Japan Data Science Consortium Co. Ltd.

Business Details

This segment leverages data science, machine learning, and AI to conduct Joint R&D with leading companies in each industry. It adopts a business model that creates and productizes AI solutions addressing common industry challenges, then deploys them horizontally to generate recurring revenue. Revenue is built on a two-layer structure combining flow-type revenue (quasi-delegated service provision) and stock-type revenue (operation and maintenance fees, license usage fees, consortium membership fees, etc.). The company retains ownership of AI algorithms, creating an entry barrier whose precision improves as the number of client companies increases.

Recent Overview

Robust AI demand drove segment revenue up 54.7% year on year, with substantial growth in both revenue and profit

For the cumulative nine months of FY2026 (ending June 2026), AI Solutions Business revenue was ¥3,163 million (up 54.7% year on year), and segment profit was ¥360 million (up 24.1% year on year), marking growth in both revenue and profit. Robust AI demand contributed to new customer acquisition and upselling to existing customers. The number of full-time employees reached 194 at the end of Q3, with over 220 expected by fiscal year-end, indicating organizational expansion progressing beyond the initial plan. Cost control through in-housing of outsourced work continues to be pursued.

Key Products

Growth Drivers

• Robust demand driven by the rapid expansion of corporate AI investment (increase in projects related to AI agent and LLM utilization themes)
• Revenue expansion through new customer acquisition and upselling to existing customers
• Gross margin improvement effect from an increasing number of AI solution horizontal deployment cases
• Strengthening of organizational structure through active recruitment and training (194 full-time employees at end of Q3 FY2026 ending June 2026, with over 220 expected by fiscal year-end)
• Strengthening of entry barriers through accumulation of industry-specific data and algorithms via long-term partnerships (Joint R&D) with major companies
• Accelerating initiatives in cutting-edge AI domains such as AI agent development and physical AI

Risks

• Risk of costs preceding revenue due to increased personnel recruitment and training costs (continued increase in recruitment expenses, bonus provisions, and other personnel-related costs)
• Risk of revenue fluctuation due to delays or losses in acquiring AI solution development projects
• Risk of dependence on specific major partner companies (revenue from a single customer is less than 10% of consolidated revenue)
• Risk of obsolescence of existing AI algorithms amid accelerating technological innovation
• Risk of temporary instability in cost structure during the transition of outsourcing expenses to in-house operations
• Risk of increased fixed costs, such as office expansion expenses, associated with organizational growth