I cannot share any data points or examples; that would need to be my technical team. The advice I would give to another organization considering using Azure AI Foundry is that the faster they get to it, the better they are going to have ROI on the product. I would rate my overall experience with Azure AI Foundry as an eight.
Data, Analytics & Ai Senior Director, Enterprise Architecture at a comms service provider with 10,001+ employees
Real User
Top 10
Nov 20, 2025
My advice for other companies that are considering Azure AI Foundry is that developers would love it because it's a well-connected ecosystem from data to AI, using all the services within Azure Foundry. The developers would love it, and from the administration perspective, if you're a Microsoft shop, it makes perfect sense to go into that ecosystem. I gave this review an overall rating of 8.
Azure Cloud Architect at a manufacturing company with 10,001+ employees
Real User
Top 20
Nov 20, 2025
At this point in time, we do not even look at the observability features because we do not know what features are available, so we are just pinning it out to Application Insights and workspace analytics. The most useful security, compliance, and governance features have been limiting token limits. Azure AI Foundry's Entra ID to Azure AI Foundry integration needs to be a little more explicit, but that is helpful because a lot of times, my team was looking at a deployment and using an access key, which is not secure. I think it needs to be more intuitive regarding access key and token versus using Entra ID to fully secure the solution, and it is not straightforward. Regarding licensing, I did not really look at that piece. My advice to other organizations considering Azure AI Foundry would be to understand your use case, find the regions with the lowest latency, and comprehend the complete project, including security, access keys versus tokens, and the type of services being used. Additionally, knowing how to load balance and spin up multiple services to avoid creating bottlenecks and problems with latency for your customers is crucial. I would rate Azure AI Foundry at a seven overall.
Solution Architect II – Cloud Infrastructure Services (Microsoft Hyperscaler AI) at UST Global
Real User
Top 10
Nov 20, 2025
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. I can easily set the instructions and temperature without needing to write a lot of Python code. It does not take much time to develop these agents, particularly with Copilot Studio, which allows for quick building, and I appreciate how Azure AI Foundry and Copilot Studio complement each other, along with M365 Copilot and Security Copilot. There are many copilots and agent tools, which can be somewhat confusing due to their multitude. I utilize Azure AI Search frequently, especially with embedding models such as Ada. When dealing with unstructured documents that require processing or semantic search, I use Azure AI Search to bring that knowledge base in. Microsoft makes it straightforward, allowing me to avoid extensive coding for RAG, and the cost model is transparent, making the process much simpler than attempting to create these solutions independently, which is time-consuming and challenging. My primary use is within Azure AI Foundry, as I operate from a Microsoft business unit. I predominantly focus on Microsoft solutions, but I do appreciate that Microsoft offers Anthropic models, which are useful for coding tasks. I find that Gemini provides a larger context window, and if I wanted to use a Gemini model, I could do so through the agent-to-agent protocol. However, I primarily stick to the Microsoft stack due to my familiarity and organizational requirements, with minimal concern for alternatives such as Google or Amazon. I would rate this solution an 8.5 out of 10.
AI Practice Director at a consultancy with 201-500 employees
Real User
Top 20
Nov 20, 2025
The advice I would give to other organizations considering Azure AI Foundry is that it is a market leader and this is the best product that you could possibly deploy in the space between all the cloud providers. However, be aware that especially with capacity, it's essential to plan your production capacity at the beginning of your project, because it may take you months to get the capacity you need. Make sure you have a support plan that doesn't rely strictly on the customer support of Azure. I would rate my overall experience with Azure AI Foundry as an eight out of ten.
What I appreciate most about Azure AI Foundry is all of it, which is why I am using it. I have not seen benefits from the features of Azure AI Foundry yet because we have just started out on our journey, but I think they will significantly benefit us when we can get the use case right. I have not utilized Azure AI Foundry's predictive analytics feature. Azure AI Foundry has not improved decision-making in my organization yet, but I believe it will when we use it in production. Since I have been utilizing Azure AI Foundry for the past four months, my advice to another organization considering it is to pursue it; it would be unwise not to try it. I rated this review an eight out of ten.
Staff Software Developer at a tech vendor with 1,001-5,000 employees
Real User
Top 20
Nov 20, 2025
I do not utilize Azure Machine Learning yet, but it's something that I'm actively investigating. In deploying Azure AI Foundry, a lot of it is just learning AI development, which isn't necessarily something specific to Azure, and then consolidating on which service really fits our needs. That was where the challenges were, but otherwise, it's somewhat smooth. I would rate this product an 8.
Sr Director at a tech vendor with 10,001+ employees
Real User
Top 10
Nov 19, 2025
Azure AI Foundry has not improved the decision-making in my organization yet, as we have not evaluated that. I cannot provide examples of how these features have benefited my organization, as we are still evaluating and in the proof-of-concept phase, waiting for announcements at Ignite. These announcements include self-hosted containers for AI agents and natively available MCB server, which would make multi-agent orchestration and invoking tools and APIs easier. I have not utilized Azure AI Foundry's analytics feature. Once we deploy our production workload, if the scalability, speed, and performance are impressive, I will be sharing my experience with other customers. I am providing this review with an overall rating of eight out of ten.
Senior VP, AI, Innovation & Architecture at a computer software company with 501-1,000 employees
Real User
Top 10
Nov 19, 2025
Azure AI Foundry is a great platform to build commercial products on at scale. I would definitely recommend it for companies that have security and governance around the models and agents that they're putting together. I would rate Azure AI Foundry overall as a nine on a scale from one to ten, and I think there are some features that we saw at Ignite that would take it to a ten. Overall, I'm very happy and very pleased with the product.
Project Manager at a legal firm with 1,001-5,000 employees
Real User
Top 20
Nov 19, 2025
We are deploying AI applications in a cloud environment. A lot of this is obviously relevant to Azure AI Foundry, but we also look at other solutions that are SaaS-based products, which are obviously cloud products. In terms of Azure AI Foundry, we would be cloud. I believe we are utilizing Azure Machine Learning as a firm, but I do not think there is much that we are using there at present. I do not have any experience with machine learning that I can speak about. I could not confidently say which AI services we are utilizing or realizing the most impact from on a business level, to be honest. Anything I would say on that might be misleading. I think we are using Bing and RAG, but I am not one of the IT colleagues who would be able to tell you in terms of what that looks like and what impact they have had. I plan to use it in the future. I have very limited experience with it, and it is more conceptual rather than having actually put something out there in the wild. It is very much controlled, with only a couple of IT experts involved. I do not think we are using Azure AI Foundry Models for assessing various types of AI models so far. We are aware it exists; we have done some very brief testing on it, but nothing significant. I think for us, it is still this huge opportunity with Azure AI Foundry. We have not seen any direct value from it yet, but we have a huge bank of opportunities that we want to try to develop in Azure AI Foundry for, so I think that is as much as I can say on that. My experience with pricing, setup costs, and licensing of Azure AI Foundry is quite limited, so I do not know much about it. I have not been involved in the deployment of Azure AI Foundry as yet, but I hope to be involved at some stage. I would rate this review experience a nine out of ten.
Manager, Data Science at a outsourcing company with 10,001+ employees
Real User
Top 10
Nov 19, 2025
Azure AI Foundry scales effectively with our growing needs, serving our requirements successfully. We have expanded usage of Azure AI Foundry considerably. The process of expansion has been smooth, mostly just involving increased payment. I assess the stability and reliability of Azure AI Foundry as ten out of ten. My advice to another organization considering Azure AI Foundry is that Microsoft offers many AI models available that are very easy to use compared to any other cloud services. I would rate this product eight out of ten overall.
IT Manager at a manufacturing company with 1,001-5,000 employees
Real User
Top 10
Nov 19, 2025
My advice to another organization that's considering using Azure AI Foundry is don't be scared and don't be intimidated. It's new, and there is a lack of knowledge, but it helps you build itself. Once you start using it, you'll learn, and it's a trainable model, so you're basically training it and yourself to help develop what you need. I would rate this product an eight out of ten.
Senior Consultant - Data and AI Project Manager at Reply
Consultant
Top 10
Nov 18, 2025
We actually do not use much security functionality on Azure AI Foundry, so I think the question does not apply. My experimentation and differentiation efforts are affected by the fact that we mostly use OpenAI, so for our use case, we did not choose other partners such as Mistral, but it is valuable to have a comprehensive model catalog. My advice to other companies considering Azure AI Foundry is to use it for prototyping and to try it out now with the latest releases, as they integrated a comprehensive way for telemetry and integration with API management. Azure AI Foundry is growing, so I suggest giving it a try. I would rate this solution a 7.5 out of 10.
Advisory Specialist Master at a tech vendor with 10,001+ employees
Real User
Top 5
Nov 18, 2025
Azure AI Foundry's data visualization capabilities play a pretty basic role in optimizing my operations, as I would prefer to use a third-party tool such as Tableau that provides even more visuals. I have not utilized Azure AI Foundry's predictive analytics feature. Azure AI Foundry has improved decision-making in my company. I would describe the experience of the deployment of Azure AI Foundry as not challenging, but I think it is still in a growing phase and not enterprise-grade in terms of doing a lot of things. However, I need to understand how intuitive it is to configure and set up. My advice to other companies considering Azure AI Foundry is that it should be a foundation, and then you have to supplement it with something else. Start with the foundation, which is Azure AI Foundry, and then build on top of that, as Foundry is not the only solution. I would rate this review overall at 6.5 out of 10.
Senior Director, Data Orchestration Ai & Helix Practice Advisor at Connection
Real User
Top 10
Nov 18, 2025
RAG is relevant, and RAG grounding and RAG are important. We did check them, but again, right now we are not using any of that with the database or anything. The deployment process for Azure AI Foundry involves using CI/CD to deploy, so we have scripting with DevOps engineers. It is definitely easier to build versus deployment because then other teams are involved. Right now, because the model we are just using as an API, it is not that hard. We have a vault where we save the secrets for the keys and all. We then deploy it as a container app. That is the process that we went through. Compared to human effort, Azure AI Foundry is very fast. The security feature in Azure AI Foundry that has been useful is security. Because this is a separate tenant, we do have the normal Azure features trying to secure it, but we have not done much different. We always block the east to west and outward traffic. We always block, for example, to certain IP ranges and whitelist them. Sometimes we do the private links, so you have to get on the VPN to use Azure. That is usually the way of securing how we work with the cloud. The AI service I mostly use is not really any specific ones just yet. I have not used all of them. My overall rating for Azure AI Foundry is seven out of ten.
Assistant VP, Architecture (Engineering & Director at a financial services firm with 5,001-10,000 employees
Real User
Top 20
Nov 18, 2025
Azure AI Foundry has not improved decision-making in my company yet. My advice to other companies that are considering Azure AI Foundry is that if you are a full Microsoft shop, Azure AI Foundry is a no-brainer. However, I think it is good to keep your options open since it is a competitive space. I would rate this product seven out of ten overall.
Azure AI Foundry harnesses advanced AI technologies to streamline complex tasks across industries, offering cutting-edge solutions that enhance business processes and boost efficiency.
Azure AI Foundry integrates seamlessly into business environments, leveraging AI to transform traditional operations. It supports diverse applications by providing robust machine learning capabilities that drive innovation and enable intelligent automation. Designed to handle large-scale data analytics, it...
I cannot share any data points or examples; that would need to be my technical team. The advice I would give to another organization considering using Azure AI Foundry is that the faster they get to it, the better they are going to have ROI on the product. I would rate my overall experience with Azure AI Foundry as an eight.
My advice for other companies that are considering Azure AI Foundry is that developers would love it because it's a well-connected ecosystem from data to AI, using all the services within Azure Foundry. The developers would love it, and from the administration perspective, if you're a Microsoft shop, it makes perfect sense to go into that ecosystem. I gave this review an overall rating of 8.
At this point in time, we do not even look at the observability features because we do not know what features are available, so we are just pinning it out to Application Insights and workspace analytics. The most useful security, compliance, and governance features have been limiting token limits. Azure AI Foundry's Entra ID to Azure AI Foundry integration needs to be a little more explicit, but that is helpful because a lot of times, my team was looking at a deployment and using an access key, which is not secure. I think it needs to be more intuitive regarding access key and token versus using Entra ID to fully secure the solution, and it is not straightforward. Regarding licensing, I did not really look at that piece. My advice to other organizations considering Azure AI Foundry would be to understand your use case, find the regions with the lowest latency, and comprehend the complete project, including security, access keys versus tokens, and the type of services being used. Additionally, knowing how to load balance and spin up multiple services to avoid creating bottlenecks and problems with latency for your customers is crucial. I would rate Azure AI Foundry at a seven overall.
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. I can easily set the instructions and temperature without needing to write a lot of Python code. It does not take much time to develop these agents, particularly with Copilot Studio, which allows for quick building, and I appreciate how Azure AI Foundry and Copilot Studio complement each other, along with M365 Copilot and Security Copilot. There are many copilots and agent tools, which can be somewhat confusing due to their multitude. I utilize Azure AI Search frequently, especially with embedding models such as Ada. When dealing with unstructured documents that require processing or semantic search, I use Azure AI Search to bring that knowledge base in. Microsoft makes it straightforward, allowing me to avoid extensive coding for RAG, and the cost model is transparent, making the process much simpler than attempting to create these solutions independently, which is time-consuming and challenging. My primary use is within Azure AI Foundry, as I operate from a Microsoft business unit. I predominantly focus on Microsoft solutions, but I do appreciate that Microsoft offers Anthropic models, which are useful for coding tasks. I find that Gemini provides a larger context window, and if I wanted to use a Gemini model, I could do so through the agent-to-agent protocol. However, I primarily stick to the Microsoft stack due to my familiarity and organizational requirements, with minimal concern for alternatives such as Google or Amazon. I would rate this solution an 8.5 out of 10.
The advice I would give to other organizations considering Azure AI Foundry is that it is a market leader and this is the best product that you could possibly deploy in the space between all the cloud providers. However, be aware that especially with capacity, it's essential to plan your production capacity at the beginning of your project, because it may take you months to get the capacity you need. Make sure you have a support plan that doesn't rely strictly on the customer support of Azure. I would rate my overall experience with Azure AI Foundry as an eight out of ten.
What I appreciate most about Azure AI Foundry is all of it, which is why I am using it. I have not seen benefits from the features of Azure AI Foundry yet because we have just started out on our journey, but I think they will significantly benefit us when we can get the use case right. I have not utilized Azure AI Foundry's predictive analytics feature. Azure AI Foundry has not improved decision-making in my organization yet, but I believe it will when we use it in production. Since I have been utilizing Azure AI Foundry for the past four months, my advice to another organization considering it is to pursue it; it would be unwise not to try it. I rated this review an eight out of ten.
I do not utilize Azure Machine Learning yet, but it's something that I'm actively investigating. In deploying Azure AI Foundry, a lot of it is just learning AI development, which isn't necessarily something specific to Azure, and then consolidating on which service really fits our needs. That was where the challenges were, but otherwise, it's somewhat smooth. I would rate this product an 8.
Azure AI Foundry has not improved the decision-making in my organization yet, as we have not evaluated that. I cannot provide examples of how these features have benefited my organization, as we are still evaluating and in the proof-of-concept phase, waiting for announcements at Ignite. These announcements include self-hosted containers for AI agents and natively available MCB server, which would make multi-agent orchestration and invoking tools and APIs easier. I have not utilized Azure AI Foundry's analytics feature. Once we deploy our production workload, if the scalability, speed, and performance are impressive, I will be sharing my experience with other customers. I am providing this review with an overall rating of eight out of ten.
Azure AI Foundry is a great platform to build commercial products on at scale. I would definitely recommend it for companies that have security and governance around the models and agents that they're putting together. I would rate Azure AI Foundry overall as a nine on a scale from one to ten, and I think there are some features that we saw at Ignite that would take it to a ten. Overall, I'm very happy and very pleased with the product.
We are deploying AI applications in a cloud environment. A lot of this is obviously relevant to Azure AI Foundry, but we also look at other solutions that are SaaS-based products, which are obviously cloud products. In terms of Azure AI Foundry, we would be cloud. I believe we are utilizing Azure Machine Learning as a firm, but I do not think there is much that we are using there at present. I do not have any experience with machine learning that I can speak about. I could not confidently say which AI services we are utilizing or realizing the most impact from on a business level, to be honest. Anything I would say on that might be misleading. I think we are using Bing and RAG, but I am not one of the IT colleagues who would be able to tell you in terms of what that looks like and what impact they have had. I plan to use it in the future. I have very limited experience with it, and it is more conceptual rather than having actually put something out there in the wild. It is very much controlled, with only a couple of IT experts involved. I do not think we are using Azure AI Foundry Models for assessing various types of AI models so far. We are aware it exists; we have done some very brief testing on it, but nothing significant. I think for us, it is still this huge opportunity with Azure AI Foundry. We have not seen any direct value from it yet, but we have a huge bank of opportunities that we want to try to develop in Azure AI Foundry for, so I think that is as much as I can say on that. My experience with pricing, setup costs, and licensing of Azure AI Foundry is quite limited, so I do not know much about it. I have not been involved in the deployment of Azure AI Foundry as yet, but I hope to be involved at some stage. I would rate this review experience a nine out of ten.
Azure AI Foundry scales effectively with our growing needs, serving our requirements successfully. We have expanded usage of Azure AI Foundry considerably. The process of expansion has been smooth, mostly just involving increased payment. I assess the stability and reliability of Azure AI Foundry as ten out of ten. My advice to another organization considering Azure AI Foundry is that Microsoft offers many AI models available that are very easy to use compared to any other cloud services. I would rate this product eight out of ten overall.
My advice to another organization that's considering using Azure AI Foundry is don't be scared and don't be intimidated. It's new, and there is a lack of knowledge, but it helps you build itself. Once you start using it, you'll learn, and it's a trainable model, so you're basically training it and yourself to help develop what you need. I would rate this product an eight out of ten.
We actually do not use much security functionality on Azure AI Foundry, so I think the question does not apply. My experimentation and differentiation efforts are affected by the fact that we mostly use OpenAI, so for our use case, we did not choose other partners such as Mistral, but it is valuable to have a comprehensive model catalog. My advice to other companies considering Azure AI Foundry is to use it for prototyping and to try it out now with the latest releases, as they integrated a comprehensive way for telemetry and integration with API management. Azure AI Foundry is growing, so I suggest giving it a try. I would rate this solution a 7.5 out of 10.
Azure AI Foundry's data visualization capabilities play a pretty basic role in optimizing my operations, as I would prefer to use a third-party tool such as Tableau that provides even more visuals. I have not utilized Azure AI Foundry's predictive analytics feature. Azure AI Foundry has improved decision-making in my company. I would describe the experience of the deployment of Azure AI Foundry as not challenging, but I think it is still in a growing phase and not enterprise-grade in terms of doing a lot of things. However, I need to understand how intuitive it is to configure and set up. My advice to other companies considering Azure AI Foundry is that it should be a foundation, and then you have to supplement it with something else. Start with the foundation, which is Azure AI Foundry, and then build on top of that, as Foundry is not the only solution. I would rate this review overall at 6.5 out of 10.
RAG is relevant, and RAG grounding and RAG are important. We did check them, but again, right now we are not using any of that with the database or anything. The deployment process for Azure AI Foundry involves using CI/CD to deploy, so we have scripting with DevOps engineers. It is definitely easier to build versus deployment because then other teams are involved. Right now, because the model we are just using as an API, it is not that hard. We have a vault where we save the secrets for the keys and all. We then deploy it as a container app. That is the process that we went through. Compared to human effort, Azure AI Foundry is very fast. The security feature in Azure AI Foundry that has been useful is security. Because this is a separate tenant, we do have the normal Azure features trying to secure it, but we have not done much different. We always block the east to west and outward traffic. We always block, for example, to certain IP ranges and whitelist them. Sometimes we do the private links, so you have to get on the VPN to use Azure. That is usually the way of securing how we work with the cloud. The AI service I mostly use is not really any specific ones just yet. I have not used all of them. My overall rating for Azure AI Foundry is seven out of ten.
Azure AI Foundry has not improved decision-making in my company yet. My advice to other companies that are considering Azure AI Foundry is that if you are a full Microsoft shop, Azure AI Foundry is a no-brainer. However, I think it is good to keep your options open since it is a competitive space. I would rate this product seven out of ten overall.