Build a 24/7 AI Customer Service Agent Using Make

As a Customer Experience Automation Specialist working with U.S. businesses, one of the most impactful upgrades you can implement today is a 24/7 AI customer service agent. In this guide, you'll learn exactly how to build a 24/7 AI Customer Service Agent Using Make — without writing a single line of code — and connect it to reliable, enterprise-grade workflows that handle emails, FAQs, and customer requests automatically.

This is the same automation stack used by modern U.S. startups, small businesses, and digital-first brands to reduce support costs, speed up response times, and maintain consistent communication even outside business hours.

Why U.S. Businesses Are Shifting to AI Customer Service Agents

American customers expect rapid responses — often within minutes. Traditional support teams struggle to maintain these expectations due to rising labor costs, time zone constraints, and peak demand periods.

This is where an AI agent built on Make becomes a powerful solution. It enables companies to:

• Respond instantly to customer emails, form submissions, and inquiries.
• Use structured knowledge bases (like Google Docs) to maintain accuracy.
• Automate repetitive tasks that normally require human attention.
• Maintain consistent, professional communication 24/7.

By the end of this guide, you'll have a fully functioning automation system that handles support questions from end-to-end.

Step 1: Set Up Make and Create Your AI Agent

Your workflow starts with Make, one of the most advanced no-code automation platforms in the U.S. market. You can access it through the official website: Make.

Inside Make, head to AI Agents → Create Agent. You’ll be able to select from various LLM providers like OpenAI or Anthropic. For this guide, we use Grok (Llama-3) because it provides fast, reliable reasoning and excellent performance for support-related tasks.

Challenge: Some businesses find it overwhelming to choose the right AI model.

Solution: Start with Llama-3 for support tasks — it handles FAQs, tone matching, and contextual reasoning extremely well.

Step 2: Build a Knowledge Base With Google Docs

Your AI agent needs reliable information to respond accurately. Many U.S. teams prefer using Google Docs because it is easy to maintain and supports real-time collaboration. You can store essential support information such as:

• Product FAQs
• Shipping policies
• Refund and return guidelines
• Hours of operation
• Location details

Make allows you to fetch this document’s content through a simple automation module.

Challenge: If your FAQ document grows too large, AI responses may lose specificity.

Solution: Break long documents into smaller, structured FAQs (Shipping, Billing, Product Info, Troubleshooting). Connect each one as a separate tool for higher accuracy.

Step 3: Create a Tool in Make to Read the FAQ Automatically

Next, you'll create a Make Scenario that retrieves your Google Doc content. This scenario acts as a “tool” the AI agent can call whenever it needs factual information.

This tool becomes your agent’s real-time knowledge base. Anytime you update the Google Doc, the AI agent instantly uses the latest information.

Challenge: Some teams forget to switch the scenario to “On-Demand,” causing unnecessary operations.

Solution: Always set the FAQ retrieval scenario to On-Demand to ensure it only runs when the AI agent requests it.

Step 4: Build the Email Response Automation

Most customer support interactions in the U.S. still begin via email. Make allows you to send emails automatically through providers like Gmail, Outlook, or custom SMTP.

Create a new scenario in Make with inputs such as:

• Customer email address
• Email subject
• Email body (generated by the AI agent)

This scenario becomes another tool the AI agent can use to reply directly on your behalf.

Challenge: Automated emails can sometimes sound robotic.

Solution: Add an “Additional System Instruction” such as: “Respond with a warm, conversational tone that reflects U.S. customer service standards.”

Step 5: Collect Inquiries Using Tally Forms

Tally is a lightweight, U.S.-friendly form builder that integrates smoothly with Make. You can embed a form on your website where customers submit:

• Name
• Email
• Support question

You can integrate Tally through its official website here: Tally.

Every time a new form submission arrives, Make triggers the AI agent to analyze the request, generate a response, and send an email back instantly.

Challenge: High-volume forms can trigger too many automation runs.

Solution: Add a filter in Make to block duplicate tickets or repeated questions from the same customer.

Step 6: Connect Everything into a Fully Automated Workflow

Now that you have your tools ready, create a final scenario in Make that follows this path:

1. Tally watches for new responses.
2. Make sends the customer question to your AI agent.
3. The agent retrieves the FAQ data if needed.
4. The agent decides the best reply.
5. The Email Tool sends the response directly to the customer.

This creates a complete 24/7 support loop that works without human intervention.

Challenge: Some users forget to test each component separately.

Solution: Run each scenario once, verify the output, then activate them together.

Quick Comparison: Tools Used in This Automation

Tool	Primary Use	Key Benefit	Potential Challenge
Make	Automation + AI Agents	No-code + powerful integrations	Requires careful scenario organization
Grok (Llama-3)	AI reasoning and responses	Fast, accurate, context-aware	May require tuning for specific tones
Google Docs	Knowledge base storage	Easy to manage and update	Large documents reduce answer accuracy
Tally	Customer inquiry form	Simple and lightweight	Not ideal for complex ticketing systems

Is This Automation Scalable?

Absolutely. Many U.S. businesses start with a simple FAQ-based support agent, then expand into:

• Multi-language customer support
• WhatsApp and SMS automation
• CRM sync with platforms like HubSpot or Salesforce
• Order status lookups connected to eCommerce APIs

Because Make supports thousands of integrations, you can gradually transform your AI agent into a fully managed support ecosystem.

Conclusion

Building a 24/7 AI customer service agent using Make is one of the most valuable upgrades you can implement for a U.S. business. It eliminates delays, reduces operational costs, and creates a professional, consistent support experience that customers appreciate.

With this guide, you now have the exact blueprint to automate your entire front-line support workflow — from inquiry to response — using tools that are stable, accessible, and fully customizable.

FAQ

How accurate is an AI customer service agent for handling real U.S. customer inquiries?

Accuracy largely depends on the quality of your knowledge base. When your Google Docs are well-structured, AI agents built with Make provide highly accurate, context-aware responses suitable for real-world U.S. customers.

Can I integrate this AI agent with my eCommerce store?

Yes. Make integrates with Shopify, WooCommerce, and other platforms, allowing your agent to answer order-related questions, shipping updates, and product FAQs.

Do I need coding skills to build this workflow?

No. Make is fully no-code. You can connect your tools visually through drag-and-drop modules.

Can this AI agent handle multiple communication channels?

Absolutely. Beyond email and forms, you can connect WhatsApp, SMS, social inboxes, or even website chatbots.

What if my business receives sensitive customer data?

You can configure Make to store data safely or pass it to secure databases. Always follow U.S. compliance standards and avoid storing unnecessary personal information.