An online learning company with large volumes of education materials wants to use enterprise search.

The correct answer is C – Amazon Kendra, AWS’s enterprise search service designed for organizations with large, diverse document repositories. Kendra uses machine learning and natural language understanding (NLU) to provide semantic search, meaning it retrieves results based on meaning rather than keyword matching. According to AWS documentation, Kendra is ideal for educational, enterprise, and knowledge-management scenarios where users need fast, accurate retrieval across PDFs, HTML, Office documents, FAQs, and multimedia transcripts. Kendra connectors can index content from S3, SharePoint, LMS platforms, and internal databases, making it perfect for large volumes of training materials. Amazon Comprehend (A) is for NLP tasks like entity extraction, not enterprise search. Amazon Textract (B) extracts text from PDFs and scanned materials but does not provide search capabilities. Amazon Personalize (D) is for personalized recommendations, not document retrieval. Kendra is purpose-built for enterprise search and aligns directly with the company's needs.

Referenced AWS Documentation:

Amazon Kendra Developer Guide – Enterprise Search

AWS ML Specialty Guide – Intelligent Search Systems