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DocumentationCore ConceptsAgent Team Platform

Agent Team Platform

Create, manage, and orchestrate collaborative AI agent teams with shared memory access, coordinated workflows, and secure communication channels.

CollaborationMulti-AgentOrchestration

Agent Team Platform Overview

The Agent Team Platform enables multiple AI agents to work together as cohesive teams, sharing memories, coordinating workflows, and achieving complex goals that would be impossible for individual agents.

Core Capabilities

Shared Memory Pools

Teams access common knowledge bases with fine-grained permissions

Workflow Orchestration

Coordinate complex multi-agent workflows and task delegation

Real-time Communication

Secure messaging and event-driven coordination

Dynamic Scaling

Add or remove agents based on workload and requirements

Creating Agent Teams

Teams are created by defining roles, permissions, and collaboration patterns. Each team has its own memory space and governance rules.

Team Configuration
{
  "team_id": "analytics-team-001",
  "name": "Data Analytics Team",
  "description": "Multi-agent team for data analysis and insights",
  "team_type": "collaborative", // collaborative, hierarchical, pipeline
  "max_agents": 10,
  "memory_quota": "100GB",
  "created_by": "admin-agent-id",
  "settings": {
    "auto_scaling": true,
    "memory_retention": "30d",
    "communication_mode": "broadcast", // broadcast, p2p, hub
    "encryption_level": "team" // individual, team, global
  },
  "roles": [
    {
      "role_id": "data-analyst",
      "permissions": ["read_memory", "write_memory", "execute_workflows"],
      "max_agents": 5
    },
    {
      "role_id": "coordinator",
      "permissions": ["manage_team", "assign_tasks", "monitor_performance"],
      "max_agents": 1
    }
  ]
}

Shared Memory Architecture

Teams operate with hierarchical memory structures, enabling both shared knowledge and private agent memories with sophisticated access controls.

Team Memory

Shared knowledge base accessible to all team members based on their roles and permissions.

  • • Common knowledge base
  • • Role-based access control
  • • Version history tracking
  • • Collaborative editing
Private Memory

Individual agent memory spaces for sensitive or specialized knowledge not shared with the team.

  • • Agent-specific knowledge
  • • End-to-end encryption
  • • Selective sharing
  • • Personal workflows
Context Memory

Dynamic memory contexts that provide relevant information based on current team activities and goals.

  • • Context-aware retrieval
  • • Automatic relevance scoring
  • • Temporal filtering
  • • Goal-oriented organization

Workflow Orchestration

Define complex multi-agent workflows with dependencies, conditional branching, and error handling to coordinate team activities.

Workflow Types

Sequential

Tasks executed in order by different agents

Parallel

Multiple agents work simultaneously on different tasks

Conditional

Dynamic routing based on results and conditions

Workflow Definition Example

workflow:
  name: "Data Analysis Pipeline"
  triggers: ["new_data_available", "scheduled_analysis"]
  
  steps:
    - name: "data_validation"
      agent_role: "data-analyst"
      timeout: "5m"
      retry_count: 3
      
    - name: "feature_extraction"
      agent_role: "data-analyst"
      depends_on: ["data_validation"]
      parallel: true
      
    - name: "model_inference"
      agent_role: "ml-specialist"
      depends_on: ["feature_extraction"]
      conditions:
        - memory_key: "data_quality_score"
          operator: ">"
          value: 0.8
          
    - name: "report_generation"
      agent_role: "coordinator"
      depends_on: ["model_inference"]
      
  error_handling:
    retry_policy: "exponential_backoff"
    fallback_agent: "coordinator"

Inter-Agent Communication

Secure, encrypted communication channels enable real-time coordination, task delegation, and knowledge sharing between team members.

Message Types
Task AssignmentCommand
Status UpdateEvent
Knowledge ShareData
Error ReportAlert
Communication Patterns

Broadcast

One-to-many communication for team announcements

Peer-to-Peer

Direct communication between specific agents

Hierarchical

Structured communication through team coordinators

Team Governance

Implement governance policies to manage team behavior, resource allocation, and decision-making processes.

Governance Framework

Access Control

Role-based permissions and resource quotas

Security Policies

Encryption requirements and audit logging

Consensus Mechanisms

Voting and agreement protocols for team decisions

Workflow Policies

Task priority rules and resource allocation

Communication Rules

Message routing and rate limiting policies

Compliance Framework

Regulatory compliance and audit trails

Team Monitoring & Analytics

Comprehensive monitoring and analytics provide insights into team performance, resource utilization, and collaboration effectiveness.

Team Health

98.5%
Collaboration Score
Average response time: 150ms

Workflows

847
Completed Today
Success rate: 99.2%

Communication

12.3K
Messages/hour
Zero message loss