5 Best Chatbot Development Frameworks

Ever interacted with a chatbot? Yes, probably you have, whether you realized it or not. You might have visited any healthcare/educational website, and noticed a chat-window pop-up on your screen, asking you for details, about your visit to their website.
Source: Austin Distel from unsplash

Okay, yes!!! You got my point. The conversation(Conversational AI) you have on those chat-windows isn’t with humans but with a Human-Like software system that can understand your questions and reply to you with relevant responses.

What is a chatbot?

A chatbot is a software application that can interact and communicate effectively with people just like humans. Chatbots use natural language recognition capabilities to recognize what a user is saying, and respond accordingly to their inquiries and requests.

With examples like Siri, Alexa it is understood how a chatbot can make a difference in our daily-to-daily life. The demand and use of Chatbots have skyrocketed in recent years.

What is the need for a chatbot?

Businesses get tons of customer queries/inquiries daily. It could become difficult(sometimes impossible) to manage all the queries easily. Hence to stay competitive in such a modern and competitive business is to automate as many of your processes as possible.

And this demand is fulfilled by “AI chatbots”. Most of the companies are effectively using “chatbots” to automate their customer service and minimize the work-load of their employees.

HubSpot’s research revealed that about 71% of people prefer to get customer support from messaging apps. By using chatbots, a business can provide personalized, customizable, human-like, proactive service to millions of people at the same time.

How to build a chatbot?

Eager to start creating your chatbots? Who wouldn’t be? 

Building chatbots have become much easier with the AI chatbot development frameworks. 

Let us see some of the best chatbot development frameworks:

  • Dialogflow
  • IBM Watson
  • Rasa
  • Wit.ai
  • Microsoft Bot


Dialogflow is an end-to-end, “build-once and deploy-everywhere” type development framework used for building conversational interfaces for mobile apps, websites, popular messaging platforms, and other IoT devices. Dialogflow was previously referred to as api.ai and got acquired by Google in 2016. It’s the foremost widely used tool to build actions for quite 400M+ Google Assistant devices.

Dialogflow is user-friendly, supporting 20+ languages, and possibly the most effective framework to create Natural language processing based applications. Dialogflow is easy to learn and understand even for beginners.

This chatbot development framework helps businesses digitalize certain business processes due to its unique voice navigating features. It effectively uses Google cloud architecture and an AI-powered sophisticated system to convert speech into text. It also uses big data to understand what users are trying to say and respond accordingly.

Cost – If you just want to learn building a Chatbot, a Standard Edition is free, although it comes with certain limitations.

Integrate with:

  • Facebook Messenger
  • Google Assistant
  • Slack
  • Cortana
  • Kik
  • Alexa
  • Viber
  • Line
  • Skype
  • Twilio
  • Twitter
  • Telegram

IBM Watson

IBM Watson is a Natural Language Classifier API that helps you to interpret natural language using the custom classifier.IBM Watson Assistant is an AI service that allows you to build, train, and deploy Chatbots over the IBM cloud. IBM Watson is created using a neural network of 1 billion Wikipedia words and is appropriate in communicating with the bot users.

It gained notoriety in ’97, when Big Blue, Watson’s predecessor, defeated a world champion in chess. In 2011 it made its mark again in Jeopardy, proving how powerful its NLP is.

The IBM Cloud platform enables you to create a chatbot based on the most advanced machine learning. It classifies text into custom/various categories from multiple languages. You need not have any sort of technical experience to develop a chatbot using IBM Watson Assistant. The intuitive interface allows you to easily create dynamic conversational flows.

Cost – IBM Watson API is free to use on the IBM cloud for 30 days. Later, you can opt for any of its paid plans according to your needs.

Integrate with:

  • Facebook Messenger
  • Slack
  • Intercom
  • WordPress site
  • Custom applications through APIs.

Rasa Stack

Rasa is an open-source conversational AI platform that started as a project on GitHub. Rasa Stack is the infrastructure layer for developers for creating and deploying better AI assistants.

It is a Machine Learning Framework which is used to automate text and voice-based assistant. It provides necessary tools for high-performing, contextual, resilient, and customizable assistants.

It works on two main components – Rasa Core and Rasa NLU. Rasa Core works on the inputs based on intent and entities while Rasa NLU is the natural language processing of the bot.

How Rasa is different from other cloud-based tools? In many cases, Clients don’t want to share their data and the majority of the tools available are cloud-based and provide software as a service.

You can not run them internally in your environment/server. So you always need to send your data (indirectly) to the third party. With RASA, there is no such issue. You can build, deploy, and host Rasa internally in your own server/environment with complete control thereon. Therefore the major advantage of using Rasa Stack is that chatbot can be deployed on your own server/environment by keeping all the components safe in-house.

Cost – Rasa X is a free toolset used to improve contextual assistant built using Rasa open-source.

Integrate with:

  • Facebook Messenger
  • Rocket.Chat
  • Twilio
  • Telegram
  • Slack
  • Website


Wit.ai is the Facebook acquired company. It is an open-source chatbot framework with advanced natural language processing capabilities. Wit.ai began as a Y Combinator startup. It allows the developers to configure the entities and intents, where it takes text or voice input and returns intents and entities.

Developers can use the HTTP API to connect the wit.ai to your chatbot or some other applications.Wit.ai provides SDK in Node.js, Python, Ruby. You can use Wit.ai to create intelligent chatbots for websites, mobile apps, social channels, and IoT devices.

Owned by Facebook, Wit.ai is the most popular and preferred choice for Facebook Messenger bots. Wit.ai supports around 80+ languages from around the globe, which enables developers to easily translate data worldwide. Wit.ai lets you easily create text and voice-based bots which can be connected to messaging platforms of your choice.

Cost – Wit is free, both for personal and commercial use.

Integrate with:      

  • Your website
  • Your app
  • Slack
  • Facebook Messenger
  • Wearable devices
  • Home automation

Microsoft Bot

Microsoft Bot Framework platform enables you to create, connect, publish, and manage chatbots, which are smart and interactive to provide the best user experience. Microsoft’s Azure Bot comes with active learning. These enterprise-grade bots provide you with complete ownership and control of your data.

The web interface is available to create and publish bots that are smart and easy enough to understand. Microsoft Bot-based chatbots are capable of replying to even the most complicated questions asked by the visitors. Microsoft Bot framework can be used to train chatbots using the existing conversation and azure cognitive services.

Cost- Microsoft bot service provides a free plan of 10,000 messages per month. After that, pricing is $0.50 per 1,000 messages.

Integrate with:

  • Skype
  • Slack
  • Facebook Messenger
  • Website
  • Cortana
  • Microsoft team
  • Kik


While there are many Chatbot frameworks available nowadays, but these 5 are the most popular ones. If you are confused about choosing one framework from the above or the others available, just try to explore them first, analyze your requirement, and then see which one is best suitable for you.

If you have already used a few of them then let us know your favorite chatbot building framework in the comment section.

Thanks for reading!


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