Real-Time AI: Take Your Apps to the Next Level with Cutting-Edge AI Features

As generative AI capabilities evolve from novelty to necessity, developers are seeking new ways to integrate intelligence directly into the user experience—without sacrificing speed or accessibility. One frontier showing particular promise is real-time AI: systems that process and respond to user input instantly, whether it's voice, text, or other dynamic data streams.

In his upcoming session at Visual Studio Live! San Diego 2025, developer and educator Dan Wahlin will demonstrate how real-time AI is transforming application interfaces. Titled "Real-Time AI: Take Your Apps to the Next Level with Cutting-Edge AI Features," the presentation explores how developers can infuse their apps with voice interactivity, real-time language feedback, and conversational agents—all powered by Azure OpenAI's GPT-4o and other Azure AI services.

Real-time AI capabilities offer immediate value in scenarios ranging from healthcare to education. Whether it's helping physicians complete patient forms hands-free or guiding language learners with pronunciation coaching, the session shows practical, low-latency examples developers can adopt today. Wahlin also dives into architecture considerations, performance optimizations, and platform flexibility—including support for hybrid apps like Electron or Blazor Hybrid.

He promises attendees will:

• Understand key real-time AI features
• Learn what AI models can be used and how to create them in Azure AI Foundry
• Understand the client-side and server-side components needed to create a full real-time AI solution

We caught up with Wahlin, a principal cloud developer architect at Microsoft, ahead of his session to learn more about what's possible with real-time AI and what developers should watch out for when bringing these next-gen features to life.

VisualStudioLive! What inspired you to present a session on this topic?
Wahlin: I enjoy helping developers "think outside the box" and create more natural, human-like interfaces. Real-time AI makes that possible and unlocks some unique capabilities. Whether it's completing forms with voice or learning a language through spoken conversation, the ability to interact without typing can dramatically improve accessibility and productivity.

The repo and demo that will be used in my VSLive! talk show practical, low-latency examples developers can start using today.

Can you give a quick example of a real-time AI feature you've personally built into a line-of-business app?
One example is a voice-driven medical form assistant that lets doctors complete forms by speaking, reducing time spent on manual input. The system listens to spoken input, parses key details with an AI model, and populates the form in real-time. It improves workflow efficiency and reduces typing errors. Another example is using real-time AI to help people learn a language. It can give phrases to practice and even check pronunciation and provide advice on improving it.

Are there any specific Azure AI models you recommend for real-time agent-style apps, especially ones that need fast and accurate responses?
As of today, Azure OpenAI's gpt-4o-realtime model can be used to build conversational AI apps. It handles the incoming stream of audio data from the user and converts text generated by the AI to audio which can be streamed back to the client.

What's the most common mistake developers make when implementing client-side components for real-time AI?
This is a brand-new AI technology area so it's still a bit early to identify common mistakes. Having said that, there are optimizations that can happen on the client-side and server-side to ensure that audio data is batched up as much as possible during the streaming process. Failing to optimize streaming input/output can lead to delays that break the user experience. Another issue is not handling edge cases like disconnects or dropped audio streams gracefully. Proper state management and responsiveness are key.

Can these real-time features be used in hybrid apps, like those built with Electron or Blazor Hybrid?
Yes, real-time AI features are generally platform-agnostic and can run anywhere JavaScript, .NET, or other languages run as long as there's support for Web Sockets or WebRTC.

How does Azure AI Foundry handle privacy or data retention for real-time input like voice or text?
Azure AI Foundry applies Microsoft's Responsible AI standards, including safeguards for data use, retention, and privacy apply to all AI scenarios including real-time. Details can be found Trustworthy AI for Azure AI Foundry.

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Posted by David Ramel on 05/29/2025