Delivered on May 11, 2026
Transforming store opening strategies based on intuition and experience with AI—"gleasin" envisions DX in store development
Speakers:
Takuto Hashimoto, MD Co., Ltd., gleasin Sales Department Manager, AI Solutions Division Manager
Tamaki Hemmi, gleasin Sales Department
Affiliation and position information is as of the time of distribution
We welcomed Mr. Hashimoto and Mr. Henmi from MD Co., Ltd. to discuss their market area analysis and AI sales forecasting tool, "gleasin." This service, which originated from supporting the development of medical malls, utilizes data such as census and GPS information to support the analysis of potential store locations and sales forecasting. How can store development, which has often relied on intuition and experience, be enhanced with AI and data? We will introduce a wide range of application examples in areas such as food and beverage, fitness, and amusement, as well as future prospects.
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Background of MD Co., Ltd.'s Establishment and Two Business Pillars
MD Co., Ltd. was established in October 2018 and currently has approximately 69 employees. The company operates two main businesses. The first is the medical business, which provides consulting services to doctors and dentists aiming to open their own practices. A key feature is the provision of end-to-end services, including post-opening support, from property acquisition and interior construction direction to the operation of medical malls that attract multiple medical specialties. In particular, the company has a unique strength in attracting clinics to commercial facilities developed by major developers with strong customer drawing power.
The second pillar is the AI Digital Strategy business, to which Mr. Hashimoto and Mr. Itsumi belong. Here, they develop and provide "gleasin," a SaaS product that enables securities analysis and AI-based sales forecasting. This business was born from the belief of CEO Mr. Ito that "the biggest factor in the success of a store is its location." The idea that specialized tools are needed to help doctors open practices in optimal locations has evolved into the current general-purpose store opening support tools.
Functions of gleasin, which supports next-generation store development
gleasin is a SaaS product that began nationwide rollout in March 2025. This tool consists of two main plans. First, the "Basic Plan" has the functionality of a general GIS (Geographic Information System) tool. It visualizes open data such as census data and economic statistics in a user-friendly format, allowing users to instantly grasp the population composition, household attributes, and target residential conditions of an area simply by dropping a pin on the map.
The higher-end model offered is the "AI Sales Forecasting Model." Unlike recent generative AI, this utilizes machine learning-type AI. The AI learns from the customer's past sales data, store opening trends, and store formats. This allows the AI to comprehensively analyze multiple correlated pieces of information that influence sales and calculate with high accuracy how much sales can be expected at a new potential store location. The greatest advantage of AI-driven approaches is its ability to instantly incorporate complex and multifaceted factors into calculations, something that was difficult with conventional Huff model analysis and multiple regression analysis.
Transforming Personalized Experience into "Portable Skills"
One of the major social challenges in store development is the personalization of store opening decisions. From the Showa to the Heisei era, store development heavily relied on the years of experience and intuition of in-house professionals. However, with the aging and retirement of these veterans, the urgent challenge is how to pass on their valuable skills to the next generation. This is because individual skills are difficult to transfer to others and are not easily accumulated within an organization.
MD Corporation aims to create something close to a skill clone by training AI with the experience of these experts, thereby transforming it into "portable skills" for the entire organization. Furthermore, in the current Reiwa era, rapid changes in inbound tourism demand and social conditions mean that past experience alone is no longer sufficient in many situations. By using AI, it becomes possible to incorporate data on the vast changes in the external environment that humans cannot process, enabling the construction of more objective and reproducible store opening strategies.
Transparency in Decision-Making Brought About by Explainable AI
A major feature of the AI model provided by gleasin is its "explainable sales forecast," which is not a black box. Many general AI systems lack transparency regarding the process behind their results, but gleasin's model clearly shows the factors and correlations that underpin sales forecasts.
This allows store development personnel to explain to management, with convincing data, why a particular location is promising for opening a store. This tool is used not only for new store openings but also for renovating existing stores and as a basis for making difficult management decisions such as store closures and relocations. While the final decision on store openings is ultimately made by humans, AI is positioned as a partner that provides the strongest support for that decision, creating tangible success stories.
Application in Diverse Business Models and Future Prospects
Gleasin's applications extend beyond the food and beverage industry to include a wide range of sectors such as Pilates studios, fitness gyms, and amusement facilities. For example, a Pilates company based in Osaka successfully expanded into the Kanto region by using Gleasin's desktop analysis of an unfamiliar area, aligning it with on-site research. Furthermore, an increasing number of companies are utilizing the GPS data (human flow data) included as a standard feature to improve the accuracy of their analysis.
MD Corporation's participation in the LBMA Japan (Large-Based Marketing Association) is precisely to further expand this human flow data and increase the diversity of external data. In the future, they aim to incorporate more advanced location-based business perspectives, such as inbound-specific customer acquisition forecasts and information linked to patient acquisition in the medical field. Their strength lies in their commitment to continuously evolving their tools through information exchange with other companies in the industry, rather than considering the current tool as finished.
MD Corporation's reason for joining the LBMA Japan is precisely to further expand this human flow data and increase the diversity of external data.
Summary
Gleasin, provided by MD Corporation, is a solution that fundamentally changes the way decision-making is done in the retail business. Based on the insights gained from its medical business that "location determines success," its approach of digitizing individualized experience and transforming it into usable skills directly addresses the challenges faced by many companies.
In particular, its transparency as an explainable AI facilitates internal consensus building and supports the construction of a strategic store network. Going forward, it is expected that the company will strengthen its collaboration with external data through communities such as LBMA Japan, and expand its functionality to meet the needs of the times, including inbound tourism support and the construction of more detailed predictive models. As a key success factor in minimizing failures in store openings and creating as many successful stores as possible, the company's AI solution will become the new standard in store development.