FREE PROJECT
Build an End-to-EndHealthcare AI Assistantusing Microsoft Foundry
Build an AI assistant that retrieves patient records, manages appointments, answers hospital policy questions and processes discharge documents, using GPT-5-mini, Python and Microsoft Agent Framework.
- 7 hands-on parts, from the first agent to a tested multi-agent solution
- RAG, function calling, Azure AI Content Understanding and MCP in one project
- A portfolio project you can show to employers
Get the free project
Fill in your details and we will send the project guide straight to your inbox.
- 7Hands-on build parts
- 3Specialist AI agents
- 8Skills you will gain
- 1End-to-end portfolio project
A complete healthcare AI solution
You build it in seven parts, powered by Microsoft Foundry, GPT-5-mini, Python, RAG, Azure AI Content Understanding and Microsoft Agent Framework.
AI Healthcare Assistant
Build an AI agent with conversation memory, safety instructions and contextual responses.
Hospital knowledge retrieval (RAG)
Search hospital policy documents and generate grounded answers from what you retrieve.
Patient records and appointments
Add Python function-calling tools to retrieve patient records, check appointments and schedule follow-ups.
Discharge document intelligence
Use Azure AI Content Understanding to extract structured data from discharge notes and write patient-friendly summaries.
Multi-agent orchestration
Coordinate specialized agents for patient records, appointment scheduling and discharge workflows.
MCP integration
Connect the agent to the Microsoft Learn MCP server to discover tools and fetch current technical documentation.
Foundry setup and testing
Deploy AI models, configure your Python environment, authenticate with Azure and test the complete solution.
Automate real healthcare support work with AI agents
Healthcare organizations handle patient records, appointment scheduling, hospital policies and discharge documentation. Managing these workflows by hand takes a lot of time.
This project shows how a team of AI agents can take on that work, and how enterprise teams combine generative AI, RAG, document intelligence, function calling and multi-agent orchestration in one practical application.
Ideal for
What your assistant can do at the end
By the end, you have a complete end-to-end healthcare AI solution that can:
- Answer hospital policy questions using trusted documents
- Retrieve patient and appointment information
- Automate follow-up appointment scheduling
- Extract structured data from discharge notes
- Generate patient-friendly summaries
- Coordinate multi-agent workflows
- Retrieve documentation using MCP
- A project that strengthens your AI engineering portfolio
Hands-on projects that get people hired
Hear it from K21 Academy learners who built real projects and moved into AI roles.
“I have finally secured a contract-to-hire role as a Generative AI Engineer.”I was deploying a RAG pipeline to a web app during the actual hiring process. The projects I built at K21 were exactly what the company needed.
“I'm thrilled to share that I've recently landed a role as a Generative AI Engineer.”The hands-on projects let me confidently describe an end-to-end AI solution in the interview. The interviewer was genuinely impressed.
“I've successfully landed a job as an AI Engineer.”Worked hands-on with Azure AI services, Azure AI Foundry, and OpenAI. Later received a second offer as a Generative AI Engineer. K21 gave me the skills and confidence to choose.
“The support is extremely awesome for labs, doubts and even resume updates.”I am 3 weeks into the AI/ML program. The team creates a custom game plan and learning path for everyone. The real-world project experiences and hands-on lab experience is a key differentiator.
“I got cracked that role.”The Azure AI/ML trainee landed the job after completing the program and building out her portfolio.
“I joined K21 Academy at a time when I felt stuck and unsure about my career direction.”Connecting with Shahid was a turning point. He gave me clarity, practical guidance, and renewed confidence. The AI curriculum is exhaustive and serves as a one-stop shop for AI and ML.
Before you download
Is the project guide really free?
Yes. Fill in the form and the project guide is sent to your inbox at no cost.
What will I build?
A multi-agent Healthcare AI Assistant that answers hospital policy questions with RAG, retrieves patient and appointment information, schedules follow-ups, extracts data from discharge notes and connects to the Microsoft Learn MCP server.
Which tools does the project use?
Microsoft Foundry, GPT-5-mini, Python, Azure AI Content Understanding and Microsoft Agent Framework. You will deploy the models, set up your Python environment, sign in to Azure and test the full solution.
Who is it for?
AI engineers, cloud engineers and architects, backend developers, data engineers, machine learning engineers, automation engineers, solutions architects, and developers exploring AI agents.
Ready to build your first AI agent project?
Get the step by step guide and build an end-to-end Healthcare AI Assistant with Microsoft Foundry, from the first agent to a tested multi-agent solution.
Get the free project guideEnd to end
From Foundry setup and your first agent to RAG, tools, multi-agent orchestration and MCP.
Real workflows
Patient records, appointments, hospital policies and discharge documents.
Portfolio ready
A complete project you can show to hiring managers.
Current tooling
GPT-5-mini, Microsoft Agent Framework and the Microsoft Learn MCP server.