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  6. Case Study: Database Design Using Agent-Based RAG | Major Manufacturing Industry

Case Study: Database Design Using Agent-Based RAG | Major Manufacturing Industry

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last updated:Mar 13, 2025

homula
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Introducing a case study of a natural language processing automated response system!

We would like to introduce a case study on the implementation of "generative AI" in knowledge management at a major manufacturing company. The company faced the challenge of increased working hours due to inefficiencies in internal knowledge management. To address this, they implemented an agent-based RAG system, integrating the internal knowledge base (regulations, manuals, Q&A history, etc.). This enabled immediate responses to inquiries. 【Case Overview】 ■Challenges - Increased labor costs due to overlapping business processes - Increased burden of handling inquiries ■Results - Increased burden of handling inquiries - Streamlined information sharing and real-time updates of knowledge *For more details, please refer to the related links or feel free to contact us.

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Case Study: Database Design Using Agent-Based RAG | Major Manufacturing Industry

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  • Related Link - https://homula.notion.site/f31eef1df9fb4c1e94893c0…

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Homula Inc. Company Profile

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homula

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Homula Inc. aims to fundamentally transform corporate productivity through the development and provision of the AI agent "Agens," which understands and executes business tasks related to daily business communications such as meetings, emails, and chats. We integrate multimodal information such as voice and text, allowing AI to autonomously process the "ToDos" that arise from daily communication. We provide an environment where the insights and judgments of talented personnel can be converted into knowledge assets and deployed across the organization as reproducible processes. In recent years, we have strengthened our collaboration with the globally recognized no-code automation platform "n8n." By combining the convenience of n8n, which allows for intuitive integration with business systems and SaaS, with Agens's natural language understanding and complex task execution capabilities, we are achieving a hybrid of user-friendly and advanced AI workflows in the field. From in-house business development by non-engineers to enterprise-level security compliance, data integration, and governance design, we support the entire process from Proof of Concept (PoC) starting in as little as two weeks to implementation, establishment, and self-sustainability.

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