【Artificial Intelligence】The Best Chatbot Frameworks You Must Know

In this blog, we will discuss the top 7 chatbot development frameworks.

Chatbots are now an integral part of many businesses. They utilize chatbots to provide customer support services. Chatbots augment human agents to provide customer service support. Businesses receive a ton of inquiries every day. Answering these questions manually is not only time-consuming, but also increases costs for companies as they have to hire more people to provide customer support services. Today, a lack of timely response often leads to customer frustration. This could end up causing the business to lose customers. That's why having efficient customer service is at the heart of every business process.
This is where chatbots come in. Imagine how efficient and convenient it would be if there was a bot that could answer all the queries of the users. This imagination has become reality through artificial intelligence.
A chatbot is a computer program that simulates and processes human conversations (written or spoken), allowing humans to interact with digital devices as if they were communicating with a real person.
You must have found chatbots on many of the websites you visit, such as educational technology websites. Am I right? excellent! Yes, chatbots can handle all inquiries like those about courses/bootcamps. The chatbot is so smart, you can even book movie tickets or airline tickets just by instructing the bot. Chatbots leverage the power of NLP (Natural Language Processing) to make them super intelligent.

According to a report by Outlook (2018), 80% of businesses are expected to integrate some form of chatbot system by 2022.

So now is the perfect time for you to learn how to build chatbots like Alexa or Google Assistant. There are various frameworks available that enable you to build and integrate chatbots seamlessly.
So without wasting any more time, let's start discussing the top 7 frameworks for chatbot development.

1. Google Dialogflow

Dialogflow is a chatbot development framework owned by Google. It has built-in NLP capabilities and enables users to build NLP-based chatbots. Dialogflow is used to build conversational applications for clients in various languages ​​and on multiple platforms.
Did you know Malaysia Airlines uses Google Dialogflow to simplify flight search, booking and payment for its customers? Yes, really amazing.
advantage:

• easy to learn

• Supports text and voice-based assistants.

• Manage and scale easily

• multilingual support

• Integrate with Messenger, Skype, Telegram, Twilio, and more.

shortcoming:

• You can only provide one webhook per project.

Get started with Google Dialogflow

2. Amazon Lex

Indeed one of the most powerful frameworks for building chatbots! It features advanced NLP models for building conversational interfaces in applications. Amazon Lex manages the conversation and dynamically adjusts responses within the conversation.
The AHA's premier Heart Walk event reaches nearly one million participants nationwide to advance their mission to save lives. The AHA is using Amazon Lex to streamline the registration process so that HeartWalk participants can easily register through the website using their natural voices.
advantage:

• automatic speech recognition

• Provide SDKs for multiple platforms

• Ability to execute business logic

• AWS Lambda integration

shortcoming:

• it only supports english

• Complex Network Integration

Get started with Amazon Lex

3. TASTE

RASA is an open source framework based on python. It has two main components: RASA NLU and RASA Core. Rasa NLU is responsible for natural language understanding, while Rasa Core helps create intelligent conversational chatbots.
RASA uses machine learning models to determine the flow of a conversation. It was named a "Leading Vendor in Conversational AI Platforms" by Gartner.
T-Mobile is the second largest wireless carrier in the United States. At times, more than 20,000 customers, many with simple requests, may line up to speak with a T-Mobile specialist. That's why the company considered building a conversational AI bot that could help answer queries. They developed it entirely in-house to save costs, and they can customize every aspect of the robot. So they used RASA.
advantage:

• highly customizable

• Multiple deployment environments

• Role-Based Access Control

• Integrate with Messenger, Slack, Telegram, Twilio, and more.

shortcoming:

• Not for beginners. Knowledge of NLP is required.

• Programmers do not have fine-grained control over dialog handling.

Get started with RASA

4. IBM Watson

Do you want a chatbot framework that even non-technical users can use? Or you don't want your data to be shared? If yes, IBM Watson is the framework of choice for building chatbots.
It's built on top of neural networks that use processing frameworks to understand and learn from conversational cues.
Big Four audit, tax and consulting firm KPMG LLP uses IBM Watson to help them more efficiently find R&D tax credits for clients. It helps tax professionals determine eligibility for tax deductions with confidence.
advantage:

• Automated Predictive Analysis

• Lets you store data on a private cloud

• multilingual support

• Integrate with Messenger, Wordpress, and more.

shortcoming:

• slow integration

• quite expensive

Get started with IBM Watson

5. Wit.ai

Wit.ai is an open source chatbot building framework built by Facebook. It enables people to use their voice to control smart speakers, appliances, lighting and more.
Structurally, the Aisa Holmes chatbot asks users a variety of questions to help them find a home with qualities and features that match their specific preferences. It uses Wit.ai NLP engine to understand user intent and provide valuable information.
advantage:

• easy to deploy

• large developer community

• Provides more than 80 language support

• Integrate with Messenger, wearables, and more.

shortcoming:

• Difficulty retrieving missing parameters

• If we share data, it will be shared throughout the Wit.ai ecosystem

Get started with Wit.ai

6. Pandorabots

It is an open source chatbot development framework. It's based on the AIML (Artificial Intelligence Markup Language) scripting language that developers can use to build conversational bots.
Pandorabots is built for developers and customer experience designers. It does not come with pre-configured machine learning tools.
SuperFish AI is a language learning platform for teaching English at scale. They hope to provide a standardized solution for English learning in rural areas of China that lack English teachers. Using Pandorabot, Superfish were able to immediately introduce a robust, free-form English conversation practice partner to complement their internally developed content and lesson plans. The Pandorabots platform allows them to continuously improve and target their chatbot content based on real-time student usage.
advantage:

• No platform lock-in: own and download your code

• Rapid iteration: CI/CD, version control, chat logs

• Deploy to message or voice channel

• Easily add speech to text and text to speech

• RESTful API for integration with applications and systems

shortcoming:

• less accurate

• AIML must be learned separately

Get Started with Pandora Bot

7. Microsoft Robot Framework

Language Understanding (LUIS) is a machine learning-based service for building natural language into apps, bots, and IoT devices. LUIS interprets user intent and extracts important details from any request. LUIS also learns as you go, allowing you to continuously improve the quality of your bot's conversations.
UPS, a longtime IT innovator, has improved customer service through intelligent applications that provide its customers with a relevant and seamless experience on virtually any device. UPS delivers more than 19 million packages in more than 220 countries and territories. Customers can engage UPS Bot in text- and voice-based conversations to get the information they need about shipments, rates and UPS locations.
advantage:

• SDKs for multiple computer languages

• Enterprise Ready, Available Globally

• Integrate with Cortana, MS Team, Slack, Skype and more.

shortcoming:

• Supports Node.js or C# for development.

start using louis

in conclusion

So, in this blog, we discuss the best 7 chatbot development frameworks along with their pros and cons.
Chatbots have proven to be an extremely effective solution for improving customer service. It saves time and is efficient. No matter how good a company's technology is, if the customer support is poor, the business will suffer. This is why companies are adopting chatbot services at a very fast pace.
Let Data Confess Pvt. Ltd. organized a Bootcamp on "Build Your Own Chatbot Using RASA" and a deployment on the cloud. If you want to learn with proper guidance, you can sign up for a bootcamp.

This article: https://architect.pub/best-chatbot-frameworks-you-must-know-about
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