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 AssistanceGoogle 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
98 Plan to Renew
78 Satisfaction of Cost Relative to Value
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.
+94 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?
Pros
- Performance Enhancing
- Reliable
- Inspires Innovation
- Respectful
How to read the Emotional Footprint
The Net Emotional Footprint measures high-level user sentiment towards particular product offerings. It aggregates emotional response ratings for various dimensions of the vendor-client relationship and product effectiveness, creating a powerful indicator of overall user feeling toward the vendor and product.
While purchasing decisions shouldn't be based on emotion, it's valuable to know what kind of emotional response the vendor you're considering elicits from their users.
Footprint
Negative
Neutral
Positive
Feature Ratings
Model Training
Explainability
Data Exploration and Visualization
Model Monitoring and Management
Pre-Packaged AI/ML Services
Feature Engineering
Data Ingestion
Openness and Flexibility
Data Labeling
Algorithm Diversity
Model Tuning
Vendor Capability Ratings
Ease of Customization
Quality of Features
Ease of Implementation
Ease of Data Integration
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
- Role: Information Technology
- Industry: Technology
- Involvement: Business Leader or Manager
Submitted Nov 2022
Fantastic product
Likeliness to Recommend
Pros
- Continually Improving Product
- Enables Productivity
- Unique Features
- Efficient Service
Please tell us why you think this review should be flagged.
Sahil K.
- Role: Information Technology
- Industry: Energy
- Involvement: End User of Application
Submitted Sep 2022
" Low code Machine learning tool"
Likeliness to Recommend
What differentiates Google Cloud Vertex AI from other similar products?
Google cloud ML engine stand out from other because of 1) Low coding 2) Computer Vision 3) Natural Language Processing 4) Large data processing 5) Less Learning time 6) Model efficiency monitoring 7) Sustainable ML model 8) Model deployment is easy 9) Data processing in Real time
What is your favorite aspect of this product?
1) Pre built Model 2) Computer Vision 3) Natural Language Processing 4) Natural Language Generation
What do you dislike most about this product?
Learning time of computer vision
What recommendations would you give to someone considering this product?
It is great as you do not need to want to spend time customizing AI libraries and algorithms and data will already be in Cloud - Easy Integration with google BigQuery and google Pubsub that makes it easy to have a ready to use pipeline from data ingestion to analysis - Its CV algorithms and video processing modules makes it easy to use image/video processing application and use cases
Pros
- Helps Innovate
- Reliable
- Performance Enhancing
- Enables Productivity
Please tell us why you think this review should be flagged.
Luis A.
- Role: Information Technology
- Industry: Technology
- Involvement: IT Leader or Manager
Submitted Nov 2021
The challenges and solutions have become clearer
Likeliness to Recommend
What differentiates Google Cloud Vertex AI from other similar products?
AutoML (VertexAI), a new GCP service, integrates with various open-source machine learning frameworks (TensorFlow, PyTorch, sci-kit-learn). As a consequence, we were able to shift from on-premises open source ML to the cloud while preserving the added value of AutoML. Vertex AI is a relatively new technology (in May 2021). I was thrilled to see that Google Cloud Machine Learning Engine has just recently introduced TensorFlow to the cloud, but rivals have already begun using AutoML, so this Google cloud service appears to be following and evolving.
What is your favorite aspect of this product?
It's a cloud-based service that's been there for a long time as TensorFlow, but it's lately been reformed as a new integrated ML platform, ContactCenterAI, VertexAI, DocumentAI, and the difficulties and solutions. AutoML, which is included in Vertex AI, is very important. AutoML is a method that has gained a lot of attention in the machine learning field in recent years, but it is incredibly welcome that it is now being covered in full in a cloud machine learning service that even novices can use with reasonable ease.
What do you dislike most about this product?
As said in the positives, improving issues and solutions is a good flow, and the AI and ML disciplines are rapidly increasing, therefore I'd want to see you extend the examples and templates while introducing new technologies.
What recommendations would you give to someone considering this product?
I was able to easily switch to the GCP cloud while receiving the added functionality of AutoML by utilizing PyTorch and SciKit-Learn in my local environment. It's wonderful that AutoML = Vertex AI is now available on GCP. We've been following Vertex AI since before it was launched, and it's now a reasonable quality as part of AutoML, and we're working hard to aggressively hire in-house people. The good news is that "it has evolved to the point where Vertex AI can be implemented" based on this approach.
Pros
- Helps Innovate
- Continually Improving Product
- Reliable
- Enables Productivity
Please tell us why you think this review should be flagged.
Get Instant Access<br>to this Report
Get Instant Access
to this Report
Unlock your first report with just a business email. Register to access our entire library.
© 2025 SoftwareReviews.com. All rights reserved.
