Want to build an AI agent without writing code? Relevance.ai makes it simple for businesses to create AI-powered agents using a no-code platform. Whether you’re improving customer service or streamlining operations, this guide will show you how to get started quickly.
Relevance.ai’s user-friendly platform helps you create AI solutions tailored to your business needs. Ready to dive in? Let’s get started!
Getting started with Relevance.ai is simple and doesn’t require much technical know-how.
Follow these easy steps to set up your account:
If you're opting for the free plan, there's no need to enter a credit card to check out the platform's features .
The Relevance.ai dashboard is built for easy navigation and includes the following key sections:
| Dashboard Section | Primary Functions | Key Features |
|---|---|---|
| Agents Page | Create and manage agents | Build agents from scratch or use ready-made templates |
| Tools Hub | Connect resources | API integrations and LLM chains |
| Team Management | Set up team collaboration | Assign roles like Admin, Editor, and Viewer |
| Security Center | Monitor compliance | SOC 2 Type II and GDPR settings |
Here are some standout features of the platform:
Once your account is ready and you've explored the dashboard, you’ll be set to start planning your AI agent.
Start by defining clear objectives for your AI agent. Pinpoint the business challenges you want to tackle, keeping in mind both immediate priorities and long-term growth.
Use the SMART framework to guide your goal-setting:
| Goal Component | Description | Example |
|---|---|---|
| Specific | Clearly outline tasks and functions | Handle shipping inquiries |
| Measurable | Establish success metrics | Cut response time by 50% |
| Achievable | Set realistic targets | Process 1,000 queries daily |
| Relevant | Align with business goals | Boost customer satisfaction scores |
| Time-bound | Define a deadline | Meet goals within 3 months |
Think about the main tasks your agent will handle, the data it will need, required integrations, how autonomous it should be, compliance requirements (like GDPR or CCPA), and how success will be measured.
Relevance.ai offers two main options for creating your AI agent: pre-built templates or a custom-built solution. The choice depends on your goals and available resources.
Pre-built Templates:
Custom Build:
For instance, a major tech company enhanced their internal cloud support desk by deploying an AI agent with well-defined goals. They prioritized reducing Mean Time to Resolution (MTTR) for support tickets using an Intelligent Workflow system. This structured strategy led to measurable improvements in their operations .
For businesses new to AI agents, starting with a template and customizing it as you go often strikes the best balance between speed and functionality . This method lets you quickly deliver results while gaining hands-on experience with the platform. You can then refine the agent based on real-world feedback and data.
With clear objectives and the right approach, you're ready to start building your AI agent.
Choosing the right name for your AI agent is more important than you might think. A clear, descriptive name helps the Large Language Model (LLM) understand and execute tasks effectively.
"The names you give your tools are crucial, as they are added to the LLM prompt that powers the agent using your tool. Names significantly impact performance, as agents consider these strongly when deciding how and when to use your tools." - Relevance AI Documentation
Here’s a quick guide to naming your agent's tools:
| Do's | Don'ts | Example |
|---|---|---|
| Be specific about the purpose | Avoid vague terms | ✓ "Get LinkedIn company posts" |
| Include both an action and an object | Skip to technical implementation | ✗ "LinkedIn scraper" |
| Keep the language clear and concise | Avoid overly technical jargon | ✓ "Summarize Glassdoor interviews" |
| Mention the system for integrations | Use generic descriptions | ✗ "Search LinkedIn" |
Once you’ve nailed down a clear name and purpose, you’re ready to configure the agent’s settings for consistent results.
The 'Build' tab is where you’ll set your agent’s core configurations to ensure it functions as needed:
{{}} notation. Disable the "Infer output from last step of tool" option for better control over outputs.
Enhance your agent’s abilities by integrating tools. The platform supports a range of systems and platforms, creating an efficient automation network.
Here are some popular tool categories and their potential impact:
| Category | Key Tools | Business Impact |
|---|---|---|
| Communication | Slack Integration, Email Escalation | Better team coordination |
| CRM | Hubspot Sync, Airtable Toolkit | Improved customer data management |
| Content | YouTube Transcription, LinkedIn Post Enhancement | Easier content production |
| Sales | SPIN Selling, Lead Enrichment | Faster sales workflows |
| Research | Knowledge Retrieval, Sentiment Analysis | Smarter, data-backed decisions |
Pick tools that align with your agent’s goals. For example, a customer service agent would benefit more from communication and CRM tools than content creation features.
Thorough testing can reduce errors by 35% and increase satisfaction by 25% .
| Test Category | Example Scenarios | Success Metrics |
|---|---|---|
| Basic Functions | Query handling, Tool integration | Response time < 2s |
| Edge Cases | Complex requests, Multiple tools | Task completion > 80% |
| Error Handling | Invalid inputs, System limits | Error rate < 5% |
| Performance | High volume, Concurrent requests | Latency within specs |
"Testing is the foundation of building AI agents that are reliable, efficient, and trusted." - Manjeet Singh, Senior Director of Product Management, Salesforce AI Cloud
Once you've validated basic functions and edge cases, focus on fine-tuning your agent's responses.
Refining your agent's performance is key:
Make sure your agent meets these performance benchmarks:
| Metric | Target | Monitoring Tool |
|---|---|---|
| Response Time | Under 2 seconds | Performance Dashboard |
| Task Completion | 80% or higher | Analytics Panel |
| Error Rate | Below 5% | Error Tracking System |
| User Satisfaction | Above 85% | Feedback Metrics |
"Advanced benchmarks expose the gulf between laboratory performance and real-world reliability. They're not just tests; they're roadmaps for building truly robust AI systems." - Dr. Emma Liu, AI Ethics Researcher
Once your AI agent is tested and live, you can start exploring its potential to enhance customer service and drive sales.
AI agents are transforming customer support by automating tasks and efficiently routing tickets. For instance, a major telecommunications company managed to cut simple support tickets by 60% within just three months . These AI tools can handle common support scenarios with over 95% accuracy . This success is largely due to their advanced natural language processing capabilities, machine learning techniques, and integration with CRM systems.
"AI agents are computer programs that automate customer service tasks by using artificial intelligence to understand and respond to customer queries. They combine natural language processing, machine learning, and knowledge bases to handle everything from basic questions to complex support tickets without human intervention." - Scott Henderson, Head of Marketing at Relevance AI
AI agents aren't just limited to customer service - they're also making waves in sales and marketing.
In sales and marketing, AI agents are helping businesses deliver highly personalized, data-driven communication. A recent study revealed that 65% of organizations now use generative AI in marketing, with personalized campaigns increasing customer spending by 37% . A B2B tech company saw impressive results when targeting CTOs with cybersecurity content on LinkedIn, achieving conversion rates 75% higher than their average leads .
"Before diving into AI when it comes to B2B lead generation, the first thing you should make sure to have is accurate data that mimics your target audience. Without quality data it is very difficult to use AI. This is because AI tools rely on accurate data sets to provide analysis and recommendations on how to generate leads." - Ryan Doser, VP of Inbound Marketing, Empathy First Media
Relevance.ai makes it easy for businesses to build AI agents without needing to write a single line of code. Its user-friendly design allows professionals to create AI solutions without technical skills. This approach aligns with industry forecasts, such as Gartner's prediction that by 2025, 70% of new enterprise applications will rely on low-code or no-code tools .
"Even though it's a no-code platform the use cases are unlimited and you can customize it any way you want and DO anything you want." - Ben Van Sprundel, AI Consultant and Youtuber
Interested in exploring what this platform can do for you? It’s easy to dive in and start building.
Signing up is straightforward and free - no credit card needed . The platform offers expert-designed templates, access to multiple LLM providers (like OpenAI, Anthropic, Cohere, and PaLM), and tools for customizing in natural language - all within a visual interface. Start by choosing a pre-built template that fits your business goals. Test and fine-tune your AI agent through smaller deployments. Once you’re confident, scale up by using the platform’s multi-agent tools to grow your AI capabilities .
