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Amazon

Amazon Q

Composite Score

7.3 /10

CX Score

7.6 /10

5 Reviews Write a Review

What is Amazon Q?

Amazon Q is a generative AI assistant that transforms how work gets done in your organization. With specialized capabilities for software developers, business intelligence analysts, contact center employees, supply chain analysts, and anyone building with AWS, Amazon Q helps every employee get insights on their data and accelerate their tasks. Leveraging Amazon Q's advanced agentic capabilities, companies can streamline processes, get to decisions faster, and help employees be more productive.

Company Details

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Amazon Q Ratings

Real user data aggregated to summarize the product performance and customer experience.

Product scores listed below represent current data. This may be different from data contained in reports and awards, which express data as of their publication date.

78 Likeliness to Recommend

60 Plan to Renew

75 Satisfaction of Cost Relative to Value

100

Product Experience

Negotiation and Contract

Conflict Resolution

Strategy & Innovation

100

Service Experience

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Emotional Footprint Overview

Product Experience:: 100%
Negotiation and Contract:: 92%
Conflict Resolution:: 92%
Strategy & Innovation:: 96%
Service Experience:: 100%

Product scores listed below represent current data. This may be different from data contained in reports and awards, which express data as of their publication date.

+97 Net Emotional Footprint

The emotional sentiment held by end users of the software based on their experience with the vendor. Responses are captured on an eight-point scale.

How much do users love Amazon Q?

0% Negative

0% Neutral

100% Positive

Pros

Helps Innovate
Continually Improving Product
Reliable
Performance Enhancing

Feature Ratings

Average 78

Data Labeling

Model Monitoring and Management

Algorithm Recommendation

Model Tuning

Model Training

Algorithm Diversity

Pre-Packaged AI/ML Services

Data Exploration and Visualization

Performance and Scalability

Feature Engineering

Data Pre-Processing

Vendor Capability Ratings

Average 77

Availability and Quality of Training

Ease of Implementation

Ease of IT Administration

Vendor Support

Quality of Features

Ease of Customization

Ease of Data Integration

Usability and Intuitiveness

Product Strategy and Rate of Improvement

Breadth of Features

Business Value Created

Amazon Q Reviews

Oluwaseun E.

Role: Information Technology
Industry: Technology
Involvement: IT Development, Integration, and Administration

Validated Review

Verified Reviewer

Submitted Mar 2025

The software is good if only you as a user know it

Likeliness to Recommend

8 /10

What differentiates Amazon Q from other similar products?

It's the most capable generative AI-powered assistant for building, operating, and transforming software, with advanced capabilities.

What is your favorite aspect of this product?

It is it's ability to help write codes and answers some questions

What do you dislike most about this product?

It does make use of hallucinations thereby influencing it's response sometimes

What recommendations would you give to someone considering this product?

My recommendation will be that the user understands the intricacies that surrounds Amazon q and hoe it works to avoid getting wrong code and the user learning how to debug at least to know where the problem is in case there's error

Pros

Helps Innovate
Continually Improving Product
Reliable
Enables Productivity

Latest Research

Amazon Q

What is Amazon Q?

Company Details

Need Assistance?

Amazon Q Ratings

78 Likeliness to Recommend

60 Plan to Renew

75 Satisfaction of Cost Relative to Value

Emotional Footprint Overview

Emotional Footprint Overview

+97 Net Emotional Footprint

How much do users love Amazon Q?

Chart

Pros

Feature Ratings Average rating of all product features, some of which may not be shown below

Data Labeling Ability to annotate/ label data to create a training data set.

Model Monitoring and Management Ability to monitor model use and performance in production, incl. identifying models for refresh and/or replacement.

Algorithm Recommendation Ability to recommend a best ML algorithm to use based on dataset characteristics.

Model Tuning Ability to fine-tune models based on monitoring feedback within the platform.

Model Training Ability to train a model with a range of data sets that you provide.

Algorithm Diversity Provides multiple diverse ready-to-use machine learning algorithms out-of-the-box.

Pre-Packaged AI/ML Services Pre-trained models and associated resources, e.g., for forecasting, recommendations, image and video analysis, NLP, voice, etc.

Data Exploration and Visualization Ability to visually manipulate, interact with, and explore data, and perform basic descriptive statistics and pattern detection.

Performance and Scalability Systems performance (time) and scalability end-to-end: from data load and processing to model creation and deployment.

Feature Engineering Ability to extract and build features from raw data.

Data Pre-Processing Ability to wrangle or pre-process data to ready it for model training.

Vendor Capability Ratings Average rating of all vendor capabilities, some of which may not be shown below

Availability and Quality of Training Effective and readily available training enables users to get the most out of the software you've chosen. Use this section to make sure your vendor's training programs and materials measure up.

Ease of Implementation Successfully implementing new software is necessary to realize its full value and promote end user adoption. This data indicates whether or not the product is easy to implement.

Ease of IT Administration This data indicates whether IT personnel will be able to resolve issues and perform configurations efficiently and effectively.

Vendor Support The importance of vendor support will vary for each organization depending on internal capabilities, but there will always be issues that only the vendor can resolve.

Quality of Features Feature quality is just as important as quantity. Use this data to determine if this product will do what you're purchasing it to do, easily, intuitively, reliably, and effectively.

Ease of Customization Don't get bogged down in a difficult customization; use this data to make sure you can easily achieve the functionality you need for your particular situation.

Ease of Data Integration Use this data to determine whether the product will cause headaches or make data integration easy.

Usability and Intuitiveness End user learning curves cost the organization money. Pay attention to your end users' technical ability to determine how important UX is in your purchase.

Product Strategy and Rate of Improvement Vendors who don't stay on top of emerging needs and trends won't enable you to meet your business goals. Use this data to separate innovators from imposters.

Breadth of Features Users prefer feature rich software that enables them to perform diverse series of tasks. This data expresses user satisfaction with the product's breadth of features.

Business Value Created Software needs to create value for employees, customers, partners, and, ultimately, shareholders. This data expresses user satisfaction - or lack thereof - with the product's business value.

Amazon Q Reviews

Oluwaseun E.

The software is good if only you as a user know it

Likeliness to Recommend

Pros

Title

Feature Ratings

Data Labeling

Model Monitoring and Management

Algorithm Recommendation

Model Tuning

Model Training

Algorithm Diversity

Pre-Packaged AI/ML Services

Data Exploration and Visualization

Performance and Scalability

Feature Engineering

Data Pre-Processing

Vendor Capability Ratings

Availability and Quality of Training

Ease of Implementation

Ease of IT Administration

Vendor Support

Quality of Features

Ease of Customization

Ease of Data Integration

Usability and Intuitiveness

Product Strategy and Rate of Improvement

Breadth of Features

Business Value Created