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    Decorative pattern
    Decorative pattern
    1. Home
    2. Concepts & Definitions
    3. Agent Orchestrator

    Agent Orchestrator

    System that coordinates multiple AI agents to work together on complex tasks, managing task distribution, parallel execution, and result synthesis. Key component in ASMR and other multi-agent systems.

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    Websitewww.emergence.ai
    PublishedMar 24, 2026

    Categories

    1 Item
    Concepts & Definitions

    Tags

    3 Items
    #Multi Agent#Orchestration#Coordination

    Similar Products

    6 result(s)
    Semantic Kernel

    Open-source SDK from Microsoft that enables developers to build AI agents and integrate LLMs into applications with support for multi-agent orchestration, function calling, and memory management across C#, Python, and Java.

    ASMR Technique
    Featured

    Agentic Search and Memory Retrieval technique by Supermemory using parallel reader agents and search agents that achieved ~99% accuracy on LongMemEval benchmark.

    Plan-Execute-Verify Framework

    Agent orchestration pattern used by Emergence AI that plans tasks, executes with specialized agents, and verifies results to achieve reliable autonomous workflow automation.

    Pluggable Orchestration Strategies

    Modular agent coordination patterns in AG2 allowing developers to swap orchestration logic without changing agent code, enabling flexible multi-agent workflows.

    CrewAI
    Featured

    Leading open-source framework for orchestrating autonomous AI agent crews with production-ready workflows combining collaborative intelligence through Crews and precise control through Flows.

    AG2

    Open-source multi-agent AI framework (formerly Microsoft AutoGen) with event-driven core, async-first execution, and pluggable orchestration strategies for building AI agent systems.

    Overview

    An Agent Orchestrator is a system that coordinates multiple AI agents to work together on complex tasks, managing their interactions, task distribution, and result synthesis.

    Key Responsibilities

    • Task Decomposition: Breaking complex queries into subtasks
    • Agent Assignment: Routing subtasks to appropriate specialized agents
    • Parallel Execution: Coordinating concurrent agent operations
    • Result Synthesis: Combining outputs from multiple agents
    • Error Handling: Managing failures and retries
    • Resource Management: Optimizing agent utilization

    Examples in Production

    ASMR (Supermemory)

    Deployes an agent orchestrator utilizing 3 parallel reader agents and 3 parallel search agents for memory retrieval.

    Emergence AI

    Uses a plan-execute-verify framework to orchestrate self-improving agents and dynamically created variant agents.

    AG2/AutoGen

    Provides orchestration patterns for multi-agent conversations and task execution.

    Design Patterns

    • Hierarchical: Master agent delegates to worker agents
    • Peer-to-peer: Agents communicate directly
    • Pipeline: Sequential agent execution
    • Parallel: Concurrent agent execution with result merging

    Challenges

    • Agent coordination complexity
    • State management across agents
    • Handling conflicting outputs
    • Performance optimization
    • Cost management

    2026 Trends

    Agent orchestration is becoming standardized through frameworks like AG2, LangGraph, and CrewAI, with built-in orchestration primitives.

    Pricing

    Pattern/concept, implemented through various frameworks.