#Japan #Tokyo #BIPROGY #Serverworks #G-gen

Accelerating AI Transformation: A Strategic Partnership

BIPROGY has entered into a strategic collaboration with Serverworks and G-gen aimed at fast-tracking AI transformation for businesses. This partnership combines BIPROGY's operational expertise with Serverworks' and G-gen's specialized knowledge in AWS and Google Cloud, respectively. Together, they provide an integrated approach to support organizations from conceptualizing AI applications to governance and operational implementation, ensuring AI is embedded in business processes.

Objectives and Background of the Partnership

The BIPROGY Group has long been focused on advancing digital transformation (DX) for its clients, utilizing its strengths in system development and operational capabilities. In today's fast-paced environment, many companies are under pressure to integrate AI into their operations, alongside moving towards cloud technologies and modernization. To achieve sustained business results, it is crucial to comprehensively manage AI adoption from initial conceptualization through to operational governance and organizational adoption.

This partnership enhances BIPROGY's capabilities by fusing its industry knowledge in system development with the cloud and AI expertise of Serverworks and G-gen, enabling a comprehensive support system for clients to effectively utilize cloud and AI solutions.

Overview of the Partnership

1. Business Transformation Utilizing Diverse AI Models
Leveraging AI to drive business outcomes requires more than just efficiency improvements. It necessitates the integration of AI throughout decision-making processes, taking into account specific business challenges and data owned by the organization. This partnership focuses on aiding clients in employing generative AI and AI agents tailored to their industry and business characteristics. Utilizing platforms like Microsoft 365 and Google Workspace, they work to design integrated generative AI models and services, creating an environment where internal knowledge can be effectively utilized.

Specific use cases will focus on sectors such as retail and fieldwork. In the retail sector, they will enhance data utilization frameworks under the concept of