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Google Vertex AI vs Prem Studio comparison

 

Comparison Buyer's Guide

Executive Summary

Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Categories and Ranking

Google Vertex AI
Ranking in AI Development Platforms
2nd
Average Rating
8.2
Reviews Sentiment
6.4
Number of Reviews
14
Ranking in other categories
AI-Agent Builders (4th)
Prem Studio
Ranking in AI Development Platforms
16th
Average Rating
10.0
Reviews Sentiment
1.0
Number of Reviews
2
Ranking in other categories
No ranking in other categories
 

Featured Reviews

Hamada Farag - PeerSpot reviewer
Customization and integration empower diverse AI applications
We are familiar with most Google Cloud services, particularly infrastructure services, storage, compute, AI tools, containerization, GCP containerization, and cloud SQL. We are familiar with approximately eighty percent of Google's services, primarily related to infrastructure, AI, containers, backup, storage, and compute. We are familiar with Gemini AI and Google Vertex AI, and we have completed some exercises and cases with our customers for Google AI. We use automation in machine learning. I work with a team where everyone has specific responsibilities. We have design and development processes in place. Based on my experience, I would rate Google Vertex AI a 9 out of 10.
reviewer2760291 - PeerSpot reviewer
Has accelerated AI solution development through automated evaluation and fine-tuning
Prem Studio allowed me to easily automate and solve the complicated problem of exploring and identifying the best AI architecture for our problems. Prem Studio has a straightforward yet powerful approach to evaluate disparate AI architectures on our business problems and to accurately fine-tune the most promising ones. This significantly reduced time-to-market, almost by a factor of ten in my case, for solutions tailored and optimized for customer requirements and KPIs.

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Pros

"The support is perfect and fantastic."
"The monitoring feature is a true life-saver for data scientists. I give it a ten out of ten."
"The integration of AutoML features streamlines our machine-learning workflows."
"Google Vertex AI is an out-of-the-box and very easy-to-use solution."
"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."
"Vertex comes with inbuilt integration with GCP for data storage."
"With just one single platform, Google Vertex AI platform, we can achieve everything; we need not switch over to multiple tools, multiple platforms, as everything can be accomplished through this one single platform for integration with existing workflows, systems, tools, and databases."
"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."
"The dataset management feature and the managed finetuning are the most valuable because they save the most time."
 

Cons

"The tool's documentation is not good. It is hard."
"Both major systems, Azure and Google, are not yet stabilized, especially their customer support."
"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."
"It is not completely mature and needs some features and functions. The interface needs to be more user-friendly."
"I think the technical documentation is not readily available in the tool."
"I'm not sure if I have suggestions for improvement."
"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."
"It is not completely mature and needs some features and functions. The interface needs to be more user-friendly."
"The inference should be faster."
 

Pricing and Cost Advice

"I think almost every tool offers a decent discount. In terms of credits or other stuff, every cloud provider provides a good number of incentives to onboard new clients."
"The solution's pricing is moderate."
"The Versa AI offers attractive pricing. With this pricing structure, I can leverage various opportunities to bring value to my business. It's a positive aspect worth considering."
"The price structure is very clear"
Information not available
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Top Industries

By visitors reading reviews
Computer Software Company
14%
Financial Services Firm
10%
Manufacturing Company
9%
Educational Organization
7%
No data available
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business5
Midsize Enterprise3
Large Enterprise7
No data available
 

Questions from the Community

What do you like most about Google Vertex AI?
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 trai...
What is your experience regarding pricing and costs for Google Vertex AI?
They have different pricing models like pay-as-you-go or subscription model, and total cost of ownership. It is comparatively cheaper than Azure.
What needs improvement with Google Vertex AI?
We used AutoML feature for developing AI models automatically, but we are not comfortable with the performance of those models. We have to do some fine-tuning, hyperparameter optimization, and othe...
What is your experience regarding pricing and costs for Prem Studio?
To maximize the effectiveness of fine-tuning, I would suggest using the parallelism features of the platform. This allows fine-tuning and evaluating multiple models at the same time, making compari...
What needs improvement with Prem Studio?
Prem Studio is perfect for text input and output. We requested support for vLM, which should be available soon.
What is your primary use case for Prem Studio?
I use Prem Studio to automate fine-tuning and evaluation of AI solutions.
 

Overview

Information not available
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