governed execution, and long-lived collaboration
• operate human-agent collaboration in real environments

Production-tested at Ant Group — As of early July 2026, Avernet supports multi-agent deployments across 12 business groups (BGs), with a 90%+ task completion rate in measured multi-agent workflows.

Capabilities & Status

Status note: All core capability areas are deployed internally in production environments. Public open-source coverage varies by component and is being released incrementally.

Legend: Available = usable in the public repo now · Partial = partially public · In progress = being opened or integrated · Planned = intended but not yet public

• Trusted core
  
  Identity, auth, permissions, security, audit, and lifecycle management for agents and participants.

• Execution infrastructure
  
  Support for heterogeneous agent engines, bot-as-a-service runtimes, containers, clusters, and operational runtimes.

• Agent coordination network
  
  Discovery, relationship building, team formation, routing, collaboration, and governance across multiple agents.

• Shared intelligence and evolution
  

  Bot diagnosis, repeatable Bench evaluation, goal- or diagnosis-driven optimization, and recoverable Pack versions are available through AgentEvolve. Orchestration is available via the Avernet coordination layer. Context and memory remain planned.

• Application building blocks
  
  Agent apps, canvas apps, workflows, and domain-specific extensions built on top of Avernet. Workflow orchestration is available through TaskGuard.

Quick Start

Clone the repository:

git clone https://github.com/inclusionAI/Avernet.git
cd Avernet

Recommended local setup

./scripts/singlebox.sh install-tools
./scripts/singlebox.sh

This starts a local Avernet stack with:

• Avernet process
• frontend workbench
• 5 local test bots

Open the frontend at:

http://127.0.0.1:8000/

For Docker and advanced setup options, see:

• Quick Start
• Docker Guide
• Dependencies

Demo

The current public demo is intended to show:

• local onboarding and coordination flow
• workbench interaction
• integration of local test bots
• a reproducible starting point for public evaluation

It is not intended to fully demonstrate all production-scale properties of Avernet, such as large-scale connection envelopes, permission isolation, audit depth, failure recovery, or long-horizon organizational collaboration.

<p align="center"> <video src="https://github.com/user-attachments/assets/f3fc4b52-4d23-4a73-b618-fe0110e2f2fb" width="80%" controls></video> </p><p align="center"> <img src="./docs/images/group.jpg" alt="Group coordination" width="80%" /> </p>

Why Avernet

As agent systems scale, teams often hit the same four bottlenecks:

• Cannot find — capabilities are hard to discover
• Cannot align — apparent consensus hides real misalignment
• Cannot run fast — execution depends on human relay
• Cannot retain — knowledge does not accumulate as organizational capability

Avernet is built to address these problems with infrastructure for persistent agents, structured coordination, governed execution, and compounding organizational memory.

<p align="center"> <img src="./docs/images/organizational-problems.jpg" alt="Organizational alignment problems" width="80%" /> </p>

Architecture

   +----------------------------+  +----------------------------+  +----------------------------+
   | Local Agents               |  | Agent Runtime              |  | Existing Bot Platform      |
   | Plugin mode                |  | /ws/bot runtime            |  | Downlink gateway           |
   +-------------+--------------+  +-------------+--------------+  +-------------+--------------+
                 |                               |                               ^
                 |                               |                               |
                 +---------------+---------------+                               |
                                 | agent -> BCS:                                 | BCS -> platform:
                                 | connect / register / receive / report         | dispatch / schedule / callback
                                 v                                               |
+----------------------------------------------------------------------------+     +-------------------+
| Avernet / BCS                                                              |     | bcs-cli / tools   |
| connection / registration / routing / delivery / sessions                  |<--->| onboard / inspect |
| collaboration state / multi-bot network management                         |     |                   |
+----------------------------------------------------------------------------+     +-------------------+

Integration

Avernet does not lock you into a single agent engine. It supports two integration paths for connecting agents, runtimes, and existing bot platforms into one collaboration network.

Integration path	Best for	Current capability	Docs
Plugin integration	OpenClaw, local agent runtimes, custom bot processes	Agents actively connect to Avernet through a plugin or runtime for registration, onboarding, message receiving, and result reporting.	Bot Integration Guide, Local OpenClaw from source
Gateway integration	Existing bot platforms, multi-instance agent services, external scheduling systems	Avernet dispatches tasks to an external platform, which schedules agents and reports results back when work completes.	Bot Platform Integration

Repository layout

ocb/
├── .env.example
├── Dockerfile.ocb
├── docker-compose.yml
├── docs/
├── scripts/
├── src/
│   ├── frontend/
│   ├── bcs/
│   └── plugin/
├── tests/
├── AGENTS.md
├── README.md
└── README.zh-CN.md

Documentation

• Quick Start
• Dependencies
• Docker Guide
• Bot Platform Integration
• Bot Integration Guide
• Local OpenClaw from source
• Architecture docs
• BCS Development Guide
• AgentEvolve
• TaskGuard

Security

Do not commit secrets, tokens, cookies, private keys, private service endpoints, local databases, runtime logs, or machine-specific configuration.

If credentials have already been committed, revoke or rotate them before cleaning repository history.

License

This project is licensed under the Apache License 2.0.