A Prompt Column is a new AI-powered data type in Microsoft Dataverse (currently in preview) that allows you to define natural language prompts tied to other columns in a table. These prompts are processed by an AI model to generate relevant responses, which are then persistently stored in the prompt column. This column value can be used in apps, workflows, or reports. Prerequisites To […]
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What is MCP? Model Context Protocol (MCP) represents a new standard for building secure and scalable AI extensions. In this blog, we explore how MCP enables developers to build modular, plug-and-play capabilities that Copilot Studio agents can invoke, making the agents more powerful, contextual, and personalized. Model Context Protocol (MCP) allows users to connect with existing
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Autonomous agents are advanced AI systems designed to operate independently, managing and automating complex business tasks to enhance efficiency and innovation within an organization. Unlike simpler retrieval-based or task-based agents, autonomous agents do not require constant human input. Instead, they are pre-programmed to respond to specific triggers or events. Key Characteristics: Sample Scenario: An autonomous agent
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How to Extend Microsoft 365 Copilot with agents? Microsoft 365 Copilot is an AI-powered productivity tool that keeps users in the flow of their work across Microsoft 365 applications. It provides default experiences for engaging with content and resources from across an organization. Using Copilot Studio, we can extend Microsoft 365 Copilot with a specialized
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Azure AI Search enables intelligent, AI-powered search capabilities inside Copilot Studio, allowing bots to retrieve relevant information from structured and unstructured data sources. By integrating Azure AI Search, Copilot can search, rank, and return precise answers from documents, FAQs, policies, and other knowledge bases. Sample Use Cases Step 1: Create an Azure Subscription Azure is
Azure AI Search enables intelligent, AI-powered search capabilities inside Copilot Studio, allowing bots to retrieve relevant information from structured and unstructured data sources. By integrating Azure AI Search, Copilot can search, rank, and return precise answers from documents, FAQs, policies, and other knowledge bases. Advantages Pre-requisite Assumptions before proceeding to create Azure AI Search Service:
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Copilot Studio now allows users to upload images directly into the platform. Once uploaded, Copilot will analyze these images and provide contextually accurate responses based on the visual content. This feature is set to enhance the interaction quality by making AI responses more intuitive and visually informed. In generative mode, we can upload images directly
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With Copilot Studio, we can configure our copilot to hand off conversations to live agents seamlessly and contextually. When your copilot hands off a conversation, it shares the full history of the conversation, and all variables collected in the interaction. Dynamics 365 Customer Service routes incoming escalations to the right queue, and a live agent
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Microsoft Copilot is now available on WhatsApp. This innovative integration allows users to effortlessly harness the power of AI to boost productivity and streamline their tasks. https://www.microsoft.com/en-us/microsoft-copilot/for-individuals/onwhatsapp Happy Copiloting !!!
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In this post, we’re exploring a practical implementation of Copilot Studio where a Copilot is deployed on a custom website integrated with Dataverse and AI Builder for enhanced functionality. What sets this solution apart is the use of Manual Authentication to securely connect the Copilot to external systems, specifically for interacting with Dataverse data and
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