Case study of implementing a RAG chatbot that achieved a 60% reduction in help desk inquiries.
We will share a case study where we implemented a RAG chatbot in the internal help desk, reducing inquiry responses by 60%. We will explain the configuration using LangChain, vector DB, and GPT-4o, the secretive operation on-premises, estimated implementation costs, and a reliable approach based on real experiences. For more details, please refer to the technical column in the related links.
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basic information
【Technical Elements】 - RAG (Retrieval-Augmented Generation) - LangChain - Vector DB - GPT-4o - On-Premises Confidential Operations 【Category】AI・Chatbot *For more details, please refer to the technical column in the related links.
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Applications/Examples of results
【Intended Use】 - Automation of internal help desk inquiries - Efficiency improvement in searching internal regulations and manuals - Reduction of inquiry response workload 【Example of Achievements】 - Reduced internal help desk inquiry responses by 60%
Company information
Technosphere Co., Ltd. is a system development company based in Osaka that tackles customer challenges in advanced technology areas such as AI, IoT, and web system development. Since its founding in 2021, the company has leveraged a flat team structure to achieve a flexible and speedy development style. We are engaged in solutions that directly address social issues, such as image inspection AI and smart factory support systems.
