5582.T

• Overall Financial Performance

  • The first half total revenue was 1.315 billion yen, operating profit was 278 million yen, ordinary profit was 282 million yen, and net income was 186 million yen. All metrics increased significantly year-over-year. Revenue met plan, while profit is progressing ahead of schedule.
  • YoY operating profit growth: Compared to 62 million yen operating profit in the prior year first half, flow-type revenue contributed 322 million yen growth and stock-type revenue contributed 102 million yen growth. Growth in cost of goods sold and SG&A was relatively limited, leading to a large overall increase in profit.
  • Key performance metrics: Revenue growth rate hit 47.7%, operating margin reached 21.1%, average customer revenue rose to 40.3 million yen. The number of clients is growing gradually in line with the company's strategy of focused support for infrastructure clients, rather than rapid large-scale expansion.

• Business & Operational Trends

  • AI business revenue is shifting from the historical pattern of heavy concentration in the second half to a more levelized trend, with relatively even revenue distribution in the first half of this fiscal year.
  • For energy storage facility development in the energy management segment, partial revenue was recognized upfront in Q1 and Q2, and these projects are expected to gradually contribute to earnings in the second half, remaining on plan overall.
  • Order trends align with historical seasonal patterns common for infrastructure-focused transactions. Outstanding orders are flat due to a trend of shorter project delivery cycles and faster timing from order receipt to revenue recognition.
  • The number of AI projects is gradually increasing, and the company has built out sufficient internal capacity to handle the growing volume. Both flow-type and stock-type revenue have seen rising average customer unit prices, enabling efficient development progress alongside growth in project count and unit price.
  • Workforce expansion: The company has gradually increased headcount, with a specific focus on strengthening sales and consulting divisions (in addition to engineering) this fiscal year. Productivity has not declined significantly and remains stable at historical levels. The company intentionally keeps average paid utilization moderate to reserve time for future technology development, balancing short-term revenue generation with long-term R&D investment.

• Recent Product & Operational Milestones

  • Launched functional expansion development for ReNom Railway in the railway sector.
  • Completed deployment of a new AI ship routing optimization system for Tokuyama, and has started full-scale commercial operation.
  • Announced the launch of GeNom, an industry-specific generative AI built for the power sector.

• Full-year revenue and profit guidance remains unchanged from the original initial plan. Management will continue operations in the second half to achieve the original plan as scheduled.
• The company manages overall revenue and profit on a full-year basis rather than focusing strictly on quarterly targets. Quarterly short-term revenue and profit fluctuations are expected as project timing varies, but overall full-year targets remain on track.

By industry domain (absolute amounts and revenue contribution %):

• Power sector: 6.81 billion yen, 51.9%
• Manufacturing & Logistics sector: 2.06 billion yen, 15.7%
• Urban & Transportation sector: 3.04 billion yen, 23.2% (the new railway business within this segment has launched and contributed to earnings)
• New Energy Management sector: 0.80 billion yen, 6.1%

By AI revenue type:

• Flow-type revenue: 885 million yen, showing steady year-over-year growth
• Stock-type revenue: 349 million yen, also showing steady year-over-year growth; stock-type revenue accounted for 26.6% of total revenue, consistent with historical levels

The primary stated challenge the company faces as it scales is organizational: as the company grows in size, it must transition from relying on individual capabilities to building unified, organization-wide operational capacity. This includes aligning the entire expanded organization around shared strategic goals, implementing consistent and reliable profit management, maintaining efficient development workflows without compromising customer experience, and building overall corporate competitiveness that does not depend solely on individual performance. No other material operational or financial risks were explicitly discussed.

Q: The Q3 and Q4 operating profit forecast is lower than the initial plan at the start of the fiscal year. Could you explain the reason, and are there any new increasing expenses?

A: We manage overall revenue and profit on a full-year basis rather than focusing on quarterly targets. Short-term quarterly fluctuations in earnings can occur due to project timing, and some earnings may be pulled forward into earlier quarters based on project needs. We are still controlling overall performance on track to achieve the original full-year revenue and profit plan as scheduled.

Q: What are the key expectations for GeNom?

A: We have a long history of developing machine learning and AI solutions, and have conducted ongoing R&D since generative AI emerged. We developed GeNom because we saw an opportunity to deliver standalone value to clients with a generative AI tailored to industry needs. The power sector faces constant changes to operations to comply with updated regulations and government policies, with large volumes of new regulatory documents and policy materials released constantly. Power companies spend significant time reviewing these materials to update their internal policies, and GeNom is designed to reduce review time while enabling more sophisticated policy analysis for these clients. As an industry-specific generative AI, we place extreme priority on output accuracy. We built the system with robust hallucination mitigation, guaranteed access to source and primary data, and clear citation of the underlying information for every output. GeNom has been pre-released to a limited number of power sector clients, and has received very positive early feedback from these early users. We plan to expand access to more clients going forward to gradually grow this new business line.

Q: Could you provide an update on quantum computer R&D progress?

A: We have conducted foundational quantum computing research since around 2017, and have gradually shifted to application-focused development starting in 2024-2025. As quantum hardware has advanced, with qubit counts increasing steadily, it has become increasingly plausible that quantum computing will reach real-world social implementation, justifying this shift to applied R&D. Our core business is planning and operations for social infrastructure, so we are focusing our quantum circuit development on applications for this domain, specifically targeting power sector planning use cases. Infrastructure companies face major challenges planning operations amid uncertainty, and we are developing methods to address this problem with quantum computing, building corresponding quantum circuits and pursuing patent protection for our work. Our internal research team is advancing this work, and we are also collaborating with an automotive company on co-development of new algorithms, with our team working directly with the client to advance R&D. We will continue R&D with the goal of having our algorithms and quantum circuits ready to deploy when quantum computing reaches broad commercial social implementation. We are also holding a seminar on quantum computing trends tomorrow.

Q: The company is growing very smoothly, but what do you see as your key challenges going forward?

A: Historically, we worked on complex problems with very long project delivery cycles, taking significant time to deliver each project. As our organization has scaled, we have become more efficient, delivery cycles have shortened, and we can deliver value to clients much faster, which is a major change from just a few years ago. The main challenge going forward is organizational: as we scale our team, we need to move beyond relying on individual expertise and build a cohesive organization that can compete as a unified entity. We need to align our entire expanded organization around shared goals, implement robust profit management, maintain efficient development without causing issues for clients, and transition to competing based on overall organizational capability rather than just individual performance. Growing as an organization while addressing this challenge is our current priority, and we are working to tackle this to enable further company growth.