Master Relevance AI with our step-by-step tutorial, detailed feature walkthrough, and expert tips.
Sign up at app.relevanceai.com and explore the dashboard Create your first agent using the visual builder or clone a template from the Marketplace Connect knowledge sources by uploading documents or syncing from supported sources Build custom tools using the no
code tool builder to integrate with your APIs and business systems Test your agent in the chat interface and configure autonomy levels and approval workflows Deploy via triggers, scheduled runs, API, or embedded interfaces where supported
💡 Quick Start: Follow these 2 steps in order to get up and running with Relevance AI quickly.
Explore the key features that make Relevance AI powerful for ai agents & autonomous workflows workflows.
Configure agents with skills, knowledge bases, and conversation patterns through a visual interface. Define agent roles, set autonomy levels, and deploy without writing code.
Creating a sales development agent that researches prospects, personalizes outreach drafts, and logs activities in a CRM.
Create agent tools by connecting API calls, data transformations, conditional logic, and LLM processing steps. Tools become reusable capabilities across agents.
Building a custom tool that queries an internal pricing database, applies discount logic, and generates a formatted quote.
Connect multiple specialized agents to handle complex, multi-step workflows. Each agent focuses on specific tasks while the workforce handles coordination and handoffs.
Building a lead qualification workforce where one agent researches prospects, another scores leads, and a third updates CRM records and triggers follow-up.
Connect documents, websites, or business information as agent knowledge sources for retrieval-augmented responses and workflow context.
Creating a product knowledge base from documentation, FAQ pages, and training materials that agents use to answer customer questions.
Connect agents with business platforms and internal systems through supported integrations, APIs, and workflow tools. Confirm exact supported apps and plan availability before buying.
Building an agent that monitors customer conversations, identifies high-priority issues, creates CRM records, and notifies the team.
Deploy agents through supported interfaces such as chat, APIs, scheduled tasks, or webhook-triggered automations.
Deploying a support agent that answers common questions and runs scheduled checks on open tickets.
No. Relevance AI is positioned as a no-code platform for building agents, agent tools, and business workflows. Technical teams may still be useful for advanced API connections, data governance, and production rollout.
Relevance AI trades some low-level flexibility for faster setup and business-team accessibility. Code frameworks give developers more control, while Relevance AI is better suited to teams that want a managed visual platform for operational agents.
The public record reviewed here is not sufficient to guarantee an exact provider list for every plan or deployment. Buyers should confirm the currently supported models, routing options, and any bring-your-own-key requirements before standardizing on a deployment.
Relevance AI has enterprise-oriented positioning, but organizations handling sensitive data should review the current security page, DPA, retention terms, encryption details, SSO availability, audit logging, and contract commitments directly with the vendor.
Agents are individual AI workers configured for specific tasks. Workforces are collections of agents that collaborate across a larger process, such as prospect research, qualification, CRM updates, and follow-up drafting.
Now that you know how to use Relevance AI, it's time to put this knowledge into practice.
Sign up and follow the tutorial steps
Check pros, cons, and user feedback
See how it stacks against alternatives
Follow our tutorial and master this powerful ai agents & autonomous workflows tool in minutes.
Tutorial updated March 2026