Q&A

Building Generative AI Applications with Azure AI Foundry

• By David Ramel
• 03/06/2025

With everyone scrambling to keep abreast of the rapidly advancing GenAI space, where some new tool or tech seems to be announced every week, Azure AI Foundry has emerged as a crucial end-to-end platform in the Microsoft-centric developer space.

Azure AI Foundry is a unified platform for enterprise AI operations, model development, and application building, offering production-grade infrastructure and user-friendly interfaces for seamless AI deployment. Specifically, Microsoft says it's designed to help developers:

• Build generative AI applications on an enterprise-grade platform.
• Explore, build, test, and deploy using cutting-edge AI tools and ML models, grounded in responsible AI practices.
• Collaborate with a team for the full life-cycle of application development.

Because the platform (formerly called Azure AI Studio) is so important in Microsoft's ecosystem, the best way to learn about it is through immersive, hands-on training from the company's own front-line experts.

And that's exactly what Maxim Salnikov, Developer Productivity Lead, will provide in the From Traction to Production: Building Generative AI Applications with Azure AI Foundry two-day virtual training seminar taking place March 25-26.

It's part of the Live! 360 Conferences series of developer-education events, including Visual Studio Live! and many more, presented by the parent company of Visual Studio Magazine.

With our special access, we asked Maxim to tell us more about his seminar in a short Q&A.

VisualStudioMagazine: What inspired you to present a seminar on this topic?
Generative AI is transforming the way developers build applications, enabling new levels of automation, creativity, and user interaction. With Azure AI Foundry, Microsoft is providing a powerful suite of tools to make AI development more accessible and scalable.

My goal with this seminar is to bridge the gap between cutting-edge AI technology and practical application by helping developers understand how to leverage Azure AI Foundry effectively. Seeing the growing interest in AI-powered copilots and enterprise AI solutions, I wanted to provide hands-on insights into how businesses and developers can integrate these capabilities seamlessly.

What makes Azure AI Foundry different from other AI development platforms?
Azure AI Foundry stands out by offering an end-to-end AI development environment tailored for both beginners and experts. Unlike many other platforms, it provides deep integration with enterprise-grade security, compliance, and governance features. It also offers pre-built AI models, tools for fine-tuning, and a seamless deployment pipeline. Another key differentiator is its robust ecosystem within Microsoft Azure, allowing for seamless connectivity with data sources, cloud infrastructure, and existing enterprise applications.

How does Azure AI Foundry simplify the process of building and deploying generative AI applications?
Azure AI Foundry streamlines AI development through a no-code/low-code interface, intuitive APIs, and automated GenAIOps pipelines. Developers can quickly experiment with pre-trained models, fine-tune them using custom datasets, and deploy them with minimal effort. The platform also provides tools for prompt engineering, evaluation, and optimization, ensuring that applications are efficient and production-ready. With built-in monitoring and scaling capabilities, teams can focus on innovation rather than infrastructure management.

What are some key security considerations when using Azure AI for AI-driven applications?
Security is a top priority when deploying AI applications, especially in enterprise environments. Azure AI Foundry incorporates industry-leading security measures, including data encryption, secure model hosting, and identity management. Additionally, responsible AI frameworks within Azure AI Foundry help ensure transparency, fairness, and accountability in AI-driven decision-making.

How can developers fine-tune AI models within Azure AI Foundry without extensive machine learning expertise?
Azure AI Foundry provides an accessible approach to model fine-tuning through automated workflows and user-friendly tools. Developers can leverage fine-tuning with minimal code using the platform’s managed services. This allows developers to enhance AI performance without needing deep expertise in data science or ML engineering.

What are some practical use cases for integrating custom data into AI-powered copilots?
Custom data integration into AI copilots unlocks numerous possibilities across industries. Some common use cases include:

• Customer Support: Enhancing chatbots with company-specific knowledge bases for more accurate responses.
• Finance: Automating compliance checks and risk assessments using proprietary financial data.
• Retail and E-commerce: Personalizing recommendations based on customer behavior and inventory data.

How does Azure AI Foundry help ensure responsible AI practices in deployed applications?
Responsible AI is a key focus within Azure AI Foundry, and Microsoft provides various tools and frameworks to support ethical AI development. The platform includes built-in model evaluation for fairness, bias detection, and explainability features to ensure transparency.

What resources would you recommend for attendees to get up to speed with Azure AI Foundry and prepare for your session?
For those looking to dive into Azure AI Foundry before attending the seminar, I recommend exploring the following resources:

• Azure AI Foundry Documentation: Official documentation with guides and API references.
• Microsoft Learn: Interactive tutorials and courses on Azure AI Foundry.
• Azure AI Foundry Playground: A hands-on way to experiment with AI models.

Note: Those wishing to attend the seminar can save money by registering early, according to the event's pricing page. "Save $150 when you register by the Early Bird savings deadline of March 14," said the organizer of the event.