NaU Data Lab Inc.

NaU Data Lab Inc. (株式会社なうデータ研究所) is a Japanese software company headquartered in Iizuka, Fukuoka, founded on 1 November 1996. The company is best known for its business rule engine "NaU DSP," which centralizes organizational business knowledge and uses three inference functions—forward judgment, backward judgment, and proposal-type judgment—to automate explainable decision-making. The engine is positioned as a form of explainable, human-collaborative AI that turns tacit operational rules into a durable organizational asset. The company traces its intellectual roots to the guidance of the late Professor Isao Nagasawa and Professor Masanobu Umeda of the Faculty of Computer Science and Systems Engineering at Kyushu Institute of Technology, with whom NaU Data Lab has maintained industry-academia collaboration. Since its founding, NaU DSP has been applied to a wide range of systems, including health checkup systems, customer management systems, public-sector systems, manufacturing support systems, energy management systems, and automated personnel assignment systems. NaU Data Lab serves major Japanese clients such as Fujitsu, NTT Docomo, and Nippon Airport Techno, and its case studies include large-scale customer information management for NTT Docomo, an application document checking system for Waseda University combining AI-OCR with the rule engine, and a technical information leakage prevention and monitoring system for a major precision machinery manufacturer. The company is privately held with capital of 25 million yen and 41 employees as of May 2026. Its leadership includes Representative Director and President Tsuyoshi Tsuruzaki, Directors Keita Yamaguchi and Kunihiro Ono. The corporate logo features a pill bug (dangomushi), symbolizing the company's aspiration to be an unseen but essential supporter of customers' business knowledge infrastructure.

NaU Data Lab Inc. was founded on 1 November 1996 in Iizuka, Fukuoka, Japan. The company's origins are closely tied to the Faculty of Computer Science and Systems Engineering at Kyushu Institute of Technology, where the late Professor Isao Nagasawa and Professor Masanobu Umeda provided academic guidance that shaped the company's approach to rule-based systems. Since its founding, NaU Data Lab has focused on developing and applying its business rule engine, NaU DSP, which was created through industry-academia collaboration with Kyushu Institute of Technology. The company's core technology, NaU DSP, is a rule engine designed to capture and manage business knowledge as an organizational asset. It features three inference functions—forward judgment, backward judgment, and proposal-type judgment—along with flexible content management capabilities. This allows it to function as explainable AI that automates decision-making based on business knowledge. Over the years, NaU DSP has been deployed in diverse domains, including health checkup systems, customer management systems, public systems, manufacturing support systems, energy management systems, and automated personnel assignment systems. By the 2020s, NaU Data Lab had established relationships with major Japanese corporations and institutions. Notable implementations include a large-scale customer information management system for NTT Docomo, an application document checking system for Waseda University that integrates AI-OCR with the rule engine, and a technical information leakage prevention and monitoring system for a major precision machinery manufacturer. The company marked its 25th anniversary on 1 November 2021. In October 2024, it began joint research with Ehime University, and it continues to sponsor local technology initiatives such as the e-ZUKA Smart App Contest. As of May 2026, the company reported 41 employees and capital of 25 million yen, and it remains privately held.

• Company founded in Iizuka, Fukuoka, Japan

• Celebrated 25th anniversary

• Started joint research with Ehime University

• Sponsored e-ZUKA Smart App Contest 2024

Explainable, human-collaborative AI through a business rule engine that turns organizational knowledge into a competitive asset.

• NaU DSP

  Business rule engine with three inference functions (forward, backward, proposal-type) for explainable decision automation.

1. 1株式会社なうデータ研究所nau.co.jp
2. 2企業情報 | なうデータ研究所nau.co.jp
3. 3NAU DATA Institute Inc. (Japan) - Wikidatawikidata.org