How to Make Your Manychat Bot Smarter with Dialogflow AI

Introduction

In today’s fast-paced digital world, customers expect instant, personalized responses day and night. If you’re using Manychat to automate conversations on Messenger, Instagram, or WhatsApp, you’re already ahead of the game. But what if you could make your bot even smarter by adding AI-powered Natural Language Processing (NLP) to understand and respond like a human, truly? That’s where Dialogflow by Google and Janis come in. Integrate Dialogflow AI with Manychat to build smarter chatbots, automate replies, reduce support costs, and boost engagement.

In this guide, you’ll learn how to integrate Dialogflow with Manychat using Janis, so your chatbot can deliver intelligent responses, reduce support costs, close more leads, and increase customer satisfaction — 24/7. The best part? No technical experience is required. Start building smarter conversations today. Join Manychat now and launch your chatbot without writing a single line of code.

Why Integrate Dialogflow AI with Manychat?

Manychat is great for building rule-based bots using Flows. However, bots often struggle when users type in something unexpected. Dialogflow solves this problem by using AI to understand meaning and intent, not just keywords. With it, your bot can carry on more natural conversations.

Here’s what you can do by integrating Dialogflow AI:

• Answer FAQs automatically
  
• Understand user input in multiple languages
  
• Capture important details (like phone numbers or dates)
  
• Reduce human support needs
  
• Boost engagement and conversions
  

Using Janis, a no-code integration tool, you can easily connect Dialogflow to your Manychat bot and start reaping the benefits immediately.

How Dialogflow Works: A Crash Course

Before diving into the steps, let’s quickly understand how Dialogflow operates: Looking to take your AI-powered bot even further? You can set up real-time alerts whenever a user needs human help. Check out our guide on how to create a doorbell for your Manychat bots using Slack — it’s a simple way to stay notified and jump into conversations when your bot needs backup.

Intents

These are user goals or messages you want your bot to recognize. For example, an intent like “Store Hours” could respond to users asking, “What time do you open?”

Training Phrases

These are example phrases users might say to trigger an intent. You can add as many as needed to improve recognition.

Entities and Parameters

Entities are like keywords that hold data. For instance, “Friday” is an entity for the date. Parameters store those values and can be synced with Custom User Fields in Manychat.

Context

It helps Dialogflow remember the flow of a conversation, so the bot knows what the user is referring to. You can manage context by adding or removing tags in Manychat Flows.

Events

These are special triggers like a “thumbs-up” emoji that can also activate an Intent without typing a phrase.

Dialogflow also supports multi-language bots and can deliver intelligent responses based on the user’s language — a great win for global businesses.

Manychat makes automation simple and powerful. Sign up now and take your customer engagement to the next level.

Step-by-Step Guide to Connecting Dialogflow with Manychat

Here’s a simple 5-step process to make your Manychat bot smarter using Dialogflow and Janis: Ready to create an AI-powered chatbot? Get started with Manychat and connect with your audience like never before.

Step 1: Get Your Dialogflow AI Agent

Head over to Dialogflow.com, sign in with your Google account, and click Create Agent.

• Give your agent a name (preferably the same or similar to your Manychat bot)
  
• Choose your default language and time zone
  
• Click Create
  

You now have a basic AI brain ready to train.

Step 2: Connect Your AI to Janis in Slack

Janis makes managing Dialogflow easy, right from Slack, a workspace used by millions, including the Manychat team itself.

• Create a free Slack workspace if you don’t have one.
  
• Go to Janis.ai and Add Janis to Slack.
  
• Once Janis is added, type connect Dialogflow in Slack to link your agent.
  

Tip: You can connect multiple Dialogflow agents and Manychat bots to a single Slack workspace.

Step 3: Connect Manychat to Janis

There are two ways to integrate Janis with Manychat: AI template integration or custom integration.

Option 1: Use the Janis AI Template (Recommended for Beginners)

• Janis will provide a template key
  
• Go to Manychat and install the AI template
  
• Paste the key into the specified field
  

This option gives you:

• Pre-trained Dialogflow intents for common user queries
  
• Editable Manychat Flows for customizing responses
  
• A head start in AI training
  

Option 2: Do a Custom Integration

Prefer building from scratch?

• Janis gives you a custom Webhook URL
  
• Paste this into a Dynamic Input card inside your Default Reply
  
• This forwards user input to Dialogflow for processing
  

Either way, your bot becomes capable of understanding and responding to open-ended user messages with AI.

Step 4: Connect Your Facebook Page to Janis

By linking Janis to your Facebook page, you unlock powerful monitoring tools:

• Janis will monitor all user inputs
  
• Alert you in Slack when the bot doesn’t understand something
  
• Let you pause AI and take over live
  
• Train AI based on real Messenger conversations
  

This hybrid approach ensures seamless handoffs between bot and human, improving both automation and customer satisfaction.

Step 5: Start Training and Collaborating with Janis

Once you send a message to your bot and it replies via Dialogflow, your integration is working.

Now you’ll start seeing:

• Slack alerts for misunderstood messages
  
• Real-time bot responses in Messenger
  
• Opportunities to fine-tune AI by adding new Intents and training phrases
  

With Janis in Slack, you can:

• Collaborate with your team, clients, or partners
  
• Assign roles and manage permissions
  
• Keep improving your bot using real conversations
  

Best Practices for Smarter AI Conversations

Making your chatbot smarter is not just about adding AI — it’s about training and refinement. Here’s how to get better results:

Use Pre-trained Templates

AI training takes time. Start with Janis’s pre-trained templates to cover the most common questions and save hours of work.

Monitor Unrecognized Messages

Slack alerts from Janis help you spot what users say that your bot doesn’t understand. Train your Dialogflow agent using those messages as training phrases.

Use Custom User Fields in Manychat

Sync parameters from Dialogflow to store user data like names, dates, or locations, and use that data for personalized replies later.

Handle Language Preferences

If your audience is multilingual, set a Custom User Field to tell Dialogflow which language to use in responses.

Use Tags and Contexts Strategically

Apply or remove tags in Flows to control context in Dialogflow, enabling smarter multi-step conversations.

Why Janis Is a Game-Changer for Manychat and Dialogflow Integration

Janis is more than a connector — it’s an AI management toolkit:

• Provides pre-trained AI templates
  
• Helps with live monitoring and training
  
• Alerts you to message gaps
  
• Works inside Slack for seamless collaboration
  

Even if you’re new to AI, Janis simplifies the learning curve, helping you build a smarter bot without hiring a developer.

Need Help Integrating AI into Your Manychat Bot?

Need help integrating AI into your Manychat bot? At Axiabits, we specialize in building and optimizing AI-powered chatbots using Manychat, Dialogflow, and Janis.

Whether you need a custom integration, pre-trained template setup, or ongoing AI training support, we’ve got you covered.

Book now and let’s get started!

Final Thoughts: Your 24/7 Smart Bot Is Just a Few Clicks Away

By integrating Dialogflow AI with Manychat using Janis, you unlock the true potential of conversational marketing. Whether you’re running an eCommerce store, a SaaS business, or offering services, AI will help you scale your customer interactions like never before.

It’s time to stop using static bots and start building intelligent assistants that:

• Learn from real conversations
  
• Understand natural language
  
• Improve over time
  
• Deliver around-the-clock support

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