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Google Cloud Vertex AI

Composite Score

8.7 /10

CX Score

8.9 /10

86 Reviews Write a Review

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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

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Awards & Recognition

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

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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

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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

Vijayraj H.

Role: Information Technology
Industry: Technology
Involvement: End User of Application

Validated Review

Verified Reviewer

Submitted Mar 2024

Streamlined and Powerful, star AI platform

Likeliness to Recommend

10 /10

What differentiates Google Cloud Vertex AI from other similar products?

Google Cloud Vertex AI distinguishes itself through its comprehensive suite of features, offering a unified environment for ML development, advanced AutoML capabilities, seamless integration with Google Cloud services, scalability, and robust monitoring functionality.

What is your favorite aspect of this product?

A standout feature of Google Vertex AI is its powerful AutoML capabilities, which enable users to create custom machine learning models with ease. This empowers developers with varying levels of expertise to leverage advanced machine learning techniques and create high-quality models tailored to their specific needs and requirements.

What do you dislike most about this product?

One aspect of Google Vertex AI that users may find challenging is the complexity of its pricing structure. Understanding and managing costs within the Google Cloud ecosystem, including Vertex AI, can be intricate and potentially lead to unexpected expenses if not carefully monitored. Additionally, users might find it difficult to predict and optimize their expenditure, especially when dealing with fluctuating resource usage or scaling requirements within their machine learning projects.

Pros

Continually Improving Product
Reliable
Performance Enhancing
Unique Features

Tushar M.

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

Validated Review

Verified Reviewer

Submitted Mar 2024

Powerful but pricey AI solution.

Likeliness to Recommend

10 /10

What differentiates Google Cloud Vertex AI from other similar products?

Google Cloud Vertex stands out due to its streamlined workflow for machine learning tasks offering autoML capabilities, pre-trained models, and unified Al platform integration. It’s ease of use, scalability, and comprehensive feature set distinguish, making AI development accessible and efficient for business of all size.

What is your favorite aspect of this product?

My favourite aspect of Google Cloud Vertex AI is its user friendly interface and seamless integration, making complex AI tasks accessible to everyone.

What do you dislike most about this product?

The pricing structure can be complex and potentially expensive for heavy usage, limiting accessibility for smaller businesses or startups.

What recommendations would you give to someone considering this product?

For optimal utilisation, I recommend thoroughly exploring the pricing structure, leveraging available documentation and supports resources, and starting with smaller scale projects to gauge cost effectiveness and suitability for a specific needs.

Pros

Helps Innovate
Continually Improving Product
Reliable
Enables Productivity

Gangaraboina Lalit K.

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

Validated Review

Verified Reviewer

Submitted Mar 2024

It was great product and it is very easy to use.

Likeliness to Recommend

9 /10

What differentiates Google Cloud Vertex AI from other similar products?

Google Cloud Vertex AI is definitely a very good product. And it stands out due to its seamless integration with all other google cloud products. It is easy to use and this product is friendly with client. vertex AI is flexibility and supporting various machine learning frameworks.

What is your favorite aspect of this product?

My favorite aspect about this product is seamless intregration between other google cloud product. all over i love the ecosystem between google clouds.

What do you dislike most about this product?

I don't have any personnel about this product, but i think pricing is bit high.

What recommendations would you give to someone considering this product?

I will definitely recommend about this product like how well the platfrom intregrate with tools and clouds. This product is very user-friendly with client. And it is easy to use and understand.

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 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

Vijayraj H.

Streamlined and Powerful, star AI platform

Likeliness to Recommend

Pros

Tushar M.

Powerful but pricey AI solution.

Likeliness to Recommend

Pros

Gangaraboina Lalit K.

It was great product and it is very easy to use.

Likeliness to Recommend

Pros

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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