Chatbot SDK – Discover the Power of Chatbot SDK
Tags: webdev, javascript, programming, tutorial
Published: 2023-06-07 11:52:39


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A Chatbot SDK (Software Development Kit) is a set of tools and resources that developers can use to build and deploy chatbots on various platforms. These kits typically include libraries, APIs, documentation, and sample code. They make it easier for developers to create chatbots that can understand and respond to user input in a human-like manner.

Chatbot SDKs are becoming increasingly important in 2023 as more and more businesses are adopting chatbots to improve their customer service and engagement.

A study by Juniper Research predicts that by 2023, the banking, retail, and healthcare sectors will save roughly 2.5 billion customer service hours by adopting chatbots. These figures demonstrate the growing importance of chatbots and the need for businesses to adopt Chatbot SDKs to stay competitive.

## The Major Types Of Chatbot SDKs 

There are several types of chatbot SDKs that your business can adopt to reap the benefits of a  chatbot. The major types of chatbot SDKs are:

## 1. Natural Language Processing (NLP) SDKs 

Natural Language Processing (NLP) SDKs use advanced machine learning algorithms to enable chatbots to understand and generate human language. These SDKs typically include tools for tasks such as speech recognition, language translation, sentiment analysis, and entity extraction. NLP SDKs are best for building chatbots that can handle complex and open-ended user queries.

## 2. Rule-based SDKs 

Rule-based SDKs, as the name suggests, use a predefined set of rules to determine how a chatbot should respond to user input. These rules are typically based on keywords or phrases that the chatbot is programmed to recognize. Rule-based SDKs are well-suited for building chatbots that can handle simple and predictable user queries.

## 3. Hybrid SDKs

Hybrid SDKs combine the capabilities of both NLP and rule-based SDKs. These SDKs use a combination of machine learning algorithms and pre-defined rules. This will enable chatbots to understand and respond to user input. Hybrid SDKs are best for building chatbots that can handle a wide range of user queries, from simple and predictable to complex and open-ended.

## Chatbot SDK Capabilities: A Line-By-Line Comparison

If you are to analyze each type of chatbot SDK individually, it can complicate things. This table should help in easily comparing the capabilities of each type of chatbot SDK.


## Key Components and Features of a Chatbot SDK

A Chatbot SDK typically includes several key components and features that enable developers to build and deploy chatbots on various platforms. These components and features can vary depending on the specific SDK, but generally include tools for processing user input, recognizing user intent, managing conversation flow, generating responses, and integrating with external systems and APIs.

## 1. User Input Processing 

This component refers to the tools and techniques used by a Chatbot SDK to process and understand user input, whether it is in the form of spoken or written language.

## a. Speech-to-Text Conversion 

Speech-to-Text Conversion is the process of converting spoken language into written text. This feature is important for chatbots that support voice input, as it enables users to interact with the chatbot using spoken commands.

## b.Text Normalization and Preprocessing 

Text Normalization and Preprocessing are techniques used to clean and transform user input text into a format that can be more easily understood by the chatbot. This can include tasks such as correcting spelling errors, expanding abbreviations, and removing punctuation.

## 2. Intent Recognition and Entity Extraction 

Intent Recognition is the process of determining the user’s intended action or goal based on their input. Entity Extraction is the process of identifying and extracting relevant pieces of information from the user’s input, such as dates, times, locations, or product names. These features are important for enabling the chatbot to understand the user’s needs and provide appropriate responses.

## 3. Conversation Management 

This component includes tools for designing the conversation flow between the user and the chatbot, as well as tracking the context of the conversation and remembering information from previous interactions.

## a. Dialogue Flow Design 

Dialogue Flow Design is the process of defining the conversation flow between the user and the chatbot. This includes specifying the possible paths that the conversation can take, as well as defining rules for how the chatbot should respond to different user inputs.

## b. Context Tracking and Memory

Context Tracking and Memory refer to the chatbot’s ability to keep track of the context of a conversation and remember information from previous interactions with the user. This enables the chatbot to provide more personalized and relevant responses.

## 4. Response Generation

This component refers to the tools and techniques used by a Chatbot SDK to generate appropriate responses to user input, whether in the form of written or spoken language.

## a. Text-to-Speech Conversion 

-to-Speech Conversion is the process of converting written text into spoken language. This feature is important for chatbots that support voice output, as it enables users to receive responses from the chatbot in spoken form.

## b. Multilingual Support 

Multilingual Support refers to the chatbot’s ability to understand and generate responses in multiple languages. This feature is important for businesses that operate in multilingual markets or serve customers who speak different languages.

## 5. Integration with External Systems and APIs

Multilingual Support refers to the chatbot’s ability to understand and generate responses in multiple languages. This feature is important for businesses that operate in multilingual markets or serve customers who speak different languages.

Factors To Consider While Choosing The Right Chatbot SDK
When choosing a Chatbot SDK for your business, there are several factors that you should consider in order to ensure that you select the right one for your needs. By carefully evaluating these factors, you can make an informed decision and choose a chatbot SDK that best meets your requirements.

## 1. Platform Compatibility

Platform Compatibility refers to the ability of a Chatbot SDK to work with the platforms and devices that your business uses. This can include support for different operating systems, web browsers, and mobile devices. It is important to choose a Chatbot SDK that is compatible with the platforms that your customers use to interact with your business.

For example, the Kommunicate chatbot SDK is compatible with Dialogflow, Amazon Lex, Kompose Bot, IBM Watson, and even custom-made bots (Read documentation). Further, it is also compatible for real-time live chat and in-app messaging with most mobile platforms like Android and iOS.

## 2. Integration with Existing Systems

Integration with Existing Systems refers to the ability of a Chatbot SDK to integrate with the other systems and services that your business uses. This can include integration with customer relationship management (CRM) systems, databases, and payment processing systems. It is important to choose a Chatbot SDK that can easily integrate with your existing systems in order to provide a seamless user experience.

## 3. Customizability and Flexibility

Customizability and Flexibility refer to the ability of a Chatbot SDK to be customized and adapted to meet the specific needs of your business. This can include support for custom branding, custom conversation flows, and custom integrations. It is important to choose a Chatbot SDK that provides the level of customizability and flexibility that your business requires.

## 4. Cost and Licensing

Cost and Licensing refer to the financial aspects of using a Chatbot SDK. This can include upfront costs, ongoing licensing fees, and usage-based fees. It is important to carefully evaluate the cost and licensing terms of different Chatbot SDKs in order to choose one that fits within your budget and provides good value for money. 

Further, it is necessary that the pricing is also transparent. This is so that you are not surprised with hidden costs and fees at the time of invoicing. A careful calculation based on the number of chatbot sessions and the pricing for the same should help forecast costs with accuracy.

## Comparison of Popular Chatbot SDKs

There are several chatbot SDKs available in the market right now. However, there are five major ones that you should try to build a reliable chatbot. 

They are:

- Kommunicate
- Google DialogFlow
- IBM Watson Assistant
- Microsoft Bot framework
- Amazon Lex

A detailed take of the chatbot SDKs are as below:

## 1. Kommunicate 

Kommunicate is a chatbot SDK that provides an easy-to-use chatbot builder that allows you to create your own chatbots without any coding. The chatbot builder has an intuitive interface that enables you to design the conversation flow of your chatbot and integrate it with external systems and services. Kommunicate has numerous integrations built into its platform, making it easy to connect your chatbot with other systems and services.

Kommunicate is renowned for its lightweight, flexible, easily integrable SDK. It allows you to add real-time live chat and in-app messaging in your mobile applications and websites for customer support. The SDK is equipped with advanced messaging options such as sending attachments, sharing location, and rich messaging. 

## 2. Google DialogFlow

Google DialogFlow is a chatbot SDK that provides tools for building conversational agents for various products or services. It is supported by Google’s Cloud Natural Language and can be integrated with platforms such as Google Assistant, Cortana, Telegram, and Facebook Messenger.

As far as history is concerned, DialogFlow was initially known as API.AI and was created by a company called Speaktoit. Google acquired Speaktoit in September 2016 1 and in October 2017, it was renamed as DialogFlow. Ever since then, DialogFlow has become an integral part of all chatbot communication tech stack. 

## 3. IBM Watson Assistant

IBM Watson Assistant is a chatbot SDK that provides tools for building conversational agents that can understand natural language and respond to user input. It can be integrated with various platforms and services to provide a seamless user experience.

IBM Watson Assistant was officially launched on 7 October 2021 and was envisioned as a tool that is designed to make it easier for businesses to create enhanced customer service experiences across any channel – phone, web, SMS and any messaging platform. It garnered much attention as it had the ability to add voice capabilities and set up a new phone number for a virtual agent quickly.

## 4. Microsoft Bot Framework

The Microsoft Bot Framework is a chatbot SDK that provides tools for building conversational agents that supports multiple programming languages. It also provides a flexible development environment for building custom chatbots. It is typically suitable for building enterprise-grade applications. This is where the business wants to keep a stringent control over the chatbot behavior. 

Microsoft Bot Framework was introduced in Microsoft Build 2016 event as a comprehensive framework for building enterprise-grade conversational AI experiences. Some of its highlight features include the ability to design and build conversational experiences with Language Understanding, QnA Maker, and a sophisticated composition of bot replies (Language Generation).

## 5. Amazon Lex

Amazon Lex is an artificial intelligence (AI) service with advanced natural language models to design, build, test, and deploy conversational interfaces in applications. It allows businesses to build chatbots with automatic speech recognition and natural language processing. Being an Amazon product, it has seamless integration with other Amazon services like AWS.

Amazon Lex was launched in April 2017 and was then released to the developer community. Some of its highlight features include automatic speech recognition (ASR) for converting speech to text, and natural language understanding (NLU) to recognize the intent of the text. The feather on its cap is that it is the brain that powers the Amazon Alexa virtual assistant.

How to build a chatbot using the Kommunicate chatbot SDK
Building a chatbot using the Kommunicate chatbot SDK is a simple and straightforward process. Kommunicate provides an easy-to-use chatbot builder that allows you to create your own chatbots without any coding. 

The builder has an intuitive interface that enables you to design the conversation flow of your chatbot and integrate it with external systems and services. Once you have designed and tested your chatbot, you can deploy it on your website or mobile app using Kommunicate’s powerful web and mobile SDKs.

Here is a longer narrative of each step involved in building a chatbot using the Kommunicate chatbot SDK.

## 1. Setting up the Development Environment 

To build a chatbot using the Kommunicate chatbot SDK, you first need to create an account with Kommunicate. Once you have created an account, you can access the Kommunicate dashboard and navigate to the bot section to start building your chatbot.

To know more about setting up the development environment, you can follow the steps listed here.

## 2. Designing the Chatbot Conversation Flow 

Kommunicate provides an easy-to-use chatbot builder that allows you to create your own chatbots without any coding framework. The builder has an intuitive interface that enables you to design the conversation flow of your chatbot by specifying the possible paths that the conversation can take and defining rules for how the chatbot should respond to different user inputs.

## 3. Integrating with External APIs and Services

Kommunicate has numerous integrations built into its platform, making it easy to connect your chatbot with external systems and services such as Zendesk, WhatsApp, Facebook Messenger, Google Analytics, etc. Further, there are integrations with customer relationship management (CRM) systems, databases, and payment processing systems.

We have detailed documentation on integrating Kommunicate with various external platforms. For beginners, you can find the steps to integrate WhatsApp with Kommunicate here. For more, please make sure to visit the Docs section on the Kommunicate website.

## 4. Testing and Deployment

Once you have designed your chatbot conversation flow and integrated it with any external systems or services, you can test your chatbot to ensure that it is functioning as intended. Kommunicate provides tools for testing your chatbot within its dashboard. Once you are satisfied with your chatbot’s performance, you can deploy it on your website or mobile app using Kommunicate’s powerful web and mobile SDKs.

## Conclusion

To bring it all together, a chatbot SDK provides developers with the tools and resources that they need to create and integrate chatbots into their applications. With the ability to easily design and deploy conversational AI, developers can improve user engagement and productivity. Further, as chatbot technology continues to evolve, the use of chatbot SDKs will become increasingly necessary for your business.