End of support notice: On September 15, 2025, AWS will discontinue support for Amazon Lex V1. After September 15, 2025, you will no longer be able to access the Amazon Lex V1 console or Amazon Lex V1 resources. If you are using Amazon Lex V2, refer to the Amazon Lex V2 guide instead. .

Step 1: Create an Amazon Kendra Index

Begin by creating an Amazon Kendra index of documents that answer customer questions. An index provides a search API for client queries. You create the index from source documents. Amazon Kendra returns answers it finds in indexed documents to the bot, which displays them to the agent.

The quality and accuracy of the responses suggested by Amazon Kendra depend on the documents that you index. Documents should include files that are frequently accessed by the agent and must be stored in an S3 bucket. You can index unstructured and semi-structured data in .html, Microsoft Office (.doc, .ppt), PDF, and text formats.

To create an Amazon Kendra index, see Getting started with an S3 bucket (console) in the Amazon Kendra Developer Guide.

To add questions and answers (FAQs) that help answer customer queries, see Adding questions and answers in the Amazon Kendra Developer Guide. For this tutorial, use the ML_FAQ.csv file on GitHub.

Next step

Step 2: Create an Amazon Lex Bot