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Amazon Q

Amazon Q

Amazon Q is a cloud-based knowledge sharing service that enables teams to access information and subject matter experts across their organization. It uses machine learning to surface relevant answers to questions.
Amazon Q screenshot

Amazon Q: Cloud-Based Knowledge Sharing for Teams

A cloud-based knowledge sharing service enabling teams to access information and subject matter experts across their organization, powered by machine learning to surface relevant answers to questions.

What is Amazon Q?

What Is Amazon Q?

Amazon Q is an AI-powered assistant built by AWS for business and developer use cases. It connects to your company's data sources — wikis, intranets, Jira, Salesforce, S3, and more — to answer questions, generate content, and take actions based on your organization's knowledge.

Key Features

Amazon Q Business lets employees ask questions in natural language and get answers sourced from connected enterprise data, with citations. It respects existing access controls, so users only see information they are authorized to access.

Amazon Q Developer (formerly CodeWhisperer) provides AI code generation, debugging, transformation, and explanation directly in IDEs. It can modernize Java applications, generate unit tests, and explain unfamiliar codebases.

Pricing

Amazon Q Business starts at 3 dollars per user per month for the Lite tier. Amazon Q Developer has a free tier for individual developers, with Pro at 19 dollars per user per month adding higher limits and administrative features.

Amazon Q Features

Features

  1. Allows teams to access information across the organization
  2. Surfaces relevant answers to questions using machine learning
  3. Provides access to subject matter experts
  4. Enables knowledge sharing within teams

Pricing

  • Subscription-Based

Pros

Improves access to organizational knowledge

Leverages AI for better search results

Connects employees for expertise sharing

Promotes collaboration and knowledge transfer

Cons

May require change management for adoption

AI accuracy depends on quality of data

Knowledge silos may still exist if not widely adopted

Additional training required for users

Reviews & Ratings

Login to Review
3.5

57 reviews

Rating Breakdown
Ease of Use
3.8
Features
3.4
Value for Money
3.0
Customer Support
3.4
Overall Experience
3.5
Recent Reviews
ava_davis86
Ava Davis
May 26, 2026
A powerful tool when it works, but still feels like a beta product

Amazon Q is brilliant at pulling up relevant documents and connecting us to the right people when its machine learning nails the query. However, it often provides outdated or completely irrelevant answers, forcing us to double-check everything, which defeats the …

skyler_hill22
Skyler Hill
May 23, 2026
A Game-Changer for Finding Internal Information

Amazon Q has dramatically reduced the time our team spends searching for internal documentation or pinging colleagues. It consistently surfaces the right Confluence page or connects us with the correct subject matter expert in seconds. The AI is surprisingly accurate …

marcusdigital237
Marcus Jackson
May 19, 2026
Promising Concept, Poor Execution

Amazon Q constantly surfaces irrelevant or outdated information when we ask questions, often directing us to experts who left the company years ago. The search is unreliable, and the AI's confidence in wrong answers is frustrating. For the high cost, …

djackson7121
Dakota Jackson
May 19, 2026
A Promising Tool Still Finding Its Feet

Amazon Q is a solid concept and works decently for straightforward searches, but it often struggles with nuanced or context-heavy questions, delivering generic or unrelated answers. The machine learning feels underdeveloped compared to other AI assistants, and the user interface …

cjackson2900
Chris Jackson
May 15, 2026
Frustratingly Inaccurate and Limited in Scope

Amazon Q consistently fails to provide relevant answers to our team's questions, often surfacing outdated or completely unrelated information from our knowledge base. The machine learning seems poorly trained for our organizational structure, and we've wasted countless hours chasing down …

Rating Distribution
5
22
4
6
3
13
2
16
1
0

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