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AI Solution AIソリューション

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Service Overview

AsiaQuest leverages AI in the most effective way for each client’s business, supporting both enhanced competitiveness and the creation of new value. Utilizing cutting-edge technologies such as generative AI, AI agents, large language models (LLMs), and machine learning, we provide end-to-end support—from planning and design to implementation and operation. Our expertise covers a wide range of use cases, including search systems built on RAG (Retrieval-Augmented Generation) architectures.

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Our Development Approach to AI Solutions

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Three Strengths of AsiaQuest’s AI Solutions title2

  • Exceptional Speed to Full Operation

    AsiaQuest possesses strong development capabilities across both applications and infrastructure. As a systems integrator, we are able to deliver AI implementation seamlessly and rapidly—from planning through to deployment. By leveraging a wide range of system templates from various industries and domains, we can quickly identify and address the initial challenges of AI adoption. This approach enables us to significantly shorten the lead time required to launch AI solutions into full-scale operation.

  • High-Quality AI through Rapid PDCA Cycles

    By utilizing various templates from the early stages of development, we are able to execute PDCA cycles at high speed. This allows us to quickly evaluate PoCs, accurately identify issues that affect accuracy, and implement effective solutions. As a result, during the quality enhancement phase from PoC to full operation, we achieve AI solutions with significantly higher precision.

  • Engineers with Business Insight, Working Together to Find the Optimal Solution

    Our business engineers, well-versed in both our clients’ industries and digital technologies, work side by side with them to ensure the successful introduction of AI solutions. With proven expertise in AI implementation and utilization, our business engineers co-create the optimal solutions by approaching challenges from both business and technology perspectives.

What is a Business Engineer?

Concept Case

Realizing work process management through the database of expert know-how

With a RAG system, non-expert workers on site receive guidance for various issues. By storing the responses and practices of experienced workers in a database, on-site know-how is accumulated, creating an environment where anyone can access the appropriate solutions.

AI-Driven PDCA Dashboard for Retail Staff

Unlike traditional BI tools, there is no need to prepare queries in advance. Staff can extract and analyze a wide range of sales and product information using natural language. AI also proposes insights from the analysis as well as suggested next actions.

Tunnel Non-Destructive Testing

By combining generative AI with machine learning, the condition of tunnels can be assessed, deterioration levels determined, and scored. Even staff without IT expertise can fine-tune the models from the creation stage.