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79% of executives are already adopting AI agents, although 19% of firms struggle with coordination.1 They cannot manage agents across different applications. Agentic orchestration offers the solution.

Explore agentic orchestration is, its patterns, and the top frameworks that enable multi-agent collaboration.

What is agentic orchestration?

Agentic orchestration coordinates autonomous AI agents within a unified system to complete complex tasks and structured tasks across multiple systems and domains. It builds on earlier forms of automation by enabling multi-agent orchestration, where multiple agents collaborate under an orchestration layer that governs communication, task planning, and execution.

Unlike static automation scripts, agentic orchestration leverages generative AI and AI models to adapt to context, minimize the need for human intervention, and enable seamless execution across diverse systems.

Core principles 

  1. Autonomy: Agents can act independently within their defined roles, supported by function calling to external systems.
  2. Collaboration: Multiple AI agents communicate to resolve complex problems, distribute multiple tasks, and achieve end-to-end automation.
  3. Alignment: Systems maintain consistent objectives and ensure compliance with organizational and regulatory requirements in highly regulated industries.
  4. Observability: Logs, monitoring tools, and evaluations enable continuous monitoring and continuous optimization.
  5. Human oversight: Human-in-the-loop approaches combine automation with human input in high-risk or ambiguous contexts.

Orchestration patterns

Agentic orchestration can be categorized into several patterns based on how agents are coordinated within a system. These patterns determine the flow of tasks, the communication between agents, and the overall system architecture.

10:T36a2,

Note that these tools are listed based on the number of GitHub stars they received.

Compare these frameworks and learn their core capabilities:

Agentic orchestration applications

Agentic orchestration is the critical capability that transforms individual agents into a cohesive, goal-oriented system. The following are real-world applications where multi-agent systems coordinate to deliver business value.

Business processes

Agentic orchestration enables end-to-end automation across multiple departments and systems. It coordinates specialized agents to handle complex, multi-step workflows without manual handoffs.

Explore AI agents for workflow automation

Supply chain

Agentic orchestration enhances supply chain management by coordinating multiple, specialized agents to manage and optimize a complex network of planning, sourcing, logistics, and inventory management.

Enterprise systems

Agentic orchestration provides the core logic for AI-driven processes that require seamless collaboration across different enterprise platforms, such as ERP, CRM, and RPA.

Explore how AI agents are used in enterprise systems, such as:

Banking and Financial Services

In this sector, orchestration is utilized for complex, risk-sensitive workflows that necessitate multiple agents collaborating to ensure accuracy and compliance.

Check out how AI agents and agentic LLMs are utilized in finance:

Energy and utilities

Agentic orchestration allows for the management of highly distributed and complex systems, such as power grids and workforce management, by enabling specialized agents to communicate and act in real-time.

Telecom

In telecom, orchestration is used to manage and automate large-scale, complex networks and customer-facing operations.

Benefits

Challenges

Further reading

Discover more on Agentic AI by checking out:

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Centralized orchestration

In this pattern, a single manager or router agent is responsible for assigning tasks, controlling the workflow, and ensuring that objectives are met. The manager acts as a central hub, directing tasks to specialized agents based on predefined rules or a dynamic plan.

Specific patterns within this category include:

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Decentralized orchestration

This pattern eliminates the single point of control, enabling multiple agents to interact directly and complete a complex task. This approach enhances resilience and offers greater flexibility for collaborative problem-solving.

Specific patterns within this category include:

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Federated Orchestration

This pattern is helpful for highly regulated or distributed environments. It enables collaboration across different organizational silos or systems while maintaining data governance and security. It often combines elements of both centralized and decentralized approaches to manage a wider network of agents and systems.

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Tools and frameworks

Several AI agent frameworks provide the infrastructure for agentic workflows and multi-agent orchestration. Some of them include:

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