Create Agent using Dataverse As a Knowledge Source

Ready to create your own Copilot Agent using your custom Dataverse? In this comprehensive guide, I’ll show you how to leverage Copilot Studio to build a powerful Bank Balance Checker Agent. This agent can handle real-time queries like account statuses, high-value customers, and balances—all using natural language inputs!

Unlock the power of AI to streamline customer account management! In this tutorial, I'll walk you through every step to build a Bank Balance Checker Copilot Agent using a database as the data source. This agent lets you handle customer queries efficiently by providing accurate data like active accounts, high-value customers, and account balances—all with natural language queries.

Discover how to Build a Dataverse-Powered Custom Copilot Agent using Copilot Studio in this step-by-step tutorial! 🚀 Learn to harness the power of Microsoft Dataverse and Copilot Studio to create intelligent agents that streamline customer interactions and automate data-driven tasks. Whether you're an AI enthusiast or a professional looking to improve business workflows, this video will guide you through every step.

What You’ll Learn in This Video:
How to set up and connect your Dataverse as the data source
Configuring a Copilot Agent with natural language capabilities
Adding synonyms and glossaries for enhanced user queries
Testing and publishing your agent to deliver real-world solutions
This tutorial focuses on a Bank Balance Checker Agent use case, showcasing how to query active accounts, customer balances, and other critical data. Perfect for Power Platform enthusiasts, developers, and AI beginners!

Why Watch This?
Simplify customer queries with AI
Gain hands-on experience with Microsoft Copilot Studio
Enhance your Dataverse integration skills

What’s Inside:
✅ Setting up your Dataverse for the Copilot Agent
✅ Configuring synonyms and glossaries for better understanding
✅ Linking your database to Copilot Studio
✅ Testing and verifying accurate responses
✅ Publishing your agent for seamless integration

0:00 Introduction to the Bank Balance Checker Copilot Agent
0:12 Overview of the use case
0:27 Dataverse structure explained
1:12 How the agent processes natural language queries
2:30 Querying active accounts
3:00 Verifying results with database views
4:08 Setting up your dataverse for the Copilot Agent
4:44 Accessing Copilot Studio
5:45 Creating and configuring the Copilot Agent
7:18 Linking the dataverse to the agent
8:59 Using synonyms and glossaries for better understanding
13:03 Configuring conversational responses
14:20 Publishing the Copilot Agent
15:09 Testing the agent with real queries
17:57 Where to integrate your Copilot Agent
18:22 Closing remarks and next steps

F O L L O W M E O N S O C I A L M E D I A
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