{"id":29702,"date":"2026-07-29T15:44:52","date_gmt":"2026-07-29T12:44:52","guid":{"rendered":"https:\/\/www.intellectsoft.net\/blog\/?p=29702"},"modified":"2026-07-29T15:52:24","modified_gmt":"2026-07-29T12:52:24","slug":"microsoft-foundry-ai-agents","status":"publish","type":"post","link":"https:\/\/www.intellectsoft.net\/blog\/microsoft-foundry-ai-agents\/","title":{"rendered":"Take Repetitive Work Off Your Team&#8217;s Plate with Microsoft Foundry AI Agents\u00a0"},"content":{"rendered":"<p><span style=\"font-weight: 400;\">Microsoft Foundry is Microsoft&#8217;s platform for enterprise <\/span><a href=\"https:\/\/www.intellectsoft.net\/ai\/ai-agent-development\"><span style=\"font-weight: 400;\">AI agent development.<\/span><\/a><span style=\"font-weight: 400;\"> You can think of it as Microsoft&#8217;s equivalent of AWS Bedrock, integrated into the Azure ecosystem.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">In this article, we&#8217;ll look at how we use Microsoft Foundry to solve real client problems. The goal here is to build a common bridge between business and delivery teams. In fact, both sides should speak the same language to deliver brilliant AI solutions to our clients.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">We&#8217;ll answer several practical questions:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">What is Microsoft Foundry?<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">What business problems does it solve?<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">How do you explain its value to a client?<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">What are its main components?<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">How do you start building production-ready AI agents with Microsoft Foundry?<\/span><\/li>\n<\/ul>\n<h2><span style=\"font-weight: 400;\">AI Agents in 2026: Why They Matter for Enterprise Success<\/span><\/h2>\n<p><span style=\"font-weight: 400;\">Over the last few years, enterprise AI has changed out of all recognition. And of course, we need to understand what is behind this evolution. The reason is pretty simple: it sheds light on why AI agents have become so trendy today.<\/span><\/p>\n<h2><span style=\"font-weight: 400;\">2023-2024: user asks \u2013 AI answers<\/span><\/h2>\n<p><span style=\"font-weight: 400;\">A few years ago, most companies started their AI journey with chat interfaces. The first question clients usually asked was:<\/span><\/p>\n<p><i><span style=\"font-weight: 400;\">&#8220;Can we add something like ChatGPT to our product or internal system?&#8221;<\/span><\/i><\/p>\n<p><span style=\"font-weight: 400;\">As a result, AI assistants appeared everywhere. Companies added chat widgets to websites, customer portals, employee tools, and mobile applications. Sometimes these assistants delivered value. Quite often, they didn&#8217;t.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">In most cases, these solutions were just wrappers around ChatGPT. In fact, assistants could answer questions that users asked. But they didn&#8217;t understand the business and couldn&#8217;t perform any real work. And it was logical, as assistants couldn&#8217;t access company systems and knowledge bases.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">We had the same in our own projects.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">One of our clients operates a <\/span><a href=\"https:\/\/www.intellectsoft.net\/cases\/video-content-search-engine-and-aggregator\"><span style=\"font-weight: 400;\">video streaming platform. <\/span><\/a><span style=\"font-weight: 400;\">They wanted to integrate an AI assistant that could recommend movies. That\u2019s why our <\/span><a href=\"https:\/\/www.intellectsoft.net\/blog\/hire-dedicated-ai-development-team\/\"><span style=\"font-weight: 400;\">AI dedicated development team<\/span><\/a><span style=\"font-weight: 400;\"> built a chatbot that relied on user requests and provided structured recommendations in JSON format. The assistant was intentionally limited: it only answered movie-related questions and ignored everything else.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">At the time, this was a useful feature. Looking back, it was a relatively simple implementation compared to what enterprise AI can do today.<\/span><\/p>\n<h3><span style=\"font-weight: 400;\">2025-2026: user asks \u2013 AI reasons \u2013 AI uses data and tools \u2013 AI completes tasks<\/span><\/h3>\n<p><span style=\"font-weight: 400;\">The market has moved far beyond generic chatbots. Companies no longer want AI that answers questions based only on the knowledge of a language model. They want AI that understands their business.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">The first step in this evolution was retrieval-based assistants. Instead of generating answers from general knowledge, AI started using company-specific information\u2014policies, internal documentation, knowledge bases, product catalogs, and other enterprise data. We&#8217;ve built many of these solutions ourselves.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Today, the next level we&#8217;re all taking is AI agents. We are shifting from chatbots that generate answers to AI agents that analyze, find the information they need, decide which tools to use, interact with business systems, and complete tasks.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">For example, your client asks:<\/span><\/p>\n<p><i><span style=\"font-weight: 400;\">&#8220;Where is my order?&#8221;<\/span><\/i><\/p>\n<p><span style=\"font-weight: 400;\">A traditional chatbot might answer using standardized text.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">An AI agent takes the next step. It checks the order management system, retrieves the current status, explains the reason for a delay, and, if necessary, creates a support ticket or starts another business workflow \u2013 all without human intervention.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">This is the key difference between the AI assistants we built two years ago and the enterprise agents we&#8217;re building today.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">For our clients, agents are vital because they automate both interactions and work. They cut repetitive operational tasks, connect multiple systems, and allow employees to focus on more strategic duties.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">That business outcome is not the technology itself. This is what we should focus on when discussing AI agents with clients.<\/span><\/p>\n<h2><span style=\"font-weight: 400;\">What Is an Enterprise AI Agent?<\/span><\/h2>\n<p><span style=\"font-weight: 400;\">As a rule, people associate AI with Claude, GPT, Sonnet, or other LLMs. But an enterprise AI agent is much more than a model.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">The LLM model is only one component of a large system. In fact, a working AI agent consists of multiple layers that work together. They understand requests, access business knowledge, interact with enterprise systems, and complete real tasks.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">A typical enterprise comprises the following components:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>User request<\/b><span style=\"font-weight: 400;\"> \u2013 the task or question received from a user<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Agent instructions<\/b><span style=\"font-weight: 400;\"> \u2013 rules that define the agent&#8217;s role, behavior, and limitations<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>LLM reasoning<\/b><span style=\"font-weight: 400;\"> \u2013 the language model analyzes the request and plans the next steps<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Knowledge retrieval<\/b><span style=\"font-weight: 400;\"> \u2013 the agent searches company documents, policies, <\/span><a href=\"https:\/\/www.intellectsoft.net\/blog\/ai-product-catalogs\/\"><span style=\"font-weight: 400;\">AI product catalogs, <\/span><\/a><span style=\"font-weight: 400;\">or historical data to remain in context\u00a0<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Tool and API calls<\/b><span style=\"font-weight: 400;\"> \u2013 the agent connects databases, CRM, ERP, or other services to retrieve information or perform actions<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Evaluation<\/b><span style=\"font-weight: 400;\"> \u2013 the system checks whether the response is accurate and whether the agent used the right tools correctly<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Monitoring<\/b><span style=\"font-weight: 400;\"> \u2013 logs, token usage, latency, errors, and production behavior are tracked to keep the system stable<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Answer or business action<\/b><span style=\"font-weight: 400;\"> \u2013 the agent responds to the user or completes the requested business process<\/span><\/li>\n<\/ul>\n<h3><span style=\"font-weight: 400;\">LLM as a piece of the puzzle<\/span><\/h3>\n<p><span style=\"font-weight: 400;\">The language model comprehends the request, reasons about it, and generates text. All these help make the agent useful in a business environment.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Instructions tell the agent how it should behave and what tasks it can perform. Plus, they guide what an AI agent should avoid and when to clarify instead of making assumptions.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">The knowledge layer gives the agent business context: internal documentation, company policies, product catalogs, knowledge bases, or historical records. So see, it doesn\u2019t rely on its training data.\u00a0<\/span><\/p>\n<h3><span style=\"font-weight: 400;\">Instruments turn an assistant into an agent<\/span><\/h3>\n<p><span style=\"font-weight: 400;\">The biggest gap between a chatbot and an AI agent is the ability to act in different scenarios.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">An assistant can explain something. An agent can do something. Instruments make this possible.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">An instrument can access and search a database and find customer information. Plus, it can update a CRM record, restart a service, and create a support ticket. All this is possible through APIs or the<\/span><a href=\"https:\/\/www.intellectsoft.net\/blog\/model-context-protocol\/\"><span style=\"font-weight: 400;\"> Model Context Protocol (MCP).<\/span><\/a><\/p>\n<p><span style=\"font-weight: 400;\">Without instruments, AI can only generate text. With tools, it becomes part of your business operations.<\/span><\/p>\n<h3><span style=\"font-weight: 400;\">Evaluation and monitoring matter<\/span><\/h3>\n<h3><span style=\"font-weight: 400;\">Production AI also needs agent quality control to be sure that it generates accurate results.\u00a0<\/span><\/h3>\n<p><b>Evaluation<\/b><span style=\"font-weight: 400;\"> helps us test whether the agent works correctly and whether it picks the right instrument for each task.<\/span><\/p>\n<p><b>Monitoring<\/b><span style=\"font-weight: 400;\"> reveals what happens after deployment. We can track token consumption, latency, API failures, tool execution, costs, and overall agent behavior in production.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Without evaluation and monitoring, an enterprise AI agent quickly becomes difficult to trust and maintain.<\/span><\/p>\n<h3><span style=\"font-weight: 400;\">Enterprise AI is an engineering system<\/span><\/h3>\n<p><span style=\"font-weight: 400;\">One misconception we often hear is:<\/span><\/p>\n<p><span style=\"font-weight: 400;\">&#8220;We just need to write a good prompt.&#8221;<\/span><\/p>\n<p><span style=\"font-weight: 400;\">In reality, a prompt is only a small part of the solution.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">A production-grade AI agent is a complex engineering system that combines many things \u2013 prompts, knowledge retrieval, tools, evaluation, monitoring, security, and governance. All of these components work together to deliver the desired business outcomes.<\/span><\/p>\n<h2><span style=\"font-weight: 400;\">Where Microsoft Foundry Fits In<\/span><\/h2>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-29704 size-full\" src=\"https:\/\/www.intellectsoft.net\/blog\/wp-content\/uploads\/img-1-12.png\" alt=\"Where Microsoft Foundry Fits In \" width=\"1800\" height=\"1176\" srcset=\"https:\/\/www.intellectsoft.net\/blog\/wp-content\/uploads\/img-1-12.png 1800w, https:\/\/www.intellectsoft.net\/blog\/wp-content\/uploads\/img-1-12-300x196.png 300w, https:\/\/www.intellectsoft.net\/blog\/wp-content\/uploads\/img-1-12-1024x669.png 1024w, https:\/\/www.intellectsoft.net\/blog\/wp-content\/uploads\/img-1-12-768x502.png 768w, https:\/\/www.intellectsoft.net\/blog\/wp-content\/uploads\/img-1-12-1536x1004.png 1536w, https:\/\/www.intellectsoft.net\/blog\/wp-content\/uploads\/img-1-12-600x392.png 600w, https:\/\/www.intellectsoft.net\/blog\/wp-content\/uploads\/img-1-12-450x294.png 450w, https:\/\/www.intellectsoft.net\/blog\/wp-content\/uploads\/img-1-12-1000x653.png 1000w\" sizes=\"auto, (max-width: 1800px) 100vw, 1800px\" \/><\/p>\n<h3><span style=\"font-weight: 400;\">The rise of AI agent platforms<\/span><\/h3>\n<p><span style=\"font-weight: 400;\">Microsoft understands that companies want to build AI agents, and they&#8217;re right. We can compare the AI agent market to the California Gold Rush. Back then, people used pickaxes to mine for gold. Today, companies rely on platforms and frameworks to build AI agents.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Today, every major cloud provider has its own platform. Amazon has Bedrock, Google \u2013 Vertex AI, and Microsoft \u2013 Foundry.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">The demand for enterprise AI is booming. So it\u2019s logical that top players offer tools that help businesses build AI apps faster.\u00a0<\/span><\/p>\n<h3><span style=\"font-weight: 400;\">A single workspace for building AI<\/span><\/h3>\n<p><span style=\"font-weight: 400;\">Microsoft Foundry is the platform where you can build, deploy, govern, and scale AI apps and AI agents.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Foundry portal looks like a playground where developers, architects, data engineers, and business teams can work together to create AI solutions.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Inside Foundry, you can:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Experiment with different AI models<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Build AI agents<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Deploy AI applications<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Configure evaluations<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Monitor performance<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Govern <\/span><a href=\"https:\/\/www.intellectsoft.net\/ai\"><span style=\"font-weight: 400;\">AI solutions <\/span><\/a><span style=\"font-weight: 400;\">throughout their lifecycle<\/span><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">A good analogy is Tony Stark&#8217;s workshop. That&#8217;s where he built JARVIS, designed new suits, tested new technologies, and had all the tools he needed in one environment. Microsoft Microsoft agent framework plays a similar role. It&#8217;s a single workspace where you can build, test, deploy, and manage enterprise AI without switching between tools.<\/span><\/p>\n<h3><span style=\"font-weight: 400;\">From business problems to AI solutions<\/span><\/h3>\n<p><span style=\"font-weight: 400;\">AI development starts with a business process, such as customer support, sales, HR, finance, and operations.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">In these areas, companies spend much time on repetitive manual work. They search for data and need to jump between systems to complete a simple request. AI agents can fix this.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">The next layer is the AI use case. Depending on the business need, this can include:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">AI assistants<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">AI agents<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Workflow automation<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Enterprise knowledge search<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><a href=\"https:\/\/www.intellectsoft.net\/blog\/stop-building-dashboards-start-building-decisions-ai-copilots-for-business-analytics\/\"><span style=\"font-weight: 400;\">AI Copilots for business analytics<\/span><\/a><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Operational agents<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Document retrieval assistants<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">AI plugins for SaaS products<\/span><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">Microsoft Foundry is the platform layer that helps us build these AI solutions and connect a business problem with the right AI implementation.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">At the center is <\/span><b>Microsoft Foundry<\/b><span style=\"font-weight: 400;\">. It brings together everything needed to build enterprise AI platform:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">AI agents<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Foundation models<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Tools and integrations<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Evaluation<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Monitoring<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Governance<\/span><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">Foundry sits between business problems and the client&#8217;s technology stack. It doesn&#8217;t replace existing systems or require companies to rebuild them. Instead, it extends them by adding an intelligent AI layer on top.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Below Foundry are the client&#8217;s existing systems \u2013 APIs, databases, SharePoint, CRM, ERP, ticketing systems, file storage, and other enterprise apps.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Foundry connects all these systems, so AI agents can find information, complete business tasks, and automate workflows in a secure and governed way.<\/span><\/p>\n<h2><span style=\"font-weight: 400;\">Microsoft Foundry vs Competitors<\/span><\/h2>\n<p><span style=\"font-weight: 400;\">As we mentioned above, Microsoft is not the only player in the market. There are several big vendors that offer their own platforms for building AI agents and assistants.<\/span><\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-29705 size-full\" src=\"https:\/\/www.intellectsoft.net\/blog\/wp-content\/uploads\/Table-1-6.png\" alt=\"Microsoft Foundry vs Competitors \" width=\"1800\" height=\"960\" srcset=\"https:\/\/www.intellectsoft.net\/blog\/wp-content\/uploads\/Table-1-6.png 1800w, https:\/\/www.intellectsoft.net\/blog\/wp-content\/uploads\/Table-1-6-300x160.png 300w, https:\/\/www.intellectsoft.net\/blog\/wp-content\/uploads\/Table-1-6-1024x546.png 1024w, https:\/\/www.intellectsoft.net\/blog\/wp-content\/uploads\/Table-1-6-768x410.png 768w, https:\/\/www.intellectsoft.net\/blog\/wp-content\/uploads\/Table-1-6-1536x819.png 1536w, https:\/\/www.intellectsoft.net\/blog\/wp-content\/uploads\/Table-1-6-600x320.png 600w, https:\/\/www.intellectsoft.net\/blog\/wp-content\/uploads\/Table-1-6-450x240.png 450w, https:\/\/www.intellectsoft.net\/blog\/wp-content\/uploads\/Table-1-6-1000x533.png 1000w\" sizes=\"auto, (max-width: 1800px) 100vw, 1800px\" \/><\/p>\n<h3><span style=\"font-weight: 400;\">Microsoft Foundry\u00a0<\/span><\/h3>\n<p><span style=\"font-weight: 400;\">As a rule, we opt for <\/span><b>Microsoft Foundry<\/b><span style=\"font-weight: 400;\"> when our clients already use Microsoft technologies \u2013 Azure, Microsoft 365, Microsoft Entra ID, SharePoint, SQL Server, Microsoft Teams, and Microsoft Dynamics.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Plus, if your infrastructure already runs on Microsoft, it will be easy to integrate it with Foundry. Microsoft has made it as simple as possible for its products to work together, which significantly reduces the effort required to build and deploy enterprise AI solutions.<\/span><\/p>\n<h3><span style=\"font-weight: 400;\">AWS Bedrock and Google Vertex AI<\/span><\/h3>\n<p><span style=\"font-weight: 400;\">When we talk about <\/span><b>AWS Bedrock<\/b><span style=\"font-weight: 400;\"> and <\/span><b>Google Vertex AI<\/b><span style=\"font-weight: 400;\">, the logic is the same. If a client already uses the AWS or Google ecosystem, it usually makes sense to consider their platforms first. They integrate naturally with the services the company already has, making development and operations much simpler.<\/span><\/p>\n<h3><span style=\"font-weight: 400;\">OpenAI<\/span><\/h3>\n<p><span style=\"font-weight: 400;\">When it comes to <\/span><b>OpenAI<\/b><span style=\"font-weight: 400;\">, the story is a bit different. It\u2019s great for swift prototyping. If you need to build something quickly and understand whether AI can solve a particular business problem, OpenAI is often the fastest option but expensive. You can create a prototype in a few days instead of a few weeks.\u00a0<\/span><\/p>\n<h3><span style=\"font-weight: 400;\">LangChain and LangGraph<\/span><\/h3>\n<p><span style=\"font-weight: 400;\">LangChain and LangGraph are also very popular today. We usually recommend them when there is a strong and mature engineering team. They are more complex than managed platforms, but they provide an almost unlimited level of customization if you need custom agents.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">As you can see, we can\u2019t name one provider who is the best. Your ecosystem, business needs, budget, timeline, and customization influence your choice.\u00a0<\/span><\/p>\n<h2><span style=\"font-weight: 400;\">What Client Problems Can Foundry Solve?\u00a0<\/span><\/h2>\n<p><span style=\"font-weight: 400;\">As we already mentioned, Microsoft Foundry works great when a company has repetitive operations \u2013 searching, checking, summarizing, copying, validating, or preparing information. These tasks consume a lot of the team&#8217;s time and don&#8217;t require strategic actions.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">For example, an HR team may reply to questions on policies daily and feel irritated by routine duties. Won&#8217;t it be a good idea to trust this task to an AI agent? You can train it on your data so that it can respond automatically. Your HR team is pleased and has more time for other tasks. This is especially common for mid-sized and enterprise companies.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Another example is a support team. They often classify tickets, search for information, answer repetitive questions, or respond to internal users. AI assistants can handle these tasks, so your team can focus on more complex customer issues.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">The main thing is to start with the business problem, and only after picking the technology.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">We don&#8217;t begin by asking:<\/span><\/p>\n<p><span style=\"font-weight: 400;\">&#8220;Do you need an AI agent?&#8221;<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Instead, we ask questions like:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">What business process takes the most time?<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Which tasks are repetitive?<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Where do your employees spend hours searching for information?<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Which processes involve switching between multiple systems?<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">What work would you like to automate first?<\/span><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">When we\u2019re aware of business problems and needs, we can decide whether an AI agent is the right solution.<\/span><\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-29706 size-full\" src=\"https:\/\/www.intellectsoft.net\/blog\/wp-content\/uploads\/Table-2-9.png\" alt=\"What business problems AI agents solve\" width=\"1800\" height=\"1110\" srcset=\"https:\/\/www.intellectsoft.net\/blog\/wp-content\/uploads\/Table-2-9.png 1800w, https:\/\/www.intellectsoft.net\/blog\/wp-content\/uploads\/Table-2-9-300x185.png 300w, https:\/\/www.intellectsoft.net\/blog\/wp-content\/uploads\/Table-2-9-1024x631.png 1024w, https:\/\/www.intellectsoft.net\/blog\/wp-content\/uploads\/Table-2-9-768x474.png 768w, https:\/\/www.intellectsoft.net\/blog\/wp-content\/uploads\/Table-2-9-1536x947.png 1536w, https:\/\/www.intellectsoft.net\/blog\/wp-content\/uploads\/Table-2-9-600x370.png 600w, https:\/\/www.intellectsoft.net\/blog\/wp-content\/uploads\/Table-2-9-450x278.png 450w, https:\/\/www.intellectsoft.net\/blog\/wp-content\/uploads\/Table-2-9-1000x617.png 1000w\" sizes=\"auto, (max-width: 1800px) 100vw, 1800px\" \/><\/p>\n<h2><span style=\"font-weight: 400;\">Final Thoughts<\/span><\/h2>\n<p><span style=\"font-weight: 400;\">Microsoft Foundry is more than another AI platform. It provides everything needed to build, deploy, govern, and scale enterprise AI agents in one environment.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">But technology itself is only part of the equation because the main focus is on business processes. An AI agent is the instrument used to boost your productivity and automate repetitive tasks.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">No matter what you want to build: an internal HR assistant, customer support agent, or any other solution \u2013\u00a0 Microsoft Foundry offers the engineering platform to turn your idea into a working product.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">At Intellectsoft, we start with your business operations to identify gaps that AI agents can address and make you more productive. <\/span><a href=\"https:\/\/www.intellectsoft.net\/contacts\"><span style=\"font-weight: 400;\">Contact us<\/span><\/a><span style=\"font-weight: 400;\"> if you need consultation on building AI agents with Microsoft Foundry.\u00a0\u00a0<\/span><\/p>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Microsoft Foundry is Microsoft&#8217;s platform for enterprise AI agent development. You can think of it as Microsoft&#8217;s equivalent of AWS Bedrock, integrated into the Azure&#8230;<\/p>\n","protected":false},"author":91,"featured_media":29707,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[798],"tags":[],"class_list":["post-29702","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-artificial-intelligence"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v23.8 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Building Microsoft Foundry AI Agents | Intellectsoft<\/title>\n<meta name=\"description\" content=\"Explore how Intellectsoft builds AI agents with Microsoft Foundry to cut repetitive operational work and improve productivity.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" 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