Build a Custom Copilot

About the Course:

Microsoft Copilot was launched in February 2023 as a chatbot for coding assistance. Later, it branched out into assisting with debugging and eventually answering general knowledge questions using natural spoken language. Now, AI Engineers can leverage the same intelligence on their own proprietary data while maintaining full access and control over their data. Documents can be uploaded and utilized as a knowledge base for Copilot to use for reasoning and answering questions in natural language. 

This creates a fully customized Copilot experience while maintaining data privacy. In this session, we’ll explore Copilot from basic to advanced and the tools available for creating a rich user experience. Microsoft Copilot is transforming how organizations interact with information, automate tasks, and build intelligent user experiences. This hands-on session introduces developers and AI professionals to the process of creating a custom Copilot experience powered by proprietary business data while maintaining enterprise-grade privacy and control. Participants will explore how modern large language models can move beyond public knowledge and reason over internal documents, enabling organizations to build AI assistants tailored to customer support, operations, internal knowledge management, and business workflows. Starting with the fundamentals of Microsoft Foundry and the Chat Playground, attendees will learn how documents are uploaded, indexed, and prepared for intelligent retrieval and natural language interaction.

The session then moves into practical implementation, showing how to connect indexed Azure-hosted content to LLMs through API-driven integrations that power custom conversational experiences. Participants will see how AI engineers and developers can build secure, scalable copilots capable of answering questions, summarizing content, and providing contextual assistance using enterprise-specific knowledge sources. Along the way, the workshop highlights best practices for user experience design, privacy-aware AI architecture, and integrating Copilot capabilities into modern applications and workflows. By the end of the session, attendees will understand the core building blocks required to create a customized Copilot solution on Microsoft Azure using their own organizational data.

Course Objectives:

• Utilize Chat Playground in Microsoft Foundry.
• Uploading and indexing documents in Azure for LLM Access.
• Accessing LLM via API calls to create a custom Copilot user experience.

Who is the Target Audience?

• AI Engineers
• Software Developers
• Systems Analysts
• Solution architects designing AI-powered business applications
• Cloud architects implementing secure AI solutions on Microsoft Azure
• Enterprise application developers building internal AI assistants and knowledge bots
• Technical product managers evaluating custom Copilot use cases for customer and employee experiences
• IT managers exploring secure enterprise AI adoption strategies
• Data engineers supporting document ingestion, indexing, and retrieval workflows
• Knowledge management teams are building searchable AI-powered knowledge bases
• Digital transformation leaders are modernizing customer support and internal operations with AI
• Business intelligence professionals are integrating AI-assisted insights into enterprise workflows
• DevOps engineers deploying and maintaining AI-powered applications and APIs
• Platform engineers creating reusable AI infrastructure and services
• Customer support technology teams building AI-driven support assistants and helpdesk copilots
• Internal tools teams are developing employee productivity assistants using proprietary company data
• SharePoint and Microsoft 365 administrators exploring AI integrations with organizational content
• Innovation and R&D teams prototyping conversational AI applications
• Technical consultants implementing enterprise AI solutions for clients
• Startup founders and SaaS builders creating AI-enhanced customer experiences
• Enterprise search and information retrieval specialists working with semantic search and indexing
• UX designers and conversational experience designers interested in AI-assisted user interactions
• Security and compliance teams evaluating private AI deployments and data governance practices
• Business application developers using Microsoft Power Apps and low-code AI integrations
• AI adoption leaders building internal proof-of-concept copilots for enterprise teams
• Technical trainers and educators teaching practical enterprise AI implementation strategies
• API developers integrating LLM capabilities into web, desktop, or mobile applications
• Organizations building private AI assistants for HR, legal, finance, or operations departments
• Teams evaluating retrieval-augmented AI experiences using enterprise document repositories
• Microsoft ecosystem professionals working with Microsoft 365, Azure AI, and enterprise productivity platforms
• Cloud solution providers building managed AI services for business clients
• Developers transitioning from traditional applications to AI-native software experiences
• Engineering teams exploring secure prompt engineering and controlled enterprise AI workflows

Basic Knowledge:

• Fundamentals of Azure, Microsoft Foundry, LLM