Google

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

Shivam V.

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

Validated Review

Verified Reviewer

Submitted Mar 2024

Efficient, but watch out for pricing.

Likeliness to Recommend

8 /10

What differentiates Google Cloud Vertex AI from other similar products?

By seamlessly integrating tools for model creation, training, and deployment, Google Cloud Vertex AI increases accessibility to machine learning. The process is made simpler overall, freeing users to concentrate on problem-solving instead of infrastructure management.

What is your favorite aspect of this product?

One cool thing about Google Cloud Vertex AI is that it's easy to use and helps people who build and study machine learning to do their work better and faster because it has a simple layout and organized steps.

What do you dislike most about this product?

I find the pricing structure of Google Cloud Vertex AI complex or potentially costly, depending on their usage patterns and needs.

What recommendations would you give to someone considering this product?

Before using Google Cloud Vertex AI, take into account your ML requirements and financial constraints. To determine applicability and cost-effectiveness, start with smaller initiatives and make use of the resources that are available.

Pros

Helps Innovate
Continually Improving Product
Reliable
Performance Enhancing

Iyer A.

Role: Sales Marketing
Industry: Transportation
Involvement: Business Leader or Manager

Validated Review

Verified Reviewer

Submitted Mar 2024

Seamless Implementation, Medium Cost.

Likeliness to Recommend

8 /10

What differentiates Google Cloud Vertex AI from other similar products?

The main fact that google operates this means customer service, general guides, are all available at the drop of a hat. It was very easy for us to integrate this as the google suite employs many of our daily software anyway. Wide variety of inputs are acceptable. wide variety of AI models as well. Significantly faster process than other products tried.

What is your favorite aspect of this product?

The speed of setup, and time to a finished result was almost 50% less time consumed.

What do you dislike most about this product?

The price tag is a bit much.

What recommendations would you give to someone considering this product?

If you have unlimited budget, and only a light understanding of the services needed, this is a GREAT first choice.

Pros

Reliable
Enables Productivity
Trustworthy
Efficient Service

Abhiraj B.

Role: Student Academic
Industry: Engineering
Involvement: End User of Application

Validated Review

Verified Reviewer

Submitted Mar 2024

Excellent Tool :

Likeliness to Recommend

10 /10

What differentiates Google Cloud Vertex AI from other similar products?

Google Cloud Vertex AI stands apart from others for its versatility and ease of integration with other google technologies, like GC Bucket or Big Query along with this AI

What is your favorite aspect of this product?

My favourite aspect of this product is its pre trained models and ample examples available for learning purposes..

What do you dislike most about this product?

Restarting a kernel is a problematic issue. Often causes problems in the notebook.

What recommendations would you give to someone considering this product?

Definitely worth investing in if you have priorities in streamlining certain jobs, or seamlessly analysing data using existing AI Models.

Pros

Helps Innovate
Reliable
Enables Productivity
Trustworthy

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

Shivam V.

Efficient, but watch out for pricing.

Likeliness to Recommend

Pros

Iyer A.

Seamless Implementation, Medium Cost.

Likeliness to Recommend

Pros

Abhiraj B.

Excellent Tool :

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