Description

• Amazon Kendra is an intelligent search service powered by machine learning.
• It reimagines enterprise search for websites and applications, enabling employees and customers to find content scattered across multiple locations and content repositories.

How It Works

• Amazon Kendra uses natural language processing and advanced machine learning algorithms to return specific answers to search questions from your data.
• It creates a unified search experience by connecting multiple data repositories to an index and ingesting and crawling documents.
• It uses its semantic and contextual understanding capabilities to decide whether a document is relevant to a search query.

Benefits

• Amazon Kendra is highly scalable and capable of meeting performance demands.
• It is tightly integrated with other AWS services such as Amazon S3 and Amazon Lex.
• It offers enterprise-grade security and provides a console and API for managing the documents that you want to search.

Limitations

• Amazon Kendra may be expensive for small businesses or organizations with limited budgets, particularly if indexing large volumes of data is required.
• It may require customization to work with specific data sources or search requirements, which could be time-consuming and may require technical expertise.

Features

• Amazon Kendra provides an optimized Kendra Retriever API that allows you to use Amazon Kendra’s high-accuracy semantic ranker as an enterprise retriever for your Retrieval Augmented Generation (RAG) workflow.
• It includes features like ACL-based filtering, relevance tuning, metadata-based filtering and more.
• It uses machine learning to deliver more-relevant answers from unstructured data.

Use Cases

• Amazon Kendra can enhance internal search experiences for employees, improving employee productivity and unlocking the insights employees need to make data-driven business decisions through a single search interface.