AI-Powered Customer Success with Semantic Kernel by info.odysseyx@gmail.com October 14, 2024 written by info.odysseyx@gmail.com October 14, 2024 0 comment 1 views 1 semantic kernel A powerful SDK designed to integrate AI models into your applications to improve responsiveness and contextual understanding. It helps developers build sophisticated AI solutions by providing essential tools for chat completion, multi-agent coordination, and data discovery. that Virtual Customer Success Manager (VCSM), Featured at Hackathon ’24.is a C# .NET project built using the Semantic Kernel. VCSM transforms customer support, onboarding, and engagement by providing personalized interactions, proactive service, and tailored recommendations. VCSM leverages the Semantic Kernel to dynamically adapt to user needs to improve customer experience and streamline business operations. Here is a quick demo of this solution. We also provide value-based services including: Improve agent AI system technologyis designed to upskill and enable teams to capture AI-driven business value. This service accelerates your deployment capabilities. Azure OpenAIIt is powered by an Agentic AI system that incorporates customer success into delivery by design. VCSM leverages three core features of the Semantic Kernel:Chat Completion Model, Multi-Agent Frameworkand Vector Store—Provides three main use cases: Customized onboarding, Proactive supportand Personalized Recommendations. 1. Customized onboarding semantic kernel Chat Completion Model and plugin VCSM allows you to deliver an interactive, real-time onboarding experience. through automatic function callThe system dynamically guides users through the product setup process by calling appropriate functions based on user queries, such as GuideInitialSetup() or explainFeatures(). 2. Active support that Multi-Agent Framework Coordinate professional agents to monitor and resolve system issues. no way master agent Supervises the following agents: team agent (Microsoft Teams Monitoring) and Azure agent (AKS Health Analysis) Together, they proactively resolve issues to ensure system stability. 3. Personalized recommendations with Vector Store When enabled, VCSM uses Retrieval Augmented Generation (RAG) patterns to retrieve customer-specific data, such as usage patterns and preferences. This allows VCSM to deliver personalized tips and recommendations in real time and provide users with highly relevant insights based on past interactions and stored data. VCSM combines these Semantic Kernel capabilities to deliver a seamless, user-centric experience that transforms the way companies approach customer engagement and support. This section provides a high-level overview of the key modules that implement the onboarding, support, and recommendation functionality of the system. Full implementation and setup details can be found here: GitHub repository. 1. VCSM_PersonalizedOnboarding.cs This module focuses on implementing personalized onboarding using plugins from the Semantic Kernel. that Team onboarding pluginSupports features in Microsoft Teams to provide an interactive onboarding experience by automatically switching between the following features based on user requests: Guide initial settings (): Helps users set up Microsoft Teams for the first time. description function(): Details the key features of Microsoft Teams, including chat, meetings, and file sharing. Productivity Tips (): We suggest best practices and tips to improve productivity when using Microsoft Teams. The code dynamically adjusts based on user queries, making the onboarding process personalized and efficient. 2. VCSM_ProactiveSupportWithAgents.cs This module handles: Proactive support by implementing A multi-agent framework for semantic kernels. that master agent Coordinate responses between two expert agents. team agent: Monitor the performance of Microsoft Teams to identify issues like frequent disconnects or crashes. Azure agent: analyze Azure Kubernetes Service (AKS) About potential issues such as CPU and memory overuse or node exhaustion. After deliberation between the parties master agent Based on the content agreed upon with the professional agent exit strategyRecommended, crafted responses are provided for incoming system alerts. Through this parallel coordination, VCSM provides proactive, real-time support to keep your system healthy and optimized. 3. VCSM_TailoredRecommendations.cs This module is responsible for providing: Personalized Recommendations By utilizing Vector Store Deliver personalized insights. The system uploads customer-specific content (e.g. PDFs such as teamguide.pdf or teamrecommendations.pdf) and responds to user queries in a highly customized way. The workflow works like this: Profile setup instructions: For questions such as “How do I set up my profile?”, Vector Store retrieves relevant instructions and passes them to the Large Language Learning Model (LLM) to generate a personalized response. Feature Overview: When a user asks, “What features does Teams provide?”, Vector Store pulls detailed information about Teams features, allowing the system to provide a comprehensive overview. productivity tips: The system extracts actionable insights from stored content and provides personalized tips to improve productivity in Microsoft Teams. VCSM improves the user experience by combining real-time user queries with data retrieved from the vector store to create situational awareness and highly relevant recommendations. that Virtual Customer Success Manager (VCSM)Built using semantic kernel and utilize Azure OpenAIdemonstrates the power of AI-based solutions to transform customer interactions. VCSM provides dynamic, context-aware onboarding, proactive support, and personalized recommendations by seamlessly integrating chat completion, multi-agent systems, and personalized data discovery. This solution not only improves user experience but also streamlines business operations, providing a scalable approach to customer success management. 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