Relevance AI Tutorial: Build No-Code AI Agents
In this comprehensive tutorial, Ben AI demonstrates how to create no-code AI agents using Relevance AI. He begins by explaining what AI agents are, their difference from AI automations, and when to use each. AI agents can make decisions and interact intelligently with their environment, making them suitable for more complex and less predictable workflows compared to rule-based AI automations.
Ben then provides an overview of Relevance AI, highlighting its no-code nature, user-friendly interface, and powerful features like tool-building, software integrations, and multi-agent systems. He emphasizes the platform’s capabilities in managing AI agents, tracking usage, and creating complex workflows without needing to write code.
The core of the tutorial focuses on building an AI inbound lead manager agent. Ben walks through the entire process, from setting up the agent and its core instructions to building and configuring tools for lead research, CRM updates, and decision-maker identification. He demonstrates how to use Relevance AI’s built-in tools, such as Google search API, LinkedIn scraper, and web scraper, to gather and process data.
Ben also explains how to integrate the AI agent with external software using APIs, specifically showing how to trigger the agent from make.com. He highlights the importance of conditions in tool-building to ensure the workflow runs smoothly without errors.
Throughout the video, Ben shares practical tips and best practices from his experience, making it easier for viewers to understand and implement their own AI agents. He also provides access to templates and tools he has created to simplify the process.
The tutorial concludes with a demonstration of how to deploy the AI agent and manage it through Relevance AI’s interface, ensuring that users can deliver professional and efficient AI solutions to their clients or within their own organizations.