Virgent AI logoVirgent AI

Multi-Agent System

The future of business automation: Agent-to-Agent (A2A) coordination where specialized agents collaborate to complete complex workflows. Coordination agents orchestrate task agents with different MCP integrations and capabilities.

Orchestrate your agents

From coordinator to task agents, we design robust A2A patterns and guardrails.

Design my MAS

Architecture

Multi-Agent A2A Coordination
┌─────────────────┐   A2A      ┌──────────────┐
│ Producer Agent  │ ◄─────────► │ Research     │
│ (Coordinator)   │             │ Agent        │
└─────────┬───────┘             └──────────────┘
          │ A2A                          │ MCP
          ▼                              ▼
┌─────────────────┐             ┌──────────────┐
│ Design Agent    │             │ Web APIs     │
└─────────┬───────┘             │ Knowledge    │
          │ A2A                 │ Databases    │
          ▼                     └──────────────┘
┌─────────────────┐   MCP      ┌──────────────┐
│ Animation Agent │ ◄─────────► │ Creative     │
└─────────────────┘             │ Tools        │
                                └──────────────┘

A2A Capabilities

  • • Cross-agent task coordination
  • • Workflow orchestration and dependencies
  • • Real-time status synchronization
  • • Resource allocation and scheduling
  • • Model-agnostic agent communication

Future Vision

Companies will have agent representatives capable of engaging with users and other company agents directly. Your scheduling agent books meetings, while a producer agent coordinates research, design, and animation via specialized task agents with different MCP integrations.

Live A2A Demo

Watch agents coordinate a complex creative project workflow

This demo shows how a Producer Agent coordinates with specialized task agents to complete a complex creative project using A2A communication.

Orchestrate your agents

From coordinator to task agents, we design robust A2A patterns and guardrails.

Design my MAS

Real Implementation

Coordination Agents

  • • Workflow orchestration and planning
  • • Resource allocation and scheduling
  • • Cross-agent communication protocols
  • • Dependency management and tracking
  • • Performance monitoring and optimization

Task Agents

  • • Specialized MCP tool integrations
  • • Domain-specific capabilities
  • • Independent task execution
  • • Status reporting to coordinators
  • • Model-agnostic implementations

A2A Communication

  • • Inter-agent messaging protocols
  • • Shared context and memory
  • • Collaborative decision making
  • • Scalable agent networks
  • • Cross-company agent interaction

Real-World Example

Cadderly: Multi-Agent Knowledge System

See this architecture in action with our knowledge management platform

Cadderly demonstrates multi-agent coordination in production. Multiple specialized agents work together to index, process, and serve institutional knowledge across organizations.

Agent Coordination

  • • Ingestion agents process documents
  • • Analysis agents extract insights
  • • Query agents serve information
  • • Coordination agent orchestrates workflow

MCP Integrations

  • • Slack, Teams, Discord
  • • Google Drive, SharePoint
  • • Notion, Confluence
  • • Custom knowledge bases

The Agent Economy Future

Company Agent Representatives

Every company will have agent representatives capable of:

  • • Engaging with customers autonomously
  • • Negotiating with other company agents
  • • Managing internal workflows and processes
  • • Coordinating cross-company collaborations

Inter-Company A2A

Agent-to-agent business interactions will enable:

  • • Automated vendor negotiations
  • • Real-time supply chain coordination
  • • Instant partnership agreements
  • • Seamless service integrations

Ready to build your multi-agent system?

Design and implement custom multi-agent architectures with A2A coordination, MCP integrations, and scalable agent networks for your business workflows.