Agentic AIMAS

Multi-Agent System

MAS

A multi-agent system (MAS) is an AI architecture where multiple specialized agents collaborate to solve complex tasks. Each agent takes on a clearly defined role and communicates through standardized interfaces — like a well-coordinated expert team working together without human coordination.

Why does this matter?

Many business processes require diverse competencies: a quotation process needs pricing calculations, contract law, and customer history. A multi-agent system mirrors this division of labor — specialized agents work in parallel and jointly deliver results that no single agent could achieve.

How IJONIS uses this

We implement multi-agent systems with CrewAI and LangGraph, with each agent specialized in specific business domains. Orchestration uses defined communication protocols and shared state management — scalable from two to dozens of cooperating agents.

Frequently Asked Questions

When do I need a multi-agent system instead of a single AI agent?

When a process requires diverse expertise or is too complex for a single prompt context. Typical scenarios: end-to-end order processing, quality assurance with review and approval loops, or complex research tasks with fact-checking.

How expensive is a multi-agent system to operate?

Operating costs depend on the number of agents and API calls. By strategically using smaller models for routine tasks and powerful LLMs only for complex decisions, token costs can be reduced by 60-80%.

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