Google

Google Cloud Vertex AI

Composite Score

8.8 /10

CX Score

9.0 /10

90 Reviews Write a Review

Claim Software

What is Google Cloud Vertex AI?

Cloud Machine Learning Engine is a managed service that lets developers and data scientists build and run superior machine learning models in production. Cloud ML Engine offers training and prediction services, which can be used together or individually. It has been used by enterprises to solve problems ranging from identifying clouds in satellite images, ensuring food safety, and responding four times faster to customer emails. The training and prediction services within ML Engine are now referred to as AI Platform Training and AI Platform Prediction.

Company Details

Need Assistance?

We're here to help you with understanding our reports and the data inside to help you make decisions.

Get Assistance

Awards & Recognition

Google Cloud Vertex AI won the following awards in the Machine Learning Platforms category

Filter By

2024 Emotional Footprint Champion

Latest Award, 2024

Service Experience

Latest Award, 2024

2024 Data Quadrant Champion

2024

1 Top Rated Capabilities

4 Top Rated Features

2024

2023 Emotional Footprint Champion

2023

Strategy and Innovation
Service Experience
Contract Negotiation

2023

2023 Data Quadrant Champion

2023

5 Top Rated Capabilities

11 Top Rated Features

2023

3 Top Rated Capabilities

9 Top Rated Features

2022

Google Cloud Vertex AI Ratings

Real user data aggregated to summarize the product performance and customer experience.
Download the entire Product Scorecard to access more information on Google Cloud Vertex AI.

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.

89 Likeliness to Recommend

98 Plan to Renew

2
Since last award

78 Satisfaction of Cost Relative to Value

2
Since last award

Product Experience

Negotiation and Contract

Conflict Resolution

Strategy & Innovation

Service Experience

undefined

{y}

{name}

Emotional Footprint Overview

Product Experience:: 95%
Negotiation and Contract:: 89%
Conflict Resolution:: 92%
Strategy & Innovation:: 94%
Service Experience:: 96%

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.

+94 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 Google Cloud Vertex AI?

3% Negative

2% Neutral

95% Positive

Pros

Performance Enhancing
Inspires Innovation
Respectful
Reliable

Feature Ratings

Average 81

Model Training

Data Exploration and Visualization

Explainability

Model Monitoring and Management

Feature Engineering

Data Labeling

Openness and Flexibility

Pre-Packaged AI/ML Services

Data Ingestion

Algorithm Diversity

Model Tuning

Vendor Capability Ratings

Average 79

Ease of Customization

Quality of Features

Ease of Implementation

Ease of Data Integration

Ease of IT Administration

Business Value Created

Breadth of Features

Vendor Support

Availability and Quality of Training

Product Strategy and Rate of Improvement

Usability and Intuitiveness

Google Cloud Vertex AI Reviews

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

Validated Review

Anonymous Reviewer

Submitted Oct 2020

A solid ML solution

Likeliness to Recommend

9 /10

Pros

Enables Productivity
Helps Innovate
Continually Improving Product
Reliable

dalhatu m.

Role: Student Academic
Industry: Agriculture
Involvement: Business Leader or Manager

Validated Review

Verified Reviewer

Submitted Mar 2020

very interested very good. and google is the most.

Likeliness to Recommend

10 /10

What differentiates Google Cloud Vertex AI from other similar products?

is very secure.

What is your favorite aspect of this product?

architecture

What do you dislike most about this product?

nothing yet.

What recommendations would you give to someone considering this product?

i should advice to use the google products always in your organization

Pros

Helps Innovate
Continually Improving Product
Reliable
Performance Enhancing

Google Cloud Vertex AI

What is Google Cloud Vertex AI?

Company Details

Need Assistance?

Awards & Recognition

2024 Emotional Footprint Champion

2024 Data Quadrant Champion

2023 Emotional Footprint Champion

2023 Data Quadrant Champion

Google Cloud Vertex AI Ratings

89 Likeliness to Recommend

98 Plan to Renew

2 Since last award

78 Satisfaction of Cost Relative to Value

2 Since last award

Emotional Footprint Overview

Emotional Footprint Overview

+94 Net Emotional Footprint

How much do users love Google Cloud Vertex AI?

Chart

Pros

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

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

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

Explainability Ability to explain/ visualize the model.

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

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

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

Openness and Flexibility Integration with open-source and 3P resources (languages, frameworks, libraries, etc.)

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

Data Ingestion Ability to access data from various sources on-prem and in the cloud and of various type: structured, unstructured, and semi-structured, real-time, etc.

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

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

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

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.

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

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

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.

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.

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.

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.

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.

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.

Google Cloud Vertex AI Reviews

A solid ML solution

Likeliness to Recommend

Pros

dalhatu m.

very interested very good. and google is the most.

Likeliness to Recommend

Pros

Most Popular Google Cloud Vertex AI Comparisons

MathWorks MATLAB

AWS Machine Learning

Microsoft Azure Machine Learning

Databricks Data Intelligence Platform

DataRobot AI Platform

KNIME Analytics Platform

2
Since last award

2
Since last award

Feature Ratings

Model Training

Data Exploration and Visualization

Explainability

Model Monitoring and Management

Feature Engineering

Data Labeling

Openness and Flexibility

Pre-Packaged AI/ML Services

Data Ingestion

Algorithm Diversity

Model Tuning

Vendor Capability Ratings

Ease of Customization

Quality of Features

Ease of Implementation

Ease of Data Integration

Ease of IT Administration

Business Value Created

Breadth of Features

Vendor Support

Availability and Quality of Training

Product Strategy and Rate of Improvement

Usability and Intuitiveness