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Google Cloud Vertex AI

8.6 /10

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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.

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Awards & Recognition

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

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2023 Emotional Footprint Champion

Latest Award, 2023

Strategy and Innovation
Service Experience
Contract Negotiation

Latest Award, 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.

88 Likeliness to Recommend

1
Since last award

99 Plan to Renew

1
Since last award

75 Satisfaction of Cost Relative to Value

3
Since last award

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Emotional Footprint Overview

+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?

4% Negative

3% Neutral

93% Positive

Pros

Inspires Innovation
Respectful
Performance Enhancing
Effective Service

Feature Ratings

Average 80

Model Training

Data Exploration and Visualization

Pre-Packaged AI/ML Services

Explainability

Data Labeling

Feature Engineering

Openness and Flexibility

Model Monitoring and Management

Data Ingestion

Algorithm Diversity

Data Pre-Processing

Vendor Capability Ratings

Average 78

Ease of Data Integration

Ease of IT Administration

Vendor Support

Ease of Customization

Product Strategy and Rate of Improvement

Availability and Quality of Training

Ease of Implementation

Quality of Features

Breadth of Features

Business Value Created

Usability and Intuitiveness

Google Cloud Vertex AI Reviews

Atharva V.

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

Validated Review

Verified Reviewer

Submitted Apr 2024

Exciting Potential of Vertex AI

Likeliness to Recommend

10 /10

What differentiates Google Cloud Vertex AI from other similar products?

Google Cloud Vertex AI is unique because it easily fits into Google Cloud's setup, making it simple to work with services such as BigQuery and TensorFlow. Plus, its automated machine learning tools make it easier for users at any skill level to build models, simplifying everything from preparing data to putting models into implementation.

What is your favorite aspect of this product?

What I really like about this product is how easily it works alongside other Google Cloud services, making everything flow more smoothly. Also, the automated machine learning tools are a big help in simplifying the process of building models, especially for someone like me.

What do you dislike most about this product?

My biggest issue with this product is its lack of support for some advanced customization choices. Also, I find the pricing a bit confusing and high.

What recommendations would you give to someone considering this product?

Use the trial to test its features and gather feedback from other users to make an decision.

Pros

Helps Innovate
Enables Productivity
Unique Features
Inspires Innovation

Cons

Less Generous

Kumar A.

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

Validated Review

Verified Reviewer

Submitted Mar 2024

Awesome and user friendly

Likeliness to Recommend

9 /10

What differentiates Google Cloud Vertex AI from other similar products?

Google Cloud Vertex AI stands out from other similar products with its unified platform offering end-to-end machine learning lifecycle management, streamlined model development workflows, automated hyperparameter tuning, built-in model deployment, and integration with Google Cloud's powerful infrastructure and AI capabilities, all aimed at accelerating AI adoption and deployment for businesses.

What is your favorite aspect of this product?

one notable aspect of Google Cloud Vertex AI is its comprehensive suite of tools and services that streamline the entire machine learning lifecycle, making it easier for developers and data scientists to build, train, deploy, and manage AI models efficiently.

What do you dislike most about this product?

I dont have any dislike about this

What recommendations would you give to someone considering this product?

For someone considering Google Cloud Vertex AI, I would recommend thoroughly exploring its features and capabilities to ensure they align with your specific use case and requirements. Additionally, take advantage of available documentation, tutorials, and support resources to maximize the benefits of the platform. It's also advisable to start with small projects or proofs of concept to familiarize yourself with the platform before scaling up to larger deployments. Lastly, consider factors such as cost, integration with existing workflows, and potential future scalability when making your decision.

Pros

Helps Innovate
Continually Improving Product
Reliable
Performance Enhancing

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

Google Cloud Vertex AI

What is Google Cloud Vertex AI?

Company Details

Need Assistance?

Awards & Recognition

2023 Emotional Footprint Champion

2023 Data Quadrant Gold Medalist

Google Cloud Vertex AI Ratings

88 Likeliness to Recommend

1 Since last award

99 Plan to Renew

1 Since last award

75 Satisfaction of Cost Relative to Value

3 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.

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

Explainability Ability to explain/ visualize the model.

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

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

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

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.

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

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

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.

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.

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.

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.

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.

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.

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.

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.

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.

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

Atharva V.

Exciting Potential of Vertex AI

Likeliness to Recommend

Pros

Cons

Kumar A.

Awesome and user friendly

Likeliness to Recommend

Pros

Vaibhav M.

easy for the integration it provides so many free

Likeliness to Recommend

Pros

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Feature Ratings

Model Training

Data Exploration and Visualization

Pre-Packaged AI/ML Services

Explainability

Data Labeling

Feature Engineering

Openness and Flexibility

Model Monitoring and Management

Data Ingestion

Algorithm Diversity

Data Pre-Processing

Vendor Capability Ratings

Ease of Data Integration

Ease of IT Administration

Vendor Support

Ease of Customization

Product Strategy and Rate of Improvement

Availability and Quality of Training

Ease of Implementation

Quality of Features

Breadth of Features

Business Value Created

Usability and Intuitiveness