Azure RAG Pipeline Uses Terraform to Power Internal Docs Q&A System

A technical guide published on DEV Community outlines how to build an internal knowledge Q&A system using Azure AI Search and Azure OpenAI, addressing a common enterprise problem of scattered product docs and policy PDFs. The architecture routes documents through Azure Blob Storage, indexes them via Azure AI Search with hybrid vector and keyword search, and generates grounded answers with citations through the Azure OpenAI API. Infrastructure is provisioned entirely with Terraform, making the setup repeatable and version-controlled. Both the embedding and generation models are defined as Terraform variables, meaning teams can swap or upgrade models by editing a single configuration file rather than rewriting code. The pipeline also incorporates a lightweight evaluation step designed to catch performance regressions before changes reach production.