Amazon Kendra vs Gemini Notebook

Amazon Kendra is a cloud enterprise search service for websites and applications, available through APIs and the web. It uses machine learning to answer natural-language questions, match curated FAQs, and extract answers from HTML tables. The Kendra Retriever API supplies semantically relevant passages for retrieval-augmented generation, with access-control and metadata filtering and relevance tuning. Native connectors cover Amazon S3, Microsoft SharePoint, Salesforce, ServiceNow, Google Drive, and Confluence, while custom and partner connectors are supported. Experience Builder creates search applications without coding or machine-learning experience and integrates with AWS IAM Identity Center, Azure AD, and Okta. Search Analytics reports quality, usability, interaction, and content gaps. Document enrichment can add metadata, convert scans to text, classify files, extract entities, and transform content. Encryption, permission synchronization, answer citations, admin controls, and listed compliance programs are included. Pricing is paid, from $1.12 with a 30-day trial; no free plan.

Gemini Notebook, formerly NotebookLM, is a standalone research tool for organizing sources and answering questions grounded in those materials. It accepts PDFs, websites, YouTube videos, audio files, Google Docs, Google Slides, and other content. Answers include citations that point to exact source quotes. Audio Overview turns notebook material into a podcast-style discussion, while study notebooks can produce quizzes, interactive lessons, flashcards, and infographics from course materials. Notebooks can sync with Gemini Apps, where users can manage them and ask questions. A secure cloud computer can write and run code for source-grounded data analysis, with availability rolling out by plan. The Free plan costs nothing and includes 50 sources per notebook, 100 notebooks, 50 chat queries per day, and three audio generations per day. Named Google AI Plus, Pro, and Ultra plans list 2 TB, 5 TB, and 20 TB of storage, respectively, but no prices are listed. Individual data is not used to train the tool unless users provide feedback, which may permit review of the full interaction context. Workspace and Enterprise privacy terms differ, and some features require Keep Activity enabled.