You have a product support manual. You need to build a product support chatbot based on the manual. The solution must minimize development effort and costs. What should you use?

Custom question answering, a feature of Azure AI Language, is specifically designed to create a conversational question-and-answer layer over existing content, such as product manuals. This service minimizes development effort by allowing you to simply point to your content; it then automatically extracts and indexes information to build a knowledge base. This purpose-built solution is the most direct, cost-effective, and low-effort approach to creating a support chatbot from a single document, directly aligning with the stated requirements.

A. Azure AI Phi-3-medium with fine-tuning requires significant data preparation, training, and deployment effort, which contradicts the goal of minimizing development and cost.
C. This describes a Retrieval-Augmented Generation (RAG) pattern. While powerful, it is more complex and costly to implement, involving multiple services (Azure OpenAI, Azure AI Search), than the purpose-built Custom question answering feature.
D. Azure AI Document Intelligence is used for extracting text and structure from documents. It is a data extraction tool, not a complete chatbot or question-answering solution.

1. Microsoft Documentation, Azure AI Language, "What is question answering?": "Question answering provides cloud-based Natural Language Processing (NLP) that allows you to create a natural conversational layer over your data. It is used to find the most appropriate answer for any input from your custom knowledge base (KB) of information." It lists "Product Manuals" as a common data source.

Source: Microsoft Learn, learn.microsoft.com/en-us/azure/ai-services/language-service/question-answering/overview (Section: "When to use question answering").

2. Microsoft Documentation, Azure AI Language, "Question answering quickstart": The quickstart guide demonstrates that a user can create a fully functional knowledge base simply by providing a URL or uploading a file, highlighting the minimal development effort required.

Source: Microsoft Learn, learn.microsoft.com/en-us/azure/ai-services/language-service/question-answering/quickstart/sdk (Section: "Create a question answering project").

3. Microsoft Documentation, Azure OpenAI, "Azure OpenAI on your data": This document outlines the architecture which requires setting up an Azure AI Search resource, creating an index, and configuring an Azure OpenAI model. This multi-step process is more complex than the single-service approach of Custom question answering.

Source: Microsoft Learn, learn.microsoft.com/en-us/azure/ai-services/openai/concepts/use-your-data (Section: "How it works").

4. Microsoft Documentation, Azure AI Document Intelligence, "What is Azure AI Document Intelligence?": "Azure AI Document Intelligence is a cloud-based Azure AI service that enables you to build intelligent document processing solutions... It's not a standalone conversational agent."

Source: Microsoft Learn, learn.microsoft.com/en-us/azure/ai-services/document-intelligence/overview (Section: "What is Azure AI Document Intelligence?").