Microsoft Foundry Reviews

My main use case involves building multi-agent workflows.

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.

I assess the integration of Azure AI Foundry with existing cloud services as quite effective. For example, we use Databricks for landing the data, so having communication established between the agent in Azure AI Foundry and a data agent in Databricks is valuable.

The Azure AI Foundry data visualization capabilities play a significant role in optimizing my operations by enhancing the Foundry UI experience for building multi-agent systems and orchestrating all of that, which would be beneficial going forward.

The most beneficial feature for enhancing the customer experience has not been utilized yet, as we have not deployed anything to production for our customer use. We are still in the proof-of-concept phase.

To improve Azure AI Foundry, I think the next release should mainly include self-hosted containers for AI agents and the ability to build multi-agent orchestration.

I have been using Azure AI Foundry for about six months.

I assess the stability and reliability of Azure AI Foundry as satisfactory. I have not experienced any downtime, crashes, or performance issues since our workload is not in production yet.

I am yet to evaluate how well Azure AI Foundry scales with the growing needs of my organization. In 2026 and beyond, we will be deploying a significant amount of agentic workload there, at which point we will have a better understanding.

On a scale from one being the worst and ten being the best, I would rate customer service and technical support as high. I am receiving full support due to our partnership with Microsoft and because we are in the evaluation phase.

Prior to adopting Azure AI Foundry, I was not using another solution to address similar needs.

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. The experience can improve based on the announcements they made at Ignite.

I did not face any challenges with deploying, as we handled everything. If we were to host our own agents, I did not see any challenges.

I will know if we have seen a return on investment with Azure AI Foundry after we launch our first use case to customers, which is projected for 2026.

In terms of pricing, I am still trying to understand and compare with other offerings to determine what is the most economical or the best value for the investment. At this point, I do not know if the pricing is competitive.

Before selecting Azure AI Foundry, I considered our existing partnership with Microsoft, which led us to choose Azure AI Foundry as our first option.

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.

I am developing AI agents using Azure cloud. I do not utilize Azure AI Search or RAG Bing grounding; I use AI agent.

Azure AI Foundry is flexible. Azure AI Foundry helped me reduce the time taken for AI app and agent development through the integrity and integration of various applications that we are able to achieve.

There is always scope for improvement regarding Azure AI Foundry, but I am still in exploring mode. The future updates of this service will offer features that come when you completely explore all the features, but since I am navigating and in exploring mode, I am not the right person to tell you what those improvements should be.

I have been working with Azure AI Foundry for the last three years.

On a scale from one to ten, I would rate the stability of Azure AI Foundry as eight.

Regarding scalability, I rate it as scalable; you can say it is eight to eight point five.

On a scale from one to ten, I would rate the support of Microsoft, particularly in supporting this service, as eight.

Before using Azure AI Foundry, I considered other solutions from different vendors like AWS and GCP.

The implementation time for Azure AI Foundry depends on the volume of data and the volume of applications, so it is not just a few minutes or one hour in total. Approximately, it is more than an hour.

I can do it all by myself without any help from the side.

I am overall satisfied with the licensing cost; that is fine.

I chose Azure instead of AWS or GCP because I had existing infrastructure servers, SQL servers, and other systems that can be easily integrated with Azure; that is the reason.

I faced quite easy challenges with the implementation of Azure AI Foundry. I am still exploring, so I am not the right person to tell you how the features of the product have benefited my organization, but I have noticed almost all connectivity, scalability, and volumes. I would rate this review an eight overall.

There is one product I'm interested in from Azure called Microsoft Foundry. I'm trying to focus on moving everything to Azure. Microsoft Foundry can be used for various tasks and problems, though I would describe it as a glorified search bar.

From my experience, there are features that stand out for me. The fact that it connects to ConnectWise is strong, and integration is the strongest part. Regarding capabilities and AI features, I have favorites in the Defender incidents, particularly from a security aspect, which is what I appreciate here.

I do see some disadvantages that could be improved. The document management side of it needs work. I'm not sure if it's the intelligence behind it, but you could get a little bit more from how it works with unstructured documents.

As for my personal experience, I would say around twenty-five.

I would rate the stability of Microsoft Foundry at a seven to eight on a scale of zero to ten where ten is the most stable. I don't give it a ten because it's very hard to get a ten with Microsoft these days, as Microsoft being Microsoft tends to have glitches or latency issues.

In relation to Microsoft Foundry, I wouldn't know if the solution is truly scalable based on my use case, though it does pretty much what is needed.

Regarding the technical service from Microsoft, I'd stick at a rating of seven on a scale of zero to ten. Generally, we have all our own internal resources that are probably more skilled than some of the Microsoft engineers.

I haven't really looked into others, to be honest. We're a Microsoft house and we live, breathe, and sell Microsoft. From an alternative standpoint, there is AWS with Bedrock, but I wouldn't be able to comment on it.

I wouldn't say you can track return on investment, and I don't think too many people do that. There's obviously value in it, otherwise we would have gotten rid of it a long time ago.

I'm not sure if it's the intelligence behind it, but you could get a little bit more from how it works with unstructured documents.

I have never purchased any services from AWS Marketplace, specifically in relation to Microsoft.

Microsoft Foundry does help with development, though I wouldn't be able to answer whether it reduces the time it takes for AI app and agent development cycles. Regarding value for money, there's obviously value in it, otherwise we would have gotten rid of it a long time ago.