Try our new research platform with insights from 80,000+ expert users

Azure AI Foundry vs Google Vertex AI 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

Azure AI Foundry
Ranking in AI Development Platforms
7th
Ranking in AI-Agent Builders
3rd
Average Rating
8.0
Reviews Sentiment
5.7
Number of Reviews
16
Ranking in other categories
Low-Code Development Platforms (10th), Integration Platform as a Service (iPaaS) (11th)
Google Vertex AI
Ranking in AI Development Platforms
3rd
Ranking in AI-Agent Builders
5th
Average Rating
8.2
Reviews Sentiment
6.4
Number of Reviews
14
Ranking in other categories
No ranking in other categories
 

Featured Reviews

Sudhakar Pyndi - PeerSpot reviewer
Data, Analytics & Ai Senior Director, Enterprise Architecture at a comms service provider with 10,001+ employees
Document processing has accelerated contract reviews and enabled rapid development of AI-driven supply chain solutions
With regard to security, compliance, or governance features in Azure AI Foundry, this is something that we have started looking into, primarily using Microsoft Purview for our governance, data governance. There is this new module called DSPM for AI, and we are exploring it while trying to operationalize it with different policies and so forth, but we're still not where we want to be on the governance, AI governance side. It's a process and a path, and we are trying to work through that right now. Azure AI Foundry can be improved from the governance perspective, as a lot can be done. The promising part is the recent announcement on the Foundry control plane. A couple of days back, there was an announcement regarding it bringing in some of the gaps that were on the platform, so it's a really positive direction in terms of where it's going. More governance is what is lacking, but the control plane will really play a big role there.
Hamada Farag - PeerSpot reviewer
Technology Consultant at Beta Information Technology
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.

Quotes from Members

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

Pros

"Azure AI Foundry makes it very straightforward, as I do not have to write thousands of lines of code; I rely on GitHub Copilot and Azure AI Foundry."
"Azure AI Foundry has helped reduce the time taken for AI app and agent development cycles by approximately 50% for one use case."
"Azure AI Foundry has affected our management of privacy, performance, and compliance primarily based on our location in the UK, where it is more focused on the region in terms of where that data is being processed and who has access to it, which is hopefully no one other than us."
"The features of Azure AI Foundry that I appreciate the most include the containment of all the agents and the ability to see all agents in a single dashboard and to have access to all of them from one portal."
"These features have benefited our organization by allowing us to release new products and new offerings this year, accelerate our growth, and quickly drive our AI agents into customers' hands."
"The most beneficial feature of Azure AI Foundry for enhancing customer experience is the ability to use Azure Functions to call things outside of Azure AI Foundry, making it more comprehensive as a feature."
"In my evaluation process, I found that Microsoft Azure AI Foundry is much more accessible compared to AWS on model selection and the capabilities of using Document Intelligence versus Textract were much better."
"What I appreciate most about Azure AI Foundry is that for a single agent flow, the platform provides the ability to build agents quickly, which demonstrates the ease of use for a single agent workflow."
"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."
"The best feature of Google Vertex AI is the ease of use, along with the integration with the rest of the Google ecosystem and the way models can be made available outside Google through endpoints."
"Google Vertex AI is better for deployment, configuration, delivery, licensing, and integration compared to other AI platforms."
"Vertex comes with inbuilt integration with GCP for data storage."
"The most useful function of Google Vertex AI for me is the ease of integration, as we can easily create a prompt and integrate it into our current system."
"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."
"The integration of AutoML features streamlines our machine-learning workflows."
"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."
 

Cons

"I would appreciate it if Microsoft could improve Azure AI Foundry by releasing new features immediately because sometimes we have to wait for weeks or months to use them."
"My experience with deploying Azure AI Foundry is that, at this point in time, given the limited capabilities available in Foundry, we built pro-code agents, hosted them, containerized them, and deployed them."
"Even though I have only been utilizing Azure AI Foundry for the past four months, I think the understanding between Copilot Studio and Azure AI Foundry is still somewhat unclear regarding which one to use when and why, and how they complement each other is a journey we are currently undertaking."
"I would improve Azure AI Foundry by adding more functions within Foundry itself, as right now it is quite basic in what it does."
"One of the big things Azure AI Foundry could improve is continuously evolving the governance elements and how, while I know they exist, the more control we can have over different elements and observation of what different agents are doing, the better."
"My experience with Azure AI Foundry's pricing, setup cost, and licensing was a mess."
"Right now, because of the UI and the complexity of it, it is complicated and cumbersome, and I think figuring out how to simplify that would probably make it a faster process."
"In Azure AI Foundry, I did not see many tools inside to test it that can really help us. I wish there were more tooling."
"It takes a considerable amount of time to process, and I understand the technology behind why it takes this long, but this is something that could be reduced."
"Both major systems, Azure and Google, are not yet stabilized, especially their customer support."
"Google can improve Google Vertex AI in terms of analysis and accuracy. When passing a very large context, instead of receiving vague responses, it would be better if the system could prompt users not to pass overly large prompts and provide clearer guidance on how to fine-tune Gemini for specific use cases."
"It is not completely mature and needs some features and functions. The interface needs to be more user-friendly."
"Google Vertex AI is good in machine learning and AI, but it lacks optimization."
"It would be beneficial to have certain features included in the future, such as image generators and text-to-speech solutions."
"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."
"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."
 

Pricing and Cost Advice

Information not available
"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."
"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 price structure is very clear"
"The solution's pricing is moderate."
report
Use our free recommendation engine to learn which AI Development Platforms solutions are best for your needs.
881,733 professionals have used our research since 2012.
 

Top Industries

By visitors reading reviews
Financial Services Firm
19%
Outsourcing Company
14%
Manufacturing Company
13%
Retailer
13%
Computer Software Company
12%
Financial Services Firm
9%
Manufacturing Company
8%
Educational Organization
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business2
Midsize Enterprise2
Large Enterprise13
By reviewers
Company SizeCount
Small Business5
Midsize Enterprise3
Large Enterprise7
 

Questions from the Community

What is your experience regarding pricing and costs for Azure AI Foundry?
I would need to ask my technical team about my experience with the pricing, setup costs, and licensing.
What needs improvement with Azure AI Foundry?
The platform's effect on my management of privacy, performance, and compliance across different regions is quite complex because Azure AI Foundry does not make it very clear how to deploy. We set u...
What is your primary use case for Azure AI Foundry?
My main use cases for Azure AI Foundry include deploying AI applications to perform document comparison, translation services, and a chat feature, helping the digital AI team at our company. Curren...
What is your experience regarding pricing and costs for Google Vertex AI?
I purchased Google Vertex AI directly from Google, as we are a partner of Google. I would rate the pricing for Google Vertex AI as low; the price is affordable.
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 primary use case for Google Vertex AI?
We are developing AI models and agents using Google Vertex AI platform, and we are deploying them using Google Vertex AI platform on Google Cloud Platform, GCP. With just one single platform, Googl...
 

Overview

Find out what your peers are saying about Azure AI Foundry vs. Google Vertex AI and other solutions. Updated: December 2025.
881,733 professionals have used our research since 2012.