Build Your Own Enterprise ChatGPT with Azure OpenAI and C# (Including a Project Knowledge Engine)
A chat orchestration layer
Conversation memory with token-aware trimming
A project-based knowledge engine that can ingest 20–40 local files
Embedding generation and vector similarity search (without Azure AI Search)
Prompt injection for grounded responses
A Web API layer suitable for real-world deployment
Production considerations including ingress, rate limiting, and cost control
Attendees will implement a miniature Retrieval-Augmented Generation (RAG) system using in-memory vector search, learning how modern AI assistants are constructed under the hood.
The session concludes with a comparison between local vector storage, SQL vector capabilities, and enterprise-scale Azure AI Search architecture — providing a clear upgrade path from conference demo to production system.
This workshop is intended for senior developers, cloud engineers, and solution architects who want to move beyond simaple AI API calls and understand the architectural patterns required to build secure, scalable AI applications in the enterprise.