Bot Agents in Teams: Smart Search and Data Delivery

LeverX developed a smart bot for Microsoft Teams using Microsoft Copilot Studio and Azure OpenAI.

Client and Challenge

A large international retailer was struggling with fragmented data scattered across multiple, disconnected platforms like CRM, SharePoint, and various chat applications. This led to several key challenges for the company:

• Wasted Time and Reduced Efficiency: Employees spent valuable time manually searching for client data and documents instead of focusing on their primary tasks.
• Lack of Unified Context: The fragmented information led to delays and duplicated work.
• Operational Bottlenecks: The absence of a single view of the data created operational delays and forced employees to perform the same work multiple times.

Methodology and Approach

To tackle these challenges, LeverX adopted a structured and agile methodology. The key stages of their work included:

1. Problem Analysis: They started with a deep analysis of the client's fragmented data environment to identify key pain points in information retrieval and collaboration.
2. Technology Selection: LeverX chose Microsoft Copilot Studio and Azure OpenAI to build an intelligent, natural-language-aware bot.
3. Integration Design: They designed a solution to connect the bot to various back-end systems, including SharePoint, Dataverse, and the client's CRM, to create a unified search experience.
4. Iterative Development: The bot was developed to understand natural language and perform specific tasks like fetching documents, summarizing content, and retrieving case details.
5. Contextual Logic: LeverX implemented logic that allows the bot to personalize responses based on the user and the specific case they are asking about, ensuring replies are context-aware.

Solution

LeverX created a smart bot agent that serves as a single, conversational interface for corporate knowledge, deployed directly within Microsoft Teams. Key aspects of this solution are:

• Unified Search Experience: The bot allows users to ask one question in Teams and get results from across different systems.
• Natural Language Processing: The bot understands natural language queries, such as "What is the current status of the Acme contract?".
• Document Finder & Summarizer: It can fetch relevant documents from SharePoint and provide key sections or summaries.
• Intelligent Data Retrieval: The bot can look up client or case details via Dataverse or CRM and can even calculate basic scores, statuses, timelines, and open issues.
• Context-Aware Responses: The bot personalizes its replies based on who is asking and the specific case being discussed.

Technology Stack

The solution is built on a robust technology stack to ensure functionality and scalability.

• Platform: Microsoft Teams, Microsoft Copilot Studio, Azure OpenAI.
• Data Sources: SharePoint, CRM, Dataverse.

Results

This solution makes information retrieval faster, more accurate, and more aligned with how employees work.

• Unified Knowledge Access: A single interface provides access to enterprise knowledge from various systems.
• Accelerated Information Retrieval: Information is retrieved in seconds, drastically reducing search time.
• Increased Productivity: The bot eliminates the need to switch between tabs or dig through folders, boosting overall productivity.
• Personalized Responses: The bot provides context-aware and personalized replies.

The bot successfully centralizes fragmented information into a single, conversational interface within Teams, allowing employees to access crucial data and insights in seconds. This significantly boosts productivity, reduces wasted effort, and creates a more efficient way for teams to work and collaborate.