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  6. [Data] How to Implement Generative AI in Business Operations Beyond Just a Proof of Concept

[Data] How to Implement Generative AI in Business Operations Beyond Just a Proof of Concept

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last updated:May 19, 2025

homula
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We provide comprehensive guidance from selecting the LLM, preparing data, forming teams, to executing the PoC.

This document provides a detailed explanation of a comprehensive framework for maximizing the potential of AI and effectively transitioning from Proof of Concept (PoC) to a production environment. It addresses the challenges of AI implementation, including the lack of standardized processes, the absence of appropriate tools, and the underdeveloped automated pipelines. If you are considering implementation, please take a moment to read it. 【Contents (Excerpt)】 ■ Introduction to Generative AI Implementation Support Services ■ Challenges in AI Implementation ■ Evals: Accurately Measuring LLM Performance ■ RAG (Retrieval-Augmented Generation): Effectively Integrating Advanced External Knowledge *For more details, please download the PDF or feel free to contact us.

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[Data] How to Implement Generative AI in Business Operations Beyond Just a Proof of Concept

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スクリーンショット 2025-05-16 104051.png
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【Other Publication Contents (Excerpt)】 ■Fine-tuning: Improving performance in specific tasks or domains ■Temporary data storage and simplification of processing: Enhancing response speed and reducing costs ■Trust and Guardrails: Ensuring output quality and reliability ■Human+AI UX: Providing appropriate explanations and error handling ■Collect user feedback: Building a data flywheel ■AI Agents: Breaking down complex goals into a series of tasks *For more details, please download the PDF or feel free to contact us.

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[Information] How to Implement Generative AI in Actual Business Operations Beyond Just a Proof of Concept

[Information] How to Implement Generative AI in Actual Business Operations Beyond Just a Proof of Concept

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homula

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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