Architecting AI-Powered Enterprise Systems in .NET

In this session, we’ll go beyond “calling an LLM” and focus on how to architect AI features that can actually ship in enterprise .NET systems. You’ll learn how to design a production-ready AI-powered API using Clean Architecture principles, where AI remains an Infrastructure concern behind clear interfaces for testability and vendor independence. We’ll break down Retrieval-Augmented Generation (RAG) end-to-end: document chunking, embedding generation, semantic search with PostgreSQL + pgvector, top-K retrieval, prompt construction with grounded context, and returning answers with citations for auditability. We’ll also cover the hard engineering parts: latency and throughput considerations, token/cost awareness, timeouts and retries, caching strategies, guardrails for hallucinations and “unknown” responses, prompt injection risks, and safe logging/observability. A pre-built ASP.NET Core demo will show ingestion and question-answer endpoints, so you leave with a clear blueprint you can adapt to real systems.