Relevance AI

Relevance AI is a platform for building and running AI agents and multi-agent teams (an AI workforce) to complete tasks. It includes tools that agents can use, and workflows to guide how agents take actions in sequence.

AI Agent PlatformCloud-hostedDeveloper-friendly

Overview

What is Relevance AI?

Relevance AI is a platform for building and running an "AI workforce" made up of AI agents and multi-agent teams that can complete tasks.

Instead of coding everything from scratch, you configure agents and connect them to tools/workflows so they can take steps, pass information, and produce outputs in a structured way.

In practice, teams use Relevance AI to create AI agent workflows where agents follow a process (often using tools and integrations) to complete repeatable business tasks more reliably than a one-off chat prompt.

Key Features

AI agents and multi-agent teams: Build agents and teams (AI workforce-style) that can complete tasks
Tools and workflows: Define reusable tools/workflows agents can run to take consistent actions
Orchestration for AI agent workflows: Coordinate steps, handoffs, and logic across a task flow rather than relying on a single prompt
Developer resources (API/SDK): Relevance AI provides developer documentation/SDK resources for building on the platform
Platform administration features: Includes org/team controls like roles/permissions (where configured) for managing usage in a workspace

Common Use Cases

•Building AI agent workflows that follow a repeatable process to complete tasks (often as an "AI workforce")
•Creating task-focused agents that use tools/workflows to take actions consistently (instead of ad-hoc prompt runs)
•Orchestrating multi-step work where agents hand off outputs to other agents/tools as part of a broader flow

Who It's For

Relevance AI is best suited for advanced users, builders, and teams who want to design and run AI agents (including multi-agent teams) as a structured system, and who value having platform features plus developer docs/SDK support for deeper implementations.

How It Works

Core Functionality

You create and run an "AI workforce" by defining agents (and teams) and configuring how work is executed through the platform.

AI Agent Capabilities

Agents can be set up to complete tasks, and teams can be structured as multi-agent systems where responsibilities are split and coordinated.

Integrations and Data Processing

Agents can use tools/workflows (and integrations where configured) to move information through a task process and produce outputs.

Key Differentiators

✓Purpose-built for agents/teams ("AI workforce") rather than general app-to-app automation
✓Supports multi-agent systems as a first-class concept
✓Includes tools/workflows to standardize how agents take actions
✓Provides developer docs/SDK for deeper builds on the platform

Getting Started

Read the official Relevance AI documentation

Quick Start

1Start in the official docs and review core concepts (agents, workforce, tools/workflows)
2Create your first agent (or small team) and define the task it should complete
3Connect the agent to the tools/workflows it needs, then test and iterate

Try Relevance AI

When to Use Relevance AI

Relevance AI vs n8n

Relevance AI is designed around AI agents and multi-agent teams (AI workforce-style). n8n is primarily a workflow automation/orchestration tool; both can support AI agent workflows, but they're built for different core use cases.

Learn more about n8n

Relevance AI vs LangChain

Relevance AI is a hosted platform for building/running agents and teams; LangChain is a developer framework that typically requires coding to assemble and run agent systems.

Learn more about LangChain

Related Resources

Back to AI Agent Builders

Related Tools

n8n Make LangChain

Last updated: December 2025

AI Agent Builder · Workflow Automation Tool