EnergyWith Co., Ltd., after introducing its generation AI in January 2025, calculated that it could increase productivity by up to 7,000 hours per month (approximately 35 hours per person) after one year. The effects are not limited to increased productivity, but have also manifested as multiple achievements, such as securing patent rights for related technologies and developing new services.
- Simplifying the effectiveness simulation of renewable energy storage systems and turning it into a sales tool.
- We analyze the business macros scattered throughout the company to avoid black boxing and consolidate/integrate them.
- We will build a database of subsidies related to energy conservation and business continuity planning (BCP) and turn it into a support service for customers.
However, only a small fraction of use cases directly led to results. To identify which applications lead to results and to popularize them as reproducible techniques, a data-driven approach that analyzes all usage logs is promising. Over one year, the input and output logs accumulated from operations involving 120 people amounted to 150,000 round trips and 540 million characters—a massive amount of text data equivalent to 7,000 paperback books . To achieve both contextual analysis and evaluation, high-resolution visualization from this vast amount of data, and to ensure objectivity in visualization methods that are inherently subjective, we collaboratively utilized generative AI and JMP to extract usage challenges and hidden best practices.
