Laboro.AI Inc. Q4 FY2025 earnings call

• Company & Business Overview

  • Laboro.AI was founded in 2016 and listed on the Tokyo Stock Exchange Growth Market in 2023, with 96 employees as of the end of FY2025. Its mission is to create new forms of industry and connect technology and business, positioning itself as an innovation partner for large enterprises rather than a pure AI product seller.
  • Shifted to consolidated financial reporting starting in FY2025 following the acquisition of CAGLA, expanding service coverage to include AI-related system development and data infrastructure in addition to its core custom AI business.

• Core Business Model & Focus Areas

  • Custom AI Solutions is structured into two models: Value Mining (exploring uncharted AI use cases with no existing precedent) and Value Distribution (standardizing proven use cases for rapid horizontal scaling). The company targets the value-up AI theme market, which focuses on driving top-line growth and business model transformation rather than just cost cutting and efficiency improvement.
  • The business focuses on two core technical pillars: generative AI/AI agents and optimization, with particular focus on R&D-intensive industries such as semiconductor manufacturing. It is pursuing a three-stage growth strategy: 1) maintain full-custom AI Solution Design (AI-SD) as the core business for cutting-edge innovation, 2) expand semi-custom Agent Transformation (AGT-X) as a new high-growth service line, 3) explore product/SaaS-style offerings for generative AI and agent capabilities as a medium-term investment.
  • Common platform development for semi-custom services is already well advanced for the generative AI agent space, with technical foundations for semi-custom optimization services also nearing completion.

• Operational Progress in FY2025

  • Achieved stable revenue growth, with the Q4 FY2025 revenue reaching 522 million yen, an all-time high. Customer concentration has decreased gradually, with the top 3 customers accounting for only 29% of total revenue, and growth is driven equally by existing customer retention and new customer additions. The customer base is split roughly 50/50 between R&D manufacturing and consumer/infra industries.
  • Completed M&A and strategic initiatives: acquired CAGLA to enter system development, dissolved the joint venture with GLOVING and shifted to direct business cooperation, which generated special income that pushed net income above the prior forecast. Post-acquisition integration of CAGLA is progressing smoothly.
  • Total headcount reached 96 at year end, slightly below the initial hiring plan, with solution designer hiring falling short of target. Talent development and organizational engagement made strong progress during the period.

1. Custom AI Solutions Segment: Revenue was 1.892 billion yen, operating profit was 0.25 billion yen. It achieved 25% year-over-year revenue growth and 37% year-over-year operating profit growth, contributing 99.6% of total consolidated revenue. 2. System Development Segment (added via acquisition of CAGLA in FY2025): Revenue was 12 million yen, operating loss was 59 million yen. The limited revenue contribution and one-time operating loss were in line with management expectations, as the segment is still in post-acquisition integration with limited project recognition this period.

• For FY2026 (ending September 2026), the company guides consolidated revenue of 2.486 billion yen, operating profit of 0.294 billion yen, and net income of 0.201 billion yen, representing over 30% year-over-year revenue growth.
  • Plans to add approximately 50 new employees in FY2026 to scale organizational capacity, with 10 planned additions for the core solution designer role. More than half of the FY2026 hiring target is already in progress as of the earnings call.
  • Expects the newly added system development business to deliver tangible revenue and profit contributions in FY2026 after completing post-acquisition integration in FY2025.
  • AGT-X semi-custom services are targeted to become the main driver of accelerated growth, with the company aiming to build recurring revenue from platform access charges in the medium term, targeting an roughly 50/50 split between project-based and recurring revenue as an ideal long-term mix.

• Hiring of highly skilled solution designers (which require deep AI expertise and business acumen) has consistently fallen short of plan, which could constrain growth if the hiring challenge continues.
  • Revenue recognition is dependent on project delivery and inspection timelines, and project schedule changes can lead to revenue deferral between periods, resulting in results that miss short-term market expectations (as seen in FY2025 when some revenue shifted to Q1 FY2026).
  • Intensifying competition in the generative AI space could create pricing pressure if the company cannot maintain its differentiated competitive position.

Q: How does Laboro.AI plan to increase the share of recurring/stock-based revenue over time, and what is the target long-term mix of revenue models? / A: Laboro.AI's existing custom AI projects are already long-term, companionate engagements with clients that often continue for multiple years. The company will formalize and grow recurring revenue through its new semi-custom AGT-X line, which will charge for access to its common development platform. Management does not set a fixed quantitative target, but views a roughly 50/50 split between project-based and recurring revenue as the ideal long-term outcome, with ongoing exploration of new models alongside scaling existing businesses.

Q: How does Laboro.AI see the future evolution of AI technology and the industry, and how is it positioned for coming changes? / A: Management expects multiple large waves of AI evolution: after the current generative AI/LLM wave, the next wave will be AI agents (where AI acts as integrated team members within organizations, which is exactly the focus of AGT-X), followed by a third wave of physical AI/robotics. The company is expanding its service lineup to align with these coming industry changes to capture new growth opportunities.

Q: How does Laboro.AI compete in the crowded generative AI space without getting pulled into price competition? What is its core competitive advantage? / A: Success in enterprise AI requires more than just technical AI capability. It requires deep understanding of the client's business, the ability to design custom AI solutions aligned with client needs, and the capability to lead organizational transformation to embed AI effectively. This combination of skills is very rare in the market, and Laboro.AI has already built up a stock of this specialized talent, which serves as its core sustainable competitive advantage.

Q: What is Laboro.AI's hiring strategy, and what types of candidates does it target? / A: The company currently focuses on mid-career hiring, but is considering expanding new graduate hiring over the medium term, especially for engineering roles. It attracts candidates who want to become AI innovation professionals, building new types of roles and driving industry transformation rather than just working on established tasks. The AGT-X team prioritizes business consulting-style backgrounds over deep technical expertise, making it easier to scale hiring faster than for the core solution designer role.