Vertex AI Reviews & Product Details

The best thing I like is that Vertex AI is a place where I can perform all my machine-learning tasks in one place. I can build, train, and deploy all my models without switching any other tools. It is super comfortable to use, saves time, and keeps my workflow smooth.

The most helpful one is I can even train and deploy complex models and it works very well with BigQuery which lets me automate the model process and make predictions. Vertex AI is super flexible to perform AutoML and custom training. Review collected by and hosted on G2.com.

I personally feel that documentation is helpful but it can feel very lengthy for beginners and for some jobs like creating pipelines requires more setup with strong GCP experience and and technical knowledge. Vertex AI has so many tools and takes time to understand how everything relates and fits together. Review collected by and hosted on G2.com.

Google Cloud stands "tall" & proximity for the cutting-edge strong innovation enterprise integration with various services in Artificial Intelligence & Machine Learning intricacies, & data analytics capabilities with the services spanning across BigQuery, Cloud Functions, Google Kubernetes Engine, Google Workspace & Firebase etc.

There are enormous features - ease of use & implementation, user-friendly interface, & frequency of use is high due to the versatility of the platform in handling sophisticated workload, orchestration, data analysis, serverless computing, & customer support centric oriented with high-level documentation. Review collected by and hosted on G2.com.

Google Cloud could benefit from enhanced compatibility with legacy systems & non-Google applications, particularly by simplifying the process of custom configurations.

As a leading force in the cloud space, Google Cloud demonstrates innovative growth, a strong customer-centric approach, & a consistently reliable suite of products. Review collected by and hosted on G2.com.

What i really like about google cloud is how well it integrates with other google services, If you're already in google ecosystem for example using gmail, google workspace or bigquery. I used google cloud services daily and everything feels just seamless. The UI is clean and i expecially enjoy the speed and reliability of services like compute engine and cloud storage. Pricing is also very competetive. Even non technical person can use most of the services by google cloud, and for developer its very easy to integrate with. Review collected by and hosted on G2.com.

So the only thing i dislike about google cloud is its invoicing and the billing dashboard its very overwhelming. There are times when i could not identify the charges as the services for being i am charged is not clearly mentioned. Review collected by and hosted on G2.com.

I like best about Vertex AI is how it brings the entire machine learning workflow into one unified platform.From data processing and model training to evaluation and deployment.The AutoML feature is especially helpful for quickly building high performace models with minimal coding.Intigration with Bigquery and other GCP services makes data handling seamless. Review collected by and hosted on G2.com.

While vertex AI is powerful ,there are few things that could be better,the pricing can add up quickly if you are not careful with the resources you use,especially with large-scale training jobs.The UI is clean but sometimes navigating between different components like datasets,models,endpoint feels clunky.Some parts of the documentation felt a bit too technical. Review collected by and hosted on G2.com.

The best thing about Vertex AI is the ease in operating the tools available for Model building and implementation with a thorough approach to the task. The framework is user friendly and lets me as a user get the most out of my efforts with very few steps for integration to achieve my goals and requirements from Vertex AI. Review collected by and hosted on G2.com.

As a new user it was a bit challenging to get acquainted with the platform. It comes with a steep learning curve. Support for custom containers and performance issues can feel a bit delayed. Review collected by and hosted on G2.com.

Google Cloud is one of the most reliable cloud hosting provider, I have been using it for the past 2 years and so far I did not face any issues. Mostly I use Google Cloud Virtual Machine with Static IP, they charge for the ingress and egress charges through that IP Address, the configuration I choose for the VM comes under always free tier and I don't have to may anything for the VM. Review collected by and hosted on G2.com.

They don't have any dedicated technical support which I feel is a must for a cloud hosting provider Review collected by and hosted on G2.com.

What I like best about Vertex AI is how it brings everything—data preparation, model training, hyperparameter tuning, and deployment—into one unified platform. It cuts down on the complexity of managing different tools and frameworks. Plus, the AutoML and pre-built models make it super easy to get started, even without writing tons of code. The integration with BigQuery and other Google Cloud services is smooth, which really helps streamline the whole workflow. Review collected by and hosted on G2.com.

While Vertex AI is powerful, the pricing can be a bit opaque—especially for newcomers or smaller teams. Some features like AutoML or managed pipelines can quickly rack up costs if you’re not careful. Also, there’s a learning curve with navigating the interface and understanding how all the components connect, especially if you’re new to the Google Cloud ecosystem. Review collected by and hosted on G2.com.

The best part about Vertex AI is its compatibility with other services of GCP, like Data sources, VPN, BigQuery, Deployment. It makes the agent very compact and secure.

Also, Vertex AI has a no-code platform which makes it easier for non-tech professionals to develop or supervise agents on their own. Review collected by and hosted on G2.com.

In order to utilize Vertex AI, there is a certain level of technical expertise that is required, to develop agents. It makes it difficult for non-tech professionals to develop all the nitty-gritties of developing an agent. With having alternatives which seem more as a no-code agent builder, Vertex AI could go behind on the race. Review collected by and hosted on G2.com.

I’ve had the opportunity to use Google’s Vertex AI platform for several months now, and it has been a solid tool in my data science workflow. Overall, it provides an impressive suite of features that cater to both beginner and experienced data scientists alike.

Strengths:

Unified Interface: Vertex AI simplifies the often-complex task of managing machine learning workflows. The unified interface is intuitive, making it easy to integrate different stages of the machine learning pipeline, from data preprocessing to model training and deployment. The integration with Google Cloud is seamless, which is a huge plus for teams already using the cloud ecosystem. Review collected by and hosted on G2.com.

NA dislike about Vertex AI as of now it is working great Review collected by and hosted on G2.com.

Google Cloud offers a wide range of solutions for technology development and deployment, including Computing, Networking, data Storage and management, AI and machine learning, all in one integrated platform. GCP has user-friendly learning tutorials and reliable community support, which makes it easy to solve whatever challenges might come up. Review collected by and hosted on G2.com.

The user interface can appear complex to newcomers, as it lacks customization options for the left navigation menu. The inability to remove services not used by users can make the interface unnecessarily crowded. Review collected by and hosted on G2.com.