At its FY2026 Q2 earnings briefing, CAULIS reported substantial increases in revenue to ¥810 million and operating profit to ¥280 million, and announced an upward revision that raised its full-year forecast by approximately 30%. The company positions productivity gains driven by AI and the wider adoption of Grid Data KYC as the second phase of its growth.
In FY2026 Q2, revenue rose 21% year on year to ¥810 million, operating profit increased 27% to ¥280 million, and net income grew 22% to ¥170 million, bringing the operating margin to 34.7%. Productivity gains from the use of AI are driving higher profitability. SG&A expenses declined from the same period a year earlier, and the company continues to pursue a model that improves efficiency without increasing headcount.
At the same time as announcing its results, the company substantially revised its full-year earnings forecast upward. Operating profit and ordinary profit were each raised by approximately 30%, while net income was raised by approximately 22%. The revision reflects progress in new customer acquisition and cross-selling, as well as unspent personnel costs resulting from delays in the hiring plan, while AI-driven efficiency gains are viewed as a structural growth driver.
The key KPI trends show ARR up 21% to ¥1.57 billion, the contract backlog exceeding ¥1 billion, and ARPU rising to ¥278,000. The number of contracted companies, however, declined on a net basis, with 3 cancellations exceeding 2 new contracts. CEO Shimazu (島津) noted that the companies that cancelled made only a limited contribution to ARR and said the impact was limited.
Grid Data KYC is entering its second phase of market expansion. Released last year, the service has been adopted under a full contract by Kawaguchi Shinkin Bank for customer information updates, while Orient Corporation has begun a proof of concept for false-membership checks. Against the backdrop of lower postcard mailing costs, demand among financial institutions for stronger monitoring is expected to support replacement of existing systems.