AI Chatbots for Energy Management Customer Support Retrieval
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Solution Overview
Problem
Conventional power conversion systems lack scalability and efficiency in customer support due to scattered information that is not easily accessible to customer service teams, making human agent support inefficient.
Innovation Solution
Implementing AI chatbots with large language models (LLMs) that integrate with user interfaces, customer service agents, and storage layers to provide automated responses and enhance customer support through chain-of-thought prompting and retrieval-augmented generation frameworks, utilizing domain-specific models for energy management systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If human agents provide customer support in conventional power conversion systems, then customer support can be provided with detailed knowledge, but the system lacks scalability and efficiency due to scattered information not being easily accessible
Solution Approach 1:
The patent introduces an AI chatbot as an intermediary between customers and the scattered information sources. The chatbot acts as a mediator that automatically searches, retrieves, and synthesizes information from multiple data sources (tickets, knowledge base, product documentation) to provide coherent responses, eliminating the need for human agents to manually navigate complex information scattered across the tool chain.
Solution Approach 2:
The system enables self-service through the AI chatbot that autonomously accesses and processes scattered information from multiple sources. The chatbot independently retrieves relevant data from tickets, knowledge base articles, and product documentation without human intervention, providing automated customer support that scales efficiently while maintaining information accuracy.
2Quantity of substance
If more information is scattered across the tool chain, then more detailed data is available, but it becomes harder to access and process this information efficiently
Solution Approach 1:
The patent implements feedback mechanisms where the AI chatbot continuously learns from customer interactions and updates its response strategies. The system analyzes the quality and relevance of retrieved information, adjusts its search queries in real-time, and refines its synthesis process to reduce information retrieval time while maintaining comprehensive data access.
Solution Approach 2:
The system performs preliminary actions by pre-processing and indexing scattered information from multiple sources before customer queries arrive. The AI chatbot maintains an updated knowledge structure that pre-organizes data from tickets, knowledge base, and product documentation, enabling rapid retrieval and synthesis when customers ask questions without requiring real-time searching through all scattered data.
Data Source
AI summary
An apparatus for use with energy management systems is provided and comprises a user interface and a Chatbot in operable communication with the user interface for receiving a query and transmitting a response to the query and in operable communication with at least one of a large language model (LLM) tool/agent, a LLM service, customer service (CS) agent, or storage layer for developing the response to the query.