Google

Google Cloud Vertex AI

Composite Score

8.7 /10

CX Score

8.9 /10

84 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

Inspires Innovation
Performance Enhancing
Effective Service
Respectful

Feature Ratings

Average 81

Model Training

Data Exploration and Visualization

Explainability

Data Labeling

Model Monitoring and Management

Feature Engineering

Data Ingestion

Openness and Flexibility

Pre-Packaged AI/ML Services

Model Tuning

Data Pre-Processing

Vendor Capability Ratings

Average 79

Quality of Features

Ease of Customization

Ease of Data Integration

Ease of Implementation

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

Kashish G.

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

Validated Review

Verified Reviewer

Submitted Jan 2025

Powerful BI tool

Likeliness to Recommend

10 /10

What differentiates Google Cloud Vertex AI from other similar products?

Its enterprise grade scalability and its deep integration with SAP system like SAP hana and SAP S/4 HANA, unlike other BI tools , it excels in handling large complex datasets while maintaining performance. Its robust scheduling and automation features for report delivery also distinguishes it .

What is your favorite aspect of this product?

Its customizability in reporting, the platform offers a powerful tools for creating highly detailed reports tailored to specific businesses needs. I particularly appreciate the drag and drop functionality in the web intelligence tool, which simplifies the report building process without requiring advanced coding skills.

What do you dislike most about this product?

Its main drawback is its complexity of the interface, which can be intimidating for new users. The initial learning curve is steep and the platform require substantial training to master. Another issues is the lack of real time collaboration features . While it excels within the tools.

What recommendations would you give to someone considering this product?

I will highly recommend the product but before implementing it , we should analyze the infrastructure and the resources to support it . Its excellence choice for companies already using SAP products or dealing with large complex data sets.

Pros

Continually Improving Product
Unique Features
Efficient Service
Fair

Paul S.

Role: C-Level
Industry: Consulting
Involvement: End User of Application

Validated Review

Verified Reviewer

Submitted Jan 2025

Fantastic product with good features

Likeliness to Recommend

9 /10

What differentiates Google Cloud Vertex AI from other similar products?

It is so fast in processing data and does not require any technical knowledge to use

What is your favorite aspect of this product?

The ease of setup of the tool and to deploy the tool,

What do you dislike most about this product?

Expensive to use the solution but worthy

What recommendations would you give to someone considering this product?

I would recommend the solution

Pros

Helps Innovate
Continually Improving Product
Reliable
Performance Enhancing

Jefferson A.

Role: Industry Specific Role
Industry: Engineering
Involvement: IT Development, Integration, and Administration

Validated Review

Verified Reviewer

Submitted Jan 2025

an excellent choice for both beginners and experts

Likeliness to Recommend

10 /10

What differentiates Google Cloud Vertex AI from other similar products?

Google Cloud Vertex AI stands out with its unified platform for managing the entire machine learning lifecycle, seamless integration with the Google Cloud ecosystem, and advanced AutoML capabilities that simplify model development without sacrificing performance.

What is your favorite aspect of this product?

The seamless integration of Vertex AI with other Google Cloud services, like BigQuery and Dataflow, makes managing large-scale machine learning projects incredibly efficient and streamlined.

What do you dislike most about this product?

The pricing structure can become unclear and expensive for long-running or large-scale projects, especially without careful cost monitoring.

What recommendations would you give to someone considering this product?

Leverage AutoML for Quick Start: If you're new to machine learning, start with Vertex AI's AutoML to quickly build and deploy models without needing deep expertise. Integrate with Google Cloud Ecosystem: Take advantage of tools like BigQuery and Dataflow for seamless data preparation and processing to maximize the platform's potential. Monitor Costs Closely: Use Google Cloud’s cost monitoring tools to keep track of expenses, especially if your projects involve extensive compute or data storage.

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.

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.

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

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.

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

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.

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.

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

Kashish G.

Powerful BI tool

Likeliness to Recommend

Pros

Paul S.

Fantastic product with good features

Likeliness to Recommend

Pros

Jefferson A.

an excellent choice for both beginners and experts

Likeliness to Recommend

Pros

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1
Since last award

Feature Ratings

Model Training

Data Exploration and Visualization

Explainability

Data Labeling

Model Monitoring and Management

Feature Engineering

Data Ingestion

Openness and Flexibility

Pre-Packaged AI/ML Services

Model Tuning

Data Pre-Processing

Vendor Capability Ratings

Quality of Features

Ease of Customization

Ease of Data Integration

Ease of Implementation

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