Written by Govind Kamtamneni with JD Chibuk, this post guides readers through building cognitive biosensing AI apps on Azure using BCI, AI Foundry, and Agent Services. It showcases real-world scenarios, advanced architecture, and opportunities for developers.

Build Biosensing AI-Native Apps on Azure with BCI, AI Foundry, and Agents Service

Authors: Govind Kamtamneni and JD Chibuk, Founder Blueberry X

Introduction

We obsessively track physical health metrics like steps, heart rate, and sleep—but what about our mental state? Most of us are unaware of how stress, focus, and cognitive overload manifest physiologically. Capturing cognitive indicators can empower us to manage thinking, feelings, and actions in high-stress situations for the better.

🤖 Meet Your Cognitive Copilot

Imagine an AI agent that observes cognitive indicators, learns your behavioral patterns, and supports you in real time. Using technologies such as functional near-infrared spectroscopy (fNIRS), this vision is now a reality. The market is shifting towards these advanced tools for those seeking a performance edge.

These agents are designed to enhance human judgment, rather than replace it.

🎯 Real-World Applications

🏆 Sports & Performance

  • Golf: Real-time emotional regulation insights help improve shot accuracy.
  • High-impact sports: Understand the physiological impact of sports and relative blood flow responses.
  • Motorsport: Formula 1 and other drivers receive cognitive load monitoring for optimal performance, training feedback, and reminders to regulate breathing.
  • Demo: See this in action at motorsports.blueberryx.com (hosted on Azure).

⚕️ High-Stakes Professions

  • Aviation: Pilots optimize communication timing and attentional focus.
  • Surgery: Surgeons receive early alerts about stress before motor control is impaired.
  • Mining: Operators are warned of cognitive overload to help prevent accidents.

💼 Workplace Innovation

  • Healthcare: Doctors manage emotional responses during tough cases.
  • Software Development: Developers monitor mental fatigue to boost productivity.
  • Leadership: Leaders understand team-level cognitive load.
  • Finance: Stockbrokers get fatigue alerts to avoid suboptimal decisions.

Beyond Basic Wearables

Unlike standard fitness trackers, these agents use contextualized intelligence. The Azure TypeAgent BCI Sample integrates:

  • Cognitive indicator data
  • Audio/visual inputs
  • Location and calendar context
  • Biometric signals

Modular Bio-Sensing

Technologies like fNIRS are small and modular. They can be embedded into wearables such as eyeglasses, hats, headphones, and headbands, providing pulse rate, muscle movement, and deep tissue blood flow response indicators. This adaptability supports cognition-centric wearables.

🪞 Your Digital Cognitive Mirror

As these AI agents learn, they build a living cognitive model for the user—a digital mirror reflecting mental state and performance. Over time, this resource powers:

  • Self-awareness
  • Performance optimization
  • Strategic decision-making

🛠️ Builder’s Opportunity

For developers, product managers, and innovators, this opens new markets for adaptive, insight-driven workplace tools. Example applications include:

  • Emergency responders under pressure
  • Financial analysts during volatile markets
  • Factory operators for safety monitoring
  • Corporate teams maximizing well-being

🔧 Technical Architecture Overview

End-to-end architecture for the TypeAgent BCI sample

1. Input Streams:

  • Neuro-signals sourced from BlueberryX headsets (fNIRS), combined with data like heart rate, Teams messages, email, voice, and other sensors.
  • Data is normalized into a time-stamped event feed using Azure Event Grid or Event Hubs.

2. Meta Agent Orchestration:

  • A Meta Agent (built using TypeAgent or similar orchestration) runs on Azure Container Apps.
  • It delegates to specialized sub-agents for tasks like email replies, meditation, feedback, and context-specific assistance (e.g., golf-stroke analysis).

3. Reasoning & Content Generation:

  • Each agent leverages Azure AI Foundry models (like GPT-4o, o3, DALL-E), accessible via the AI Agents Service.
  • Capabilities include Bing search, function execution, and knowledge retrieval.

4. State & Search:

  • Long-term and time-series data is stored in Cosmos DB.
  • Embeddings (text/multimodal) are indexed with Azure AI Search for RAG (retrieval-augmented generation) lookups.

5. Actionable Outputs:

  • Agents deliver real-time dashboards, research reports, adaptive scripts (e.g., for meditation), and AI-generated diagrams personalized to users’ cognitive states.

⏰ Call to Action

If you’re interested in advancing human self-awareness, capability, and control via AI and biosensing, connect with the authors!

The future of emotionally intelligent digital tools starts here—get involved and help shape it.

This post appeared first on “Microsoft DevBlog”. Read the entire article here