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Google Vertex AI pros and cons

Vendor: Google
4.1 out of 5
Badge Leader

Pros & Cons summary

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Prominent pros & cons

PROS

Vertex AI eliminates the need for extensive coding with its multiple libraries and low-code/no-code services, providing flexibility for agents to build use cases.
The platform offers a comprehensive monitoring feature, ensuring a thorough understanding of model performance and results.
Vertex AI integrates seamlessly with Google Cloud's AI Prediction service for real-time predictions and streaming within existing workflows.
The inclusion of AutoML features streamlines machine-learning workflows and simplifies the integration with existing systems.
Vertex AI provides a unified platform, negating the need to switch between multiple tools and platforms, facilitating seamless integration with existing workflows, systems, tools, and databases.

CONS

Google Vertex AI would benefit from including features such as image generators and text-to-speech solutions.
Vertex AI's training time could be improved as it is perceived to be slow, especially with large data.
Using Vertex AI requires substantial domain knowledge and technical understanding, making it challenging for less technically oriented users.
Vertex AI documentation is lacking and is not readily available or easy to understand.
Improvements in analysis and accuracy are needed for Google Vertex AI, particularly when handling very large contexts.
 

Google Vertex AI Pros review quotes

Serge Dahdouh - PeerSpot reviewer
CEO at Les Roches International School of Hotel Management
Aug 16, 2023
Vertex AI possesses multiple libraries, so it eliminates the need for extensive coding.
Ivy W. - PeerSpot reviewer
Senior Data Scientist at Breuninger
Aug 31, 2023
The monitoring feature is a true life-saver for data scientists. I give it a ten out of ten.
Srikar Kumar - PeerSpot reviewer
Founder & CEO at JUMPSTARTNINJA TECHNOLOGIES LLP
Nov 9, 2023
It provides the most valuable external analytics.
Learn what your peers think about Google Vertex AI. Get advice and tips from experienced pros sharing their opinions. Updated: January 2026.
881,082 professionals have used our research since 2012.
Suresh Ayyavoo - PeerSpot reviewer
Chief Information Officer (CIO) at a tech services company with 51-200 employees
Nov 24, 2023
Google Vertex AI is an out-of-the-box and very easy-to-use solution.
TuPhan - PeerSpot reviewer
Data Engineer at a tech consulting company with 201-500 employees
Nov 28, 2023
We extensively utilize Google Cloud's Vertex AI platform for our machine learning workflows. Specifically, we leverage the IO branch for EDA data in Suresh Live Virtual, employing Forte IT for training machine learning models. The AI model registry in Vertex AI is crucial for cataloging and managing various versions of the models we develop. When it comes to deploying models, we rely on Google Cloud's AI Prediction service, seamlessly integrating it into our workflow for real-time predictions or streaming. For monitoring and tracking the outcomes of model development, we employ Vertex AI Monitoring, ensuring a comprehensive understanding of the model's performance and results. This integrated approach within Vertex AI provides a unified platform for managing, deploying, and monitoring machine learning models efficiently.
Kartik Singh - PeerSpot reviewer
Data Scientist at Tradeindia.com-Infocom Network Ltd
Jul 19, 2024
The most valuable feature we've found is the model garden, which allows us to deploy and use various models through the provided endpoints easily.
reviewer1285629 - PeerSpot reviewer
Solution Architect at a tech vendor with 10,001+ employees
Aug 1, 2024
The most valuable features of the solution are that it is quite flexible, and some of the services are almost low-code, with no-code services, so it gives agents flexibility to build the use cases according to the operational needs.
Rajeev-Dave - PeerSpot reviewer
IT Senior Manager at a tech services company with 10,001+ employees
Sep 13, 2024
The integration of AutoML features streamlines our machine-learning workflows.
Kashif Yaseen - PeerSpot reviewer
Trainee Decision Scientist at a tech services company with 1,001-5,000 employees
Nov 11, 2024
Vertex comes with inbuilt integration with GCP for data storage.
Hamada Farag - PeerSpot reviewer
Technology Consultant at Beta Information Technology
Jun 23, 2025
Google Vertex AI is better for deployment, configuration, delivery, licensing, and integration compared to other AI platforms.
 

Google Vertex AI Cons review quotes

Serge Dahdouh - PeerSpot reviewer
CEO at Les Roches International School of Hotel Management
Aug 16, 2023
It would be beneficial to have certain features included in the future, such as image generators and text-to-speech solutions.
Ivy W. - PeerSpot reviewer
Senior Data Scientist at Breuninger
Aug 31, 2023
The solution is stable, but it is quite slow. Maybe my data is too large, but I think that Google could improve Vertex AI's training time.
Srikar Kumar - PeerSpot reviewer
Founder & CEO at JUMPSTARTNINJA TECHNOLOGIES LLP
Nov 9, 2023
I've noticed that using chat activity often presents a broader range of options and insights for a well-constructed question. Improving the knowledge base could be a key aspect for enhancement—expanding the information sources to enhance the generation process.
Learn what your peers think about Google Vertex AI. Get advice and tips from experienced pros sharing their opinions. Updated: January 2026.
881,082 professionals have used our research since 2012.
Suresh Ayyavoo - PeerSpot reviewer
Chief Information Officer (CIO) at a tech services company with 51-200 employees
Nov 24, 2023
Google Vertex AI is good in machine learning and AI, but it lacks optimization.
TuPhan - PeerSpot reviewer
Data Engineer at a tech consulting company with 201-500 employees
Nov 28, 2023
I believe that Vertex AI is a robust platform, but its effectiveness depends significantly on the domain knowledge of the developer using it. While Vertex AI does offer support through the console UI in the Google Cloud environment, it is better suited for technical members who have a deeper understanding of machine learning concepts. The platform may be challenging for business process developers (BPDUs) who lack extensive technical knowledge, as it involves intricate customization and handling numerous parameters. Effectively utilizing Vertex AI requires not only familiarity with machine learning frameworks like TensorFlow or PyTorch but also a proficiency in Python programming. The complexity of these requirements might pose challenges for less technically oriented users, making it crucial to have a solid foundation in both machine learning principles and Python coding to extract the full value from Vertex AI. It would be beneficial to have a streamlined process where we can leverage the capabilities of Vertex AI directly through the BigQuery UI. This could involve functionalities such as creating machine learning models within the BigQuery UI, providing a more user-friendly and integrated experience. This would allow users to access and analyze data from BigQuery while simultaneously utilizing Vertex AI to build machine learning models, fostering a more cohesive and efficient workflow.
Kartik Singh - PeerSpot reviewer
Data Scientist at Tradeindia.com-Infocom Network Ltd
Jul 19, 2024
The tool's documentation is not good. It is hard.
reviewer1285629 - PeerSpot reviewer
Solution Architect at a tech vendor with 10,001+ employees
Aug 1, 2024
I think the technical documentation is not readily available in the tool.
Rajeev-Dave - PeerSpot reviewer
IT Senior Manager at a tech services company with 10,001+ employees
Sep 13, 2024
Both major systems, Azure and Google, are not yet stabilized, especially their customer support.
Kashif Yaseen - PeerSpot reviewer
Trainee Decision Scientist at a tech services company with 1,001-5,000 employees
Nov 11, 2024
I'm not sure if I have suggestions for improvement.
Hamada Farag - PeerSpot reviewer
Technology Consultant at Beta Information Technology
Jun 23, 2025
It is not completely mature and needs some features and functions. The interface needs to be more user-friendly.