Multi Agents System (MAS) Builder - Build your AI Workforce

Multi-Agent System (MAS)

Build a Multi Agent System

Create your own custom AI assistants that work collaboratively to execute and plan tasks based on your goals.

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Relevance AI

Multi-Agent System

Your AI Team

Create your own multi-agent system.

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Relevance AI

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Chain template name

Categorize and label your data without any human bias Categorize and label your data

Relevance AI

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Customer name

Categorize and label your data without any human bias Categorize and label your data

Relevance AI

Customer name

Categorize and label your data without any human bias Categorize and label your data

Relevance AI

Customer name

Categorize and label your data without any human bias Categorize and label your data

Relevance AI

Customer name

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Relevance AI

Automate collaborative work

Build a collaborative team to working on collaborative problems to achieve collaborative goals.

Recruit a team of specialists

Our no-code builder allows you to distill your processes and knowledge into specialist agents.

Your AI workforce, your process.

Easily add escalation to any process or conversation so you can always be in control where it matters.

Enable agent to agent feedback

Improve the quality control of your AI workforce by enabling agent to agent feedback.

No training on your data.

No training on your data. Your data is never used to train models.

You’re in good hands with us.

Join the thousands of other teams empowering their workforce with AI.

I love building with Relevance and have created some incredibly powerful production workflows for my team and our clients.

Chris Guill

GB Promotions

President

I'm looking at almost every single thing our business does and creating an AI tool or Agents to either improve the process, speed it up or add value in a different way using Relevance.

Michael Viney

Venture Capital Fund

Head of IT

Relevance has been pivotal in my ability to build AI systems for my clients. These include AI Tools like a custom-built LinkedIn Post Generator and AI Agents for conversational workflows.

Nick Roco

StellarStream AI

Founder & CEO

Our team has been blown away by both the raw horsepower and intuitive nature of the Relevance AI platform. Relevance AI's ability to link Google search, website scraping, ChatGPT, Python, and more empowers our team of 4 to operate like a team of 20.

Henry LeGard

Verisoul

Founder & CEO

Relevance AI has been a game-changer for us to rapidly develop LLM powered tools and agents for our clients.

Shane Rosse

Allience App

CTO

Relevance AI's impact on our organization is undeniable. Their combination of innovative tools and agents, supportive team, and constant development makes them a key partner in our AI strategy.

Luke Thompson

Action VFX

COO

Relevance has made solo entrepreneurialism possible for me by allowing me to manage a variety of roles supported by my purpose built agents and teams.

Jake Chamberlin

Teachers Assistant AI

Founder

The team at Relevance AI were a pleasure to work with. They seamlessly integrated my content into their AI platform and were readily available to make any needed adjustments.

Robert Coorey

Archistar.ai

Co-Founder & CEO

Building a Multi-Agent System

What is a Multi-Agent System?

A multi-agent system (MAS) is a group of intelligent agents that interact and work together towards achieving common goals. Agents in a MAS combine their individual capabilities and knowledge to collaborate on solving problems that are beyond the scope of any individual agent.
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Some key characteristics of a multi-agent system are:
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Composed of multiple autonomous agents
Agents have particular capabilities and expertise
Agents communicate and coordinate with other agents
Decentralized control and decentralized data
Emergent global behavior from local agent interactions

Benefits of a Multi-Agent System

Some of the key benefits of developing a multi-agent system are:

Modularity - Agents can be added or removed as needed
Robustness - System continues operation if some agents fail
Scalability - Easy to expand system by adding agents
Flexibility - Agents can be customized for different roles
Faster problem solving - Parallelization of work across agents
Broader intelligence - Combination of multiple skill sets

How to Build a MAS with Relevance AI

Relevance AI provides a no-code platform for easily building intelligent multi-agent systems. Here are the key steps:

Identify the Goals and Scope - Define the objectives and outcomes you want to achieve an map out different tasks and workflows required.
Create and Train Agents - Use pre-built agents or create custom agents. Train agents on specific domains and give them specialized skills
Define Agent Interactions - Model how agents will communicate and work together
Deploy and Iterate - Deploy your multi-agent system. Monitor performance and add/adjust agents as needed