Arahi AI

Q: When should I use multi-agent systems vs a single agent?

Use multi-agent systems for complex processes that involve distinct specialized skills, require parallel processing, or benefit from modular architecture. A single agent is sufficient for focused, straightforward tasks.

Q: How do agents communicate with each other?

Agents communicate through shared memory, message queues, or orchestration layers. Arahi AI handles inter-agent communication automatically, so you only need to define each agent role and the desired workflow.

Q: Is there a limit to how many agents can work together?

Practically, there is no hard limit. However, coordination overhead increases with the number of agents. The optimal number depends on the complexity of your process and how naturally it divides into specialized roles.

Q: Can different agents use different tools?

Yes. Each agent can be connected to its own set of tools and data sources. A research agent might use web scraping tools, while a CRM agent uses your Salesforce integration, and they share results through the coordination layer.

AI Concept

What is Multi-Agent Systems?

Learn what multi-agent systems is, how it works, key benefits, real-world examples, and how it relates to modern AI automation platforms.

Definition

Multi-agent systems (MAS) are architectures where multiple AI agents work together, each specializing in different tasks or domains, to solve complex problems that no single agent could handle effectively alone. Agents communicate, coordinate, and collaborate to achieve shared goals.

Detailed Explanation

Just as organizations divide work among specialized teams, multi-agent systems divide complex automation across specialized agents. A sales pipeline automation might involve a research agent, a lead scoring agent, an outreach agent, and a scheduling agent, each excelling at its specific role while coordinating with the others.

Multi-agent architectures offer several advantages over monolithic systems. Each agent can be optimized for its specific task, agents can work in parallel to improve throughput, the system is more resilient because a failure in one agent does not bring down the entire system, and new capabilities can be added by introducing additional agents.

Coordination between agents is managed through message passing, shared memory, or an orchestration layer that routes work between agents. The orchestrator ensures that agents work in the right sequence, share necessary context, and handle handoffs smoothly.

How Arahi AI Makes This Work for You

Arahi AI supports multi-agent workflows where you can deploy multiple specialized agents that work together. For example, you might have a customer support triage agent that routes tickets to specialized agents for billing, technical support, and general inquiries. The platform handles inter-agent communication and coordination automatically, ensuring seamless handoffs and shared context.

Key Benefits

Why multi-agent systems matters for your business.

Specialized Excellence

Each agent is optimized for its specific task, delivering better results than a generalist system trying to do everything.

Parallel Processing

Multiple agents work simultaneously on different aspects of a problem, dramatically reducing end-to-end processing time.

System Resilience

If one agent encounters an issue, others continue operating. The system gracefully handles partial failures without complete downtime.

Modular Scalability

Add new capabilities by deploying additional specialized agents without rebuilding existing systems.

Real-World Examples

How businesses use multi-agent systems in practice.

Sales Pipeline Automation

A research agent identifies prospects, a qualification agent scores them, a personalization agent crafts custom outreach, and a scheduling agent books meetings. Each agent excels at its specialty.

Content Production System

A research agent gathers information, a writing agent produces content, an editing agent reviews for quality, and a distribution agent publishes across channels.

Customer Service Center

A triage agent classifies incoming requests, specialized agents handle different request types, and an escalation agent manages complex cases that require human attention.