MLS-C01 Question 299
Select 3You are building a customer support chatbot for your organization using AWS services. The chatbot needs to understand natural language queries and respond appropriately. It should also be able to connect to a backend database to retrieve customer information when required. Which combination of AWS services should you use to implement this solution?
- A
Amazon Lex
- B
Amazon Comprehend
- C
Amazon DynamoDB
- D
Amazon SageMaker
- E
AWS Lambda
Show answer and explanation
Correct answers: A, C, E
Explanation
The correct combination of services for building a customer support chatbot includes Amazon Lex for natural language understanding, Amazon DynamoDB for storing and retrieving customer data, and AWS Lambda for the backend logic. Amazon Comprehend and SageMaker are not directly relevant to the stated requirements, as the scenario focuses on building a chatbot with data retrieval capabilities rather than text analysis or custom machine learning models.
- A. Correct.
Amazon Lex is the correct choice for building conversational interfaces such as chatbots. It provides natural language understanding and automatic speech recognition capabilities.
- B. Incorrect.
Amazon Comprehend is used for text analysis and understanding but is not suitable for building a full chatbot. It could complement Lex but is not necessary for this specific task.
- C. Correct.
Amazon DynamoDB is a good choice for storing and retrieving customer data because it is a highly scalable NoSQL database service that integrates well with other AWS services.
- D. Incorrect.
Amazon SageMaker is used for building, training, and deploying machine learning models and is not directly relevant to building a chatbot in this scenario.
- E. Correct.
AWS Lambda is useful for executing backend logic, such as retrieving data from DynamoDB or performing other operations in response to user queries through the chatbot.