Laboro.AI Inc. Q2 FY2025 earnings call

Strategic Focus

• The company prioritizes value-up AI themes, which focus on using AI to help clients create new products/services, transform business models, and increase enterprise value, rather than only focusing on cost-cutting and operational efficiency. The domestic value-up AI market is projected to grow to several hundred billion yen.
• The core competitive advantage is the team of Solution Designers, who have deep expertise in both cutting-edge AI technology and business new product/service development, enabling the company to tackle high-complexity value-up projects that few other competitors can deliver.
• The two-cycle business model: Value Mining explores new unaddressed AI themes to build custom solutions from scratch, while Value Distribution scales delivery by reusing accumulated technical know-how from past projects, creating an efficient growth loop. Generative AI/LLM expertise accumulated through early exploration is an example of this model in action.

Operational Progress

• Customer base expansion: Both new and existing customers grew on plan. The joint venture X-AI.Labo with Gloving is progressing well in acquiring new customers for non-organic growth.
• Organizational development: Total headcount reached 88 employees as of the end of March. Engineer and corporate teams expanded smoothly, and onboarding/employee engagement initiatives have improved significantly with structured documentation, phased integration, and multi-mentor support systems implemented.
• First M&A completed: In March, the company completed the acquisition of CAGLA, a firm with unique graph database technology and a strong customer base in the manufacturing sector centered around Toyota Motor, which creates strong complementary synergy in data infrastructure and client coverage.

Laboro.AI operates a single core segment: Custom AI Solutions, which includes two service delivery models: Value Mining (VM) for new custom AI projects and Value Distribution (VD) for scaled projects leveraging accumulated technical know-how. For the second quarter cumulative period: total revenue is 979 million yen (0.979 billion yen), up 37% year-over-year; gross profit is 679 million yen (0.679 billion yen), up more than 40% year-over-year; operating profit is 205 million yen (0.205 billion yen), up 205% year-over-year. The customer base is split approximately 50% between Research & Development-focused (manufacturing upstream) industries and 50% Social Infrastructure/Consumer-facing industries, maintaining a balanced split. Both existing and new customer revenue grew in line with expectations: 6 new customers were acquired in the first half, 4 of which were acquired in the second quarter.

• Management maintains the original full-year 2025 September fiscal year performance guidance, with no upward or downward revision. The second quarter cumulative revenue reached 49% of the full-year target, and operating profit reached 82% of the full-year target, which is ahead of the original plan.
• A new full-year consolidated guidance will be reviewed and re-disclosed after CAGLA joins the group in the third quarter of 2025.
• Medium-term growth target is to outpace the growth of the overall AI market, building on the foundation established in 2024 (post-listing phase 1) to achieve steady organic growth while exploring opportunities for discontinuous growth via M&A and partnerships.

• Hiring of Solution Designers, the company's core critical role, is significantly behind plan due to the high skill requirement (combining AI and business development expertise) and low acceptance rate of job offers. Hiring has higher difficulty and slower progress than originally projected, which may constrain near-term growth capacity.
• Value-up AI projects are inherently high complexity, with higher execution risk than standard efficiency-focused AI projects, requiring sustained investment in specialized talent and capabilities.

Q: Are there any similar companies focused on value-up AI business models internationally, and what is Laboro.AI's unique positioning? / A: Western markets have a different industry structure: large technology consulting firms like Accenture or McKinsey do strategy work for value-up transformation, but rarely handle end-to-end cutting-edge AI implementation. Product AI firms typically only deliver pre-built solutions rather than end-to-end transformation support. This structure creates a unique space for Laboro.AI, which combines both AI technical implementation and business transformation expertise, a combination that is unique globally as well as in Japan. Laboro.AI is currently focused on the domestic market but may explore global opportunities long-term.

Q: What is the bottleneck for slow Solution Designer hiring, and what steps is management taking to improve it? / A: Applicant inflow has increased significantly this period, so lack of candidates is no longer the main issue. The main bottlenecks are twofold: first, the role requires very specialized combined skills, so the company has tightened screening standards to ensure candidates can succeed, which limits the number of offers extended. Second, offer acceptance rates remain lower than desired. Management is working to improve acceptance rates by better communicating Laboro.AI's unique positioning and the long-term career growth value of the Solution Designer role at the firm.

Q: Who are Laboro.AI's main competitors, and what is the company's competitive advantage against them? / A: The main domestic competitors are other listed AI startups including PKSHA Technology, ABEJA, Exawizards, JDSC, and Ridge-i. Laboro.AI has a clear positioning difference: these firms focus on other AI segments, while Laboro.AI is exclusively focused on value-up AI for business model transformation and new business creation. Against global consulting firms, Laboro.AI differentiates itself by having an in-house team of machine learning engineers and deep expertise in end-to-end AI technology implementation, which most pure strategy consulting firms do not have.