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  6. Case Study: Data Utilization through Semantic Search | Major Office Products Company

Case Study: Data Utilization through Semantic Search | Major Office Products Company

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last updated:Mar 13, 2025

homula
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A case study of introducing an agent that automatically generates analysis queries!

We would like to introduce a case study where "generative AI" was implemented in the planning operations of a major company dealing with office-related products. The company faced the challenge of insufficient organization of a large amount of internal data, leading to decreased analysis efficiency. To address this, they implemented data documentation and semantic search. This significantly improved the transparency of data utilization and analysis efficiency. 【Case Overview】 ■Challenges - Insufficient organization of a large amount of internal data leading to decreased analysis efficiency - Lack of clarity on where data is located, hindering planning operations ■Results - Significant improvement in the transparency of data utilization and analysis efficiency *For more details, please refer to the related links or feel free to contact us.

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Case Study: Data Utilization through Semantic Search | Major Office Products Company

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Case Studies of Generative AI Utilization

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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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