Explore how to build secure and production-ready healthcare AI applications with .NET in this session from the Software Architecture Conference 2026, presented by Indrakumar Rajendran.

The session focuses on the architectural considerations involved in developing AI-powered healthcare applications where security, privacy, governance, reliability, and human oversight are critical. It demonstrates how .NET can be used to build healthcare AI solutions that combine modern AI capabilities with secure application architecture.

Key topics include secure APIs, Retrieval-Augmented Generation (RAG), healthcare data protection, AI application architecture, and human-in-the-loop design. The session highlights how RAG can help AI applications work with relevant healthcare information while maintaining controlled access to data, and how human review can remain part of important AI-assisted workflows.

The session is particularly relevant for .NET developers, software architects, AI engineers, healthcare technology professionals, solution architects, and engineering leaders building AI applications for regulated or security-sensitive environments.

Learn how to combine .NET, secure APIs, RAG, governance, security and privacy practices, and human-in-the-loop workflows to design more reliable AI applications for healthcare and other sensitive domains.