Google

Google Cloud Vertex AI

Composite Score

8.7 /10

CX Score

8.9 /10

86 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 Gold Medalist

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 Gold Medalist

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

100 Plan to Renew

77 Satisfaction of Cost Relative to Value

1
Since last award

{y}

{name}

Emotional Footprint Overview

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.

+92 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

Feature Engineering

Data Labeling

Model Monitoring and Management

Data Ingestion

Openness and Flexibility

Pre-Packaged AI/ML Services

Model Tuning

Algorithm Diversity

Vendor Capability Ratings

Average 79

Ease of Customization

Quality of Features

Ease of Data Integration

Ease of Implementation

Ease of IT Administration

Business Value Created

Breadth of Features

Availability and Quality of Training

Vendor Support

Product Strategy and Rate of Improvement

Usability and Intuitiveness

Google Cloud Vertex AI Reviews

Vaibhav M.

Role: C-Level
Industry: Agriculture
Involvement: IT Leader or Manager

Validated Review

Verified Reviewer

Submitted Mar 2024

easy for the integration it provides so many free

Likeliness to Recommend

10 /10

What differentiates Google Cloud Vertex AI from other similar products?

Vertex AI provides a unified platform that seamlessly integrates data preparation, model training, deployment, and monitoring

What is your favorite aspect of this product?

develop high-quality models with less manual intervention.

What do you dislike most about this product?

Learning curve - requires an understanding of both generative ai and vertex ai concepts

What recommendations would you give to someone considering this product?

All-in-One We love it since now it can brings everything together under one roof of GCP, our team member can focus on one

Pros

Helps Innovate
Continually Improving Product
Enables Productivity
Trustworthy

Abhay C.

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

Validated Review

Verified Reviewer

Submitted Mar 2024

Effortlessly AI Empowering AI Projects with ease.

Likeliness to Recommend

8 /10

What differentiates Google Cloud Vertex AI from other similar products?

Google Cloud Vertex AI sets itself apart by seamlessly integrating with Google Cloud's ecosystem, offering easy to use AutoML features, pre - trained models, scalability and strong support for MLOps practices, making it a comprehensive and user - friendly choice for AI projects.

What is your favorite aspect of this product?

My favorite aspect of Google Cloud Vertex AI is its user - friendly interface, which makes it easy for both seasoned data scientists and newcomers to machine learning to navigate and utilize it's powerful tools effectively.

What do you dislike most about this product?

Somewhat I have found Google Cloud vertex AI pricing structure complex, which could lead to confusion or unexpected costs. Additionally, while platform offers a comprehensive set of features there may be Occasional gaps in documentation or support for very specific or niche use cases, which can be frustrating for users seeking detailed guidance.

What recommendations would you give to someone considering this product?

Before committing to Google Cloud Vertex AI, I'd suggest exploring its features and pricing thoroughly. Take advantage of trials or demos to see if it fits your project needs and team's expertise. Stay informed about updates that could enhance functionality.

Pros

Helps Innovate
Continually Improving Product
Reliable
Performance Enhancing

Puneet S.

Role: Information Technology
Industry: Engineering
Involvement: IT Leader or Manager

Validated Review

Verified Reviewer

Submitted Mar 2024

Interactive Platform for Beginners

Likeliness to Recommend

8 /10

What differentiates Google Cloud Vertex AI from other similar products?

Vertex AI from Google Cloud stands out due to its user-friendly interface, making machine learning accessible even to those without extensive expertise. Its advanced Auto ML features empower users to create high-quality models effortlessly, saving time and resources. Additionally, Vertex AI's seamless integration with Google Cloud services streamlines the entire ML workflow, enhancing efficiency and collaboration.

What is your favorite aspect of this product?

As a user I really appreciate Vertex AI's ability to democratize machine learning. Its user-friendly interface and powerful Auto ML features make complex tasks accessible to everyone, regardless of their expertise. Moreover, Vertex AI's seamless integration with Google Cloud services simplifies the entire process, allowing users to focus on innovation rather than logistical challenges.

What do you dislike most about this product?

One common concern could be the learning curve associated with leveraging its full potential. Despite its user-friendly interface, mastering all the features and capabilities might require significant time and effort, especially for those new to machine learning. Overall, while Vertex AI offers impressive capabilities, addressing these potential challenges could further enhance its accessibility and user satisfaction.

What recommendations would you give to someone considering this product?

Firstly understand why do you need this product, check weather your requirements are met by using this product. Experiment with the free tier or trial options to get a feel for how Vertex AI aligns with your specific use cases. Additionally, don't hesitate to reach out to the community or seek guidance from experts if you encounter any challenges or have questions. Collaborating with others can provide valuable insights and support as you navigate the learning curve.

Pros

Continually Improving Product
Saves Time
Fair
Transparent

Google Cloud Vertex AI

What is Google Cloud Vertex AI?

Company Details

Need Assistance?

Awards & Recognition

2024 Emotional Footprint Champion

2024 Data Quadrant Gold Medalist

2023 Emotional Footprint Champion

2023 Data Quadrant Gold Medalist

Google Cloud Vertex AI Ratings

89 Likeliness to Recommend

100 Plan to Renew

77 Satisfaction of Cost Relative to Value

1 Since last award

Emotional Footprint Overview

+92 Net Emotional Footprint

How much do users love Google Cloud Vertex AI?

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.

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

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.

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.

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.

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

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

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

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.

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.

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.

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.

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

Vaibhav M.

easy for the integration it provides so many free

Likeliness to Recommend

Pros

Abhay C.

Effortlessly AI Empowering AI Projects with ease.

Likeliness to Recommend

Pros

Puneet S.

Interactive Platform for Beginners

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

1
Since last award

Feature Ratings

Model Training

Data Exploration and Visualization

Explainability

Feature Engineering

Data Labeling

Model Monitoring and Management

Data Ingestion

Openness and Flexibility

Pre-Packaged AI/ML Services

Model Tuning

Algorithm Diversity

Vendor Capability Ratings

Ease of Customization

Quality of Features

Ease of Data Integration

Ease of Implementation

Ease of IT Administration

Business Value Created

Breadth of Features

Availability and Quality of Training

Vendor Support

Product Strategy and Rate of Improvement

Usability and Intuitiveness