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Vertex AI Reviews & Product Details

AA
Consultant
Enterprise(> 1000 emp.)
Validated Reviewer
Review source: G2 invite
Incentivized Review
(Original )Information
What do you like best about Vertex AI?

It eases the process of training and deploying machine learning models that can be used for various use cases. In addition, all of their services are well documented and easily available. Review collected by and hosted on G2.com.

What do you dislike about Vertex AI?

It would have been better if the prices had been a little lower. Review collected by and hosted on G2.com.

What problems is Vertex AI solving and how is that benefiting you?

Great visualization features helped us efficiently display our findings to the client, and training the ml model was easier. In addition, CI CD integration helped a lot in the production environment. Review collected by and hosted on G2.com.

Vertex AI Overview

What is Vertex AI?

Build, deploy, and scale machine learning (ML) models faster, with fully managed ML tools for any use case. Through Vertex AI Workbench, Vertex AI is natively integrated with BigQuery, Dataproc, and Spark. You can use BigQuery ML to create and execute machine learning models in BigQuery using standard SQL queries on existing business intelligence tools and spreadsheets, or you can export datasets from BigQuery directly into Vertex AI Workbench and run your models from there. Use Vertex Data Labeling to generate highly accurate labels for your data collection.

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Vertex AI Details
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Product Description

Vertex AI is a managed machine learning (ML) platform that helps you build, train, and deploy ML models faster and easier. It includes a unified UI for the entire ML workflow, as well as a variety of tools and services to help you with every step of the process. Vertex AI Workbench is a cloud-based IDE that is included with Vertex AI. It makes it easy to develop and debug ML code. It provides a variety of features to help you with your ML workflow, such as code completion, linting, and debugging. Vertex AI and Vertex AI Workbench are a powerful combination that can help you accelerate your ML development. With Vertex AI, you can focus on building and training your models, while Vertex AI Workbench takes care of the rest. This frees you up to be more productive and creative, and it helps you get your models into production faster. If you're looking for a powerful and easy-to-use ML platform, then Vertex AI is a great option. With Vertex AI, you can build, train, and deploy ML models faster and easier than ever before.

How do you position yourself against your competitors?

Vertex AI is a unified platform that provides a wide range of tools and services to help you build, train, and deploy machine learning models faster and easier. It is a managed platform that takes care of the underlying infrastructure, so you can focus on building and training your models. It is also a scalable platform that can easily scale up or down your ML workloads as needed.


Seller Details
Seller
Google
Company Website
Year Founded
1998
HQ Location
Mountain View, CA
Twitter
@google
32,679,523 Twitter followers
LinkedIn® Page
www.linkedin.com
301,875 employees on LinkedIn®
Ownership
NASDAQ:GOOG
Phone
+1 (650) 253-0000
Total Revenue (USD mm)
$182,527
Description

Organize the world’s information and make it universally accessible and useful.


RJ
Overview Provided by:

Vertex AI Integrations

(4)
Verified by Vertex AI

Recent Vertex AI Reviews

Verified User
T
Verified UserSmall-Business (50 or fewer emp.)
4.0 out of 5
"Easy and efficient AI Platform"
I just had a chance to test it out, so the best part that I like until now is the variety of models that I can choose to test out my agent
MS
Mohamed S.Small-Business (50 or fewer emp.)
4.0 out of 5
"Vertex Review"
As I published my frontend app link using vertex and it was free, also for machine learning
AH
Abir H.Enterprise (> 1000 emp.)
5.0 out of 5
"Interesting"
As an computer science student I find it very interesting how AI is used in data science to function the process in data in real time.

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534 out of 535 Total Reviews for Vertex AI

4.3 out of 5
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534 out of 535 Total Reviews for Vertex AI
4.3 out of 5
534 out of 535 Total Reviews for Vertex AI
4.3 out of 5

Vertex AI Pros and Cons

How are these determined?Information
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Pros
Cons

Overall Review Sentiment for Vertex AIQuestion

Time to Implement
<1 day
>12 months
Return on Investment
<6 months
48+ months
Ease of Setup
0 (Difficult)
10 (Easy)
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AA
BI Developer.
Information Technology and Services
Mid-Market(51-1000 emp.)
More Options
Validated Reviewer
Verified Current User
Review source: Organic
(Original )Information
What do you like best about Google Cloud?

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.

What do you dislike about Google Cloud?

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.

What problems is Google Cloud solving and how is that benefiting you?

Google Cloud helps enhance our business intelligence solutions development capabilities. We use BigQuery's data warehousing service to explore, process, and analyze large datasets, uncovering patterns and insights. Google Dataflow allows us to handle growing data volumes for data preparation and pipeline automation. My team collaborates on Vertex AI to develop and integrate predictive models for forecasting and generative AI capabilities within our solutions. Overall, the Google Cloud Platform helps my team develop and deploy data-intensive solutions by providing robust technology infrastructure to manage and analyze large datasets quickly, allowing us to focus more on core tasks. Review collected by and hosted on G2.com.

YC
Product Engineer
Information Technology and Services
Small-Business(50 or fewer emp.)
Validated Reviewer
Verified Current User
Review source: G2 invite
Incentivized Review
What do you like best about Vertex AI?

Vertex AI by google is a very helpful service of the Google Cloud it helps you test AI models before you use them in your product. It have all the latest AI models, Open Source and paid both. You can generate Images, translate large audio files and deploy AI models quickly in a server. It saves ton of times when you want to build a service very quickly. I am using this from past 2 years and i saw big improment. It have a greate customer support as well which resolves your queries in no time. Review collected by and hosted on G2.com.

What do you dislike about Vertex AI?

The only problem that i see in vertex is that there are times we get errors while using AI models like gemini, errors are not user friendly. So here is a scope of improvement. Review collected by and hosted on G2.com.

What problems is Vertex AI solving and how is that benefiting you?

Vertex AI helping me test all the latest AI models and so i can choose the test. It lets me construct system prompts for AI model tasks in the portal it self, and the best thing is i can completely test it on vertex ai itself. Its fairely cheap as well when you compare it to others. Review collected by and hosted on G2.com.

PS
GitHub Org. Member @Kubernetes &amp; @Kubernetes-sigs
Small-Business(50 or fewer emp.)
More Options
Validated Reviewer
Verified Current User
Review source: G2 invite
Incentivized Review
Products used within Google Cloud: Google App Engine, Google Kubernetes Engine (GKE), Vertex AI
What do you like best about Google Cloud?

I like the simplicity and ease of use from a UI standpoint. From the main dashboard, we can easily trigger a VM to become a full-fledged Kubernetes cluster on GKE, which isn’t the case with other providers. Another feature I appreciate is the “Solutions” sidebar, which provides a great overview of available services for different purposes—even for users who might not be familiar with them.

From a CLI perspective, I like the RBAC functionality. Another strong point is its support for a variety of integrations. Additionally, customer support is excellent, especially when dealing with technical or billing-related issues. Review collected by and hosted on G2.com.

What do you dislike about Google Cloud?

Nothing. One thing I would love to see is an option to automatically provision an external load balancer when configuring an ingress controller like NGINX in Kubernetes. Review collected by and hosted on G2.com.

What problems is Google Cloud solving and how is that benefiting you?

The cloud provider space has always been complicated, but I see Google Cloud solving this in many ways—making their UI and dashboards simple and making jobs much easier.

On the open-source side, Google Cloud and Google are doing a great job promoting open-source software and making their products fit well into the CNCF ecosystem. Review collected by and hosted on G2.com.

MK
Co-Founder
Small-Business(50 or fewer emp.)
More Options
Validated Reviewer
Verified Current User
Review source: Organic
Business partner of the seller or seller's competitor, not included in G2 scores.
What do you like best about Google Cloud?

The best thing was to use google cloud run and to test it for real time task - that is using faas approach - testing the deep learning seq2seq model for classification task of the video frame in real time. Gcloud run offer multiple parameters like public and private URL to test the app internally ( in the gcloud Ip addresses) or externally ( making the app available for the public), scalability, CPU boost to boost the request from the clients and scalability using minimum and maximum number of instances. And I got results in real time for 20 clients efficiently, accurately and quickly.

Also google offered my project with the grant of 25K$ so I can use the services for free and experiment them. Review collected by and hosted on G2.com.

What do you dislike about Google Cloud?

Although I'm able to get real time results which I expected - but there I faced cold start problem - even though I set the minimum instances set to 1; but after remaining idle for above 1 to 2 hours - when there is the request of the user to the server - the model started to load and thus - the gcloud run app/link couldn't give results faster and even sometimes give no results.

Secondly, I faced Domain Sharing issue here, even though I have admin acces of my account but I solved after doing experimenting multiple things - there was no proper documentation on how to give access to the user inside the account other users. Review collected by and hosted on G2.com.

What problems is Google Cloud solving and how is that benefiting you?

I works for my company HEC computer vision project granted to me on my university ID- that is to experiment the deep learning Model for event detection system on cloud using FAAS approach to compute the results in the real time without maintaining state on the server, making my 1 of the aspect: Stateless Seq2Seq DL model. It is serving me public and private Ip's both to tes the application in real time that is classification of the video frames and checking whether it is fulfulling my 3 metrics which are robustness, scalable and accurate. Review collected by and hosted on G2.com.

JM
Senior Associate Consultant
Mid-Market(51-1000 emp.)
Validated Reviewer
Verified Current User
Review source: Organic
What do you like best about Vertex AI?

Vertex AI is one shot solution for MLOps and LLMOps needs, VertexAI is easy to use as it has very simple interface and also the APIs are quite easy to which makes the Kubeflow workflow good ansuper easy. vertex ai provides end to end solution for any MLOps pipeline. It's easy to implement as the library GCPC has very well docuemntation along with examples. Integrating vertex ai or to trigger pipeline from VS code is easy. The google support is excellent interms of service Review collected by and hosted on G2.com.

What do you dislike about Vertex AI?

The documentation and also the VS code integration inside the User managed notebook is one big flaw, apart from that everyting is very good Review collected by and hosted on G2.com.

What problems is Vertex AI solving and how is that benefiting you?

Vertex AI is solving problem by Making easy MLOps and LLMOps platform where production level ml workflows process is very good, accurate and easy to implement and understand and there by saving resources for the company and team Review collected by and hosted on G2.com.

PG
DATA ENGINEER
Small-Business(50 or fewer emp.)
Validated Reviewer
Review source: G2 invite
Incentivized Review
What do you like best about Vertex AI?

Auto ML feature. The Auto ML feature is the best thing in this and it reduces your work and you to work efficiently also the Auto Edge and Custom reduce a lot of burden

Using Vertex AI there is Ease of Implementation in this. You can integrate this easily with others or outside of Google with the import feature Review collected by and hosted on G2.com.

What do you dislike about Vertex AI?

Hyperparameters aren't that useful for everyone Review collected by and hosted on G2.com.

What problems is Vertex AI solving and how is that benefiting you?

The problem that Vertex Ai is solving is the Ease if Use and Ease of Implementation You don't need that much high level of Engineers or coders to understand the platform.The vertex Ai is so easy to use and adapt that anyone can get their hands easily. Review collected by and hosted on G2.com.

NS
iOS Developer
Small-Business(50 or fewer emp.)
Validated Reviewer
Review source: Organic
What do you like best about Vertex AI?

my daily works in company is about analytics and data science and for core analysis i have to implement machine learning and statistical models to get correct predictive analysis by doing analysis all of this is very hectic then vertex ai come likes a best buddy and true companion in implimenting machine learning models Review collected by and hosted on G2.com.

What do you dislike about Vertex AI?

sometimes while implimenting model becomes black box so you are not able to debug it easily that what would be the possible thats the only problem i have encountered so far Review collected by and hosted on G2.com.

What problems is Vertex AI solving and how is that benefiting you?

implementing machine learning becomes so handy and easy after vertex ai now i am thinking to go with it completly Review collected by and hosted on G2.com.

PS
Cloud Engineer
Information Technology and Services
Mid-Market(51-1000 emp.)
Validated Reviewer
Verified Current User
Review source: G2 invite
Incentivized Review
(Original )Information
What do you like best about Vertex AI?

My overall experience has been great as it makes me very comfortable while using it because its UI is very much user friendly and easy to use. It made us seamlessly deploy data science models in our automations.Vertex Ai by Google offers & very flexible to use, create and deploy all ml models very easily. you dont need to be experienced in coding which makes me make it use frequently with ease in implementation and can be integrated easily with our solutions. Review collected by and hosted on G2.com.

What do you dislike about Vertex AI?

Since its not for small or medium cap companis, the team need the good documentation and videos to start with the tool. Though pricing is other concern, t is often challenging to predict and manage costs effectively, especially as I scale the machine learning projects. I find that the customer support for Vertex AI, including forums and online communities, is not as extensive as some other machine learning platforms. Review collected by and hosted on G2.com.

What problems is Vertex AI solving and how is that benefiting you?

It is Simplifying my Model Development & takes care of End-to-End ML Lifecycle Management

Earlier i was facing difficulty in integrating search feature in my projects but now i have integrated Search in Applications using Vertex AI Agent Builder and developed an demo search result of that application which shows movies result in the screenshot Review collected by and hosted on G2.com.

Verified User in Information Technology and Services
TI
Small-Business(50 or fewer emp.)
Validated Reviewer
Verified Current User
Review source: G2 invite
Incentivized Review
What do you like best about Vertex AI?

I just had a chance to test it out, so the best part that I like until now is the variety of models that I can choose to test out my agent Review collected by and hosted on G2.com.

What do you dislike about Vertex AI?

Can't think of any thing that make me dislike Vertex Review collected by and hosted on G2.com.

What problems is Vertex AI solving and how is that benefiting you?

I used Vertex to test out my agent solutions, which I found pretty easy and fast to build up the test product without thinking about connecting with different model api in the backend, and I can easy change the model to test which one is more suitable for requested tasks Review collected by and hosted on G2.com.

AA
Assistant Manager Data Analytics
Enterprise(> 1000 emp.)
Validated Reviewer
Verified Current User
Review source: G2 invite
Incentivized Review
What do you like best about Vertex AI?

Vertex AI will provide you the autoML feature where you will get various machine learning pre-trained models you just have to train them on your dataset and you are ready to go for predictions or classification. Review collected by and hosted on G2.com.

What do you dislike about Vertex AI?

Computing power is very less. It is taking soooo much time to run little complex scripts but the same scripts you can run in Big Query very fast. Review collected by and hosted on G2.com.

What problems is Vertex AI solving and how is that benefiting you?

It'll help you with pre-trained ML models to perform your prediction or classification tasks.

You can even schedule your python notebooks in Vertex AI as per your requirements. Review collected by and hosted on G2.com.