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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Real user data aggregated to summarize the product performance and customer experience.
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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
80 Satisfaction of Cost Relative to Value
2
Since last award
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
Pre-Packaged AI/ML Services
Feature Engineering
Explainability
Model Monitoring and Management
Data Exploration and Visualization
Data Ingestion
Model Tuning
Openness and Flexibility
Data Labeling
Algorithm Diversity
Vendor Capability Ratings
Quality of Features
Ease of Customization
Ease of Implementation
Ease of Data Integration
Business Value Created
Ease of IT Administration
Breadth of Features
Availability and Quality of Training
Vendor Support
Product Strategy and Rate of Improvement
Usability and Intuitiveness
Google Cloud Vertex AI Reviews
Folarin T.
- Role: Sales Marketing
- Industry: Communications
- Involvement: IT Development, Integration, and Administration
Submitted Sep 2025
Cutting-edge AI platform with powerful features
Likeliness to Recommend
What differentiates Google Cloud Vertex AI from other similar products?
Vertex AI differentiates itself by being a research-driven, AI-native platform with unified AutoML + custom workflows, managed Kubeflow pipelines, and direct access to Google’s cutting-edge foundation models, all tightly integrated with BigQuery and Google’s data stack.
What is your favorite aspect of this product?
its seamless blend of AutoML and custom model development in one platform
What do you dislike most about this product?
its complexity and steep learning curve.
What recommendations would you give to someone considering this product?
Vertex AI is best for organizations that want to be on the cutting edge of AI/GenAI and are ready to handle some complexity.
Pros
- Over Delivered
- Friendly Negotiation
- Helps Innovate
- Continually Improving Product
Cons
- Less Fair
John Olayemi D.
- Role: Information Technology
- Industry: Construction
- Involvement: IT Leader or Manager
Submitted Aug 2025
Wonderful products with great features
Likeliness to Recommend
What differentiates Google Cloud Vertex AI from other similar products?
Vertex AI stands out because it unifies data preparation, training, deployment, and monitoring in a single managed environment. Its tight integration with other Google Cloud services makes scaling easier, and the pay-as-you-go model is attractive compared to platforms that require heavy upfront setup.
What is your favorite aspect of this product?
My favourite aspect is the simplicity of deploying models into production. Vertex AI makes it possible to go from training to serving with just a few steps, while also offering built-in monitoring and version control.
What do you dislike most about this product?
The main drawback is the cost, which can escalate quickly for large-scale training jobs. The learning curve for new users is also steep, and the documentation could be clearer with more practical examples.
What recommendations would you give to someone considering this product?
Start small with a proof of concept to understand usage costs before scaling up. Make use of Google’s tutorials and community resources to shorten the learning curve. Vertex AI is best suited for teams that already use Google Cloud, so ensure alignment with your existing infrastructure.
Pros
- Continually Improving Product
- Inspires Innovation
- Helps Innovate
- Reliable
Anuruddh S.
- Role: Information Technology
- Industry: Engineering
- Involvement: End User of Application
Submitted Sep 2025
Exploring the efficiency of google vertex ai
Likeliness to Recommend
What differentiates Google Cloud Vertex AI from other similar products?
It give a interactive environment and ease of use make it different from another application
What is your favorite aspect of this product?
It unifies the entire machine learning workflow from training to deployment
What do you dislike most about this product?
Some addon thing is too costlier
What recommendations would you give to someone considering this product?
Its ability to scale with user demands, and stability.
Pros
- Helps Innovate
- Continually Improving Product
- Reliable
- Performance Enhancing
