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?

Amazon Q is a knowledge management system developed by Amazon Web Services (AWS) in 2022. It is designed to help teams collaborate and access information across an organization using natural language.

The main features of Amazon Q include:

  • Q&A repository - A searchable store of questions and answers created by users, tagged and organized.
  • Expert routing - Uses machine learning to route questions to the most relevant subject matter experts.
  • Conversation - Enables back-and-forth dialogue to clarify questions and give better answers.
  • Content insights - Provides analytics about content gaps to improve knowledge sharing.
  • Integrations - Integrates with popular business apps like Slack, Salesforce, and AWS services.

Amazon Q applies innovations in language AI to improve discoverability of information at scale for enterprises. Its conversational interface makes it easy for employees to get information they need while capturing this tribal knowledge in a shareable format. As more content is added, Amazon Q gets smarter at routing and answering questions automatically.

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

15 reviews

Rating Breakdown
Ease of Use
3.7
Features
3.5
Value for Money
2.9
Customer Support
3.5
Overall Experience
3.4
Recent Reviews
M
Michael Smith
Mar 29, 2026
Promising concept, disappointing execution

We implemented Amazon Q hoping to improve cross-departmental knowledge sharing, but it consistently surfaces irrelevant or outdated information. The search algorithm seems to prioritize volume over accuracy, leading to frustrating searches and wasted time. For the price, we expected much …

S
Sophia Jackson
Mar 29, 2026
Great potential but a bit unpolished

Amazon Q is powerful when it works, saving us a lot of time finding internal documentation and experts. The machine learning model generally surfaces the right document or contact quickly. However, the search can sometimes be too rigid, missing relevant …

avery_smith61
Avery Smith
Mar 27, 2026
Finally broke down our information silos

Amazon Q has transformed how our distributed team finds answers. Instead of endless email chains, we get instant, accurate responses from company documentation and experts. The machine learning gets smarter with each query, and it's surprisingly good at connecting us …

L
Lisa Jackson
Mar 24, 2026
Frustrating experience with Amazon Q

Amazon Q frequently surfaces outdated or irrelevant answers to my questions, making it unreliable for finding accurate information. The interface is clunky and slow, and I often end up asking colleagues directly instead. For a machine learning tool, it feels …

mwalker1723
Morgan Walker
Mar 22, 2026
Great for finding experts, but the AI answers need work

Amazon Q is fantastic for quickly finding the right person to talk to in our large company - the expert search feature saved us hours of hunting. However, the machine-generated answers are often incomplete or slightly off-target, requiring us to …

Rating Distribution
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