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Table of contents
1.
What is a ChatBot?
2.
Amazon Lex 
3.
Use-Case of a ChatBot
4.
Working of Lex Bot
5.
Frequently Asked Questions
6.
Conclusion
Last Updated: Mar 27, 2024

Amazon Lex

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What is a ChatBot?

ChatBot, as the name suggests, is a robot made for chatting. ChatBot works by mimicking human beings such that the users feel that they are having a conversation with a real person. ChatBots have a wide range of applications in the customer care segments.

As the companies scale up, their number of customers also increases exponentially. It becomes physically impossible to deal with each customer manually at one point. Sometimes the problems are also repetitive & less complex. In such scenarios, using chatbots, we can suggest some elementary solutions to the user & forward more complex issues to the customer care agent.

 

A basic ChatBot that uses if-else statements is known as Command Bot. Command Bots generally give errors or default messages when a new/unseen command is entered.

A better & more complex version of ChatBot is a Learning Bot. Learning Bots uses Machine Learning and NLP algorithms to learn from the commands entered. 

Amazon Lex
 

Source: aws.amazon.com

Amazon Lex is a tool provided by Amazon that helps us make chatbots on the AWS architecture. Companies can build customized chatbots with amazon lex and easily integrate them into their applications.
 

Amazon Alexa is also built using amazon's lex, and it uses the same underlying AWS architecture.

 

Amazon Lex chatbots use Natural Language Processing to convert a person’s speech into machine language & Natural Language Understanding to understand the intent or meaning of the text. The best part about amazon lex is that the developer does not require any machine learning, NLP, or Deep learning knowledge to build chatbots.

Use-Case of a ChatBot

Suppose a user wants to know his account balance without physically going to a branch. A conventional way would be to ask a customer care executive; the executive will manually authorize the person & then provide him with the account details, including the balance. With this method, the problem would be if, at the same time, many users call customer service to inquire about their balances; some will have to wait till an executive gets free to talk to them. The bank will also require to employ more customer care executives as they scale up.

 

A better solution for this problem would be to deploy a ChatBot on the Banking website. The customers can directly interact with the ChatBots to inquire about their banking details. The ChatBot will authenticate the customer and provide a set of choices to choose from. If the customer query is more complex, it can be re-directed to an execute.

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Working of Lex Bot

Let’s understand how we can use amazon's lex for the above use-case.
 

Source: aws.amazon.com

  1. The customer will visit the Bank’s website or mobile application.
  2. They can connect easily with ChatBot made using Amazon Lex from the website.
  3. The customer will inquire/enter that they want to know the account balance.
  4. The Lex Bot will understand the query using NLP and NLU.
  5. The Lambda function will fetch the balance from the AWS storage database.
  6. The return value is shown to the customer on the Lex Bot interface.

Frequently Asked Questions

1. What is Amazon Lex?

Amazon Lex is a tool provided by Amazon that helps us make chatbots on the AWS architecture. Companies can build customized chatbots with amazon lex and easily integrate them into their applications.

 

2. How does a ChatBot works?

ChatBot works by mimicking human beings such that the users feel that they are having a conversation with a real person.
 

3. What are the use cases of Lex Bot?

The lex bot has a wide range of use-cases in the customer care segment. We can also use it as an interactive virtual response (IVR) assistant or as a virtual voice agent.
 

4. Which companies have adopted Amazon Lex?

There are many companies using Amazon Lex for a wide variety of applications like Vanguard, DropBox, Oklahoma City, etc.

Conclusion

The data in the world is growing at a really fast pace. When combined with Big Data and Cloud Computing, Machine Learning can help businesses optimize their working power & increase productivity.

Check out this link if you are a Machine Learning enthusiast or want to brush up on your knowledge with ML blogs.

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