Why create AI agents with Microsoft AI Foundry
The adoption of artificial intelligence in businesses has advanced significantly in recent years. More and more organizations are exploring how AI can help them improve efficiency, streamline processes, and support decision-making in their day-to-day operations. In this context, AI agents are gaining prominence as a natural evolution of generative AI: systems capable of interacting with people, accessing corporate knowledge, and carrying out tasks autonomously, always aligned with business processes.
However, as the use of AI-based solutions grows, new concerns are also emerging. Many companies have experimented with generic chatbots, but soon encounter significant limitations related to information security, lack of control over data, and difficulty integrating them into corporate environments. These risks mean that AI is not always viable in scenarios where confidentiality and compliance are critical.
In this landscape, tools such as Microsoft AI Foundry or aisQ AGENT offer a different approach to building enterprise AI agents, providing a foundation designed for professional environments where security, governance, and scalability are not optional, but fundamental requirements for moving from experimentation to real-world production use.
In which use cases does it make sense to create AI agents in the enterprise?
At LISDATA, we regularly work with companies that want to go beyond experimentation and build AI agents that truly work within their business environment. Our experience has shown us that these projects make sense when they start from concrete, everyday problems rather than from technology alone. That’s why most of the initiatives we support stem from real needs, such as quick access to internal knowledge, reduced operational workload, improved information analysis, or support for people in their daily work.
Across various projects, we have seen that AI agents deliver the most value when they are integrated into existing processes, respect security policies, and adapt to each organization’s context. This practical approach allows us to quickly identify which use cases are viable, which ones can scale, and which should be discarded, avoiding pilots that never reach production. Working on enterprise platforms such as Microsoft Azure AI Foundry or aisQ AGENT, and doing so alongside the teams involved, is key to turning AI agents into a useful tool that remains sustainable over time.
AI agents for querying corporate documentation
In many companies, key information is scattered across documents, manuals, regulations, or internal repositories that are difficult to make the most of. AI agents make it possible to centralize access to this corporate documentation and query it naturally, reducing search time and helping teams find reliable, up-to-date answers. This approach improves operational efficiency and ensures that access to information respects the organization’s permissions, roles, and security policies.
AI agents for analyzing tenders and contract awards
Analyzing tenders and contract awards usually involves large volumes of information and complex requirements. AI agents help process and summarize this documentation, identifying key points, relevant criteria, and potential risks more efficiently. This allows teams to reduce manual workload, improve the quality of analysis, and make more informed decisions in less time.
AI agents for generating meeting summaries
Meetings generate valuable information that can be lost if not properly structured. AI agents make it possible to generate clear summaries of the points discussed, agreements reached, and next steps, making it easier to follow up and coordinate between teams. This use case is especially useful in organizations with a heavy meeting schedule and a need for traceability in decision-making.
AI agents for querying internal policies and supporting HR
In areas such as Human Resources, AI agents provide an effective channel for resolving frequently asked questions about internal policies, procedures, and regulations. This improves the employee experience, reduces the volume of repetitive queries, and ensures that the information shared is consistent and aligned with the organization, freeing up HR team time for higher-value tasks.
AI agents for querying and analyzing logistics information
In logistics and operational environments, having clear, accessible information is key to daily operations. AI agents make it possible to query data on shipments, routes, rates, or operational status using natural language, integrating with existing systems. This improves visibility into operations, speeds up decision-making, and reduces technical dependencies in complex contexts.
How can I create AI agents for my company?
Creating AI agents for a company is not just a technological matter. It involves making key decisions about architecture, security, data governance, integration with existing systems, and adoption by teams. Without the right approach, many projects remain isolated tests that fail to scale or create distrust within the organization.
That’s why having a specialized technology partner is essential. An experienced partner like LISDATA helps define the right use cases, ensures that AI agents are built on secure, scalable foundations, and supports the company throughout the entire project lifecycle: from initial design to deployment and evolution in production.
Why work with a Microsoft partner to create AI agents?
Working with a Microsoft partner such as LISDATA ensures that AI agent projects are developed according to proven standards of quality, security, and reliability. Partner companies meet the requirements and frameworks defined by Microsoft, which means in-depth knowledge of its platforms, best practices in architecture, and an approach aligned with the demands of corporate environments. This is especially relevant when handling sensitive data, when control over information is required, or when compliance with internal security regulations and policies is necessary.
In addition to that technological backing, at LISDATA we support companies throughout the entire process of building AI agents. We don’t just implement technology; we work alongside teams to identify use cases with real impact, design solutions tailored to each organization, and ensure a gradual, sustainable adoption. Our approach is practical and hands-on, helping move from idea to action, and from there to continuous improvement, so that AI agents become a useful, reliable tool in the company’s day-to-day operations.