EAGLYS

EAGLYS Inc., established in December 2016, is a Tokyo-based firm operating at the intersection of artificial intelligence and data security. The company was founded by CEO Hiroki Imabayashi and Chief Science Officer Yusuke Maruyama. Imabayashi's journey into this field began with an interest in neuroscience at Waseda University, which evolved into a focus on computer science and AI. A pivotal experience in Silicon Valley, where data access restrictions for an AI project highlighted a critical bottleneck, convinced him that data security was a major societal challenge. This led him to pursue research in secure computing upon his return to Japan, authoring numerous papers before deciding entrepreneurship was the best path to solve current business problems.

The company addresses the growing challenge of utilizing sensitive data for digital transformation (DX) and AI-driven insights without compromising security. EAGLYS targets large enterprises in sectors like finance, manufacturing, and infrastructure, which handle significant amounts of confidential or personal data. Its business model centers on providing a secure computing platform and related software solutions, enabling clients to analyze and process data while it remains encrypted—a concept known as "data-in-use" protection. This approach allows for inter-organizational data collaboration and the use of cloud resources without exposing raw information, thereby reducing risks of data leakage and compliance breaches.

The core offering is the DataArmor product suite, which includes DataArmor Gate DB and DataArmor Gate AI. DataArmor Gate DB acts as a proxy for existing databases, ensuring data remains encrypted even during queries and processing, solving the vulnerability of data being exposed in memory. DataArmor Gate AI extends this protection to machine learning, allowing AI models to be encrypted and to make predictions using encrypted data. This facilitates applications like cross-company fraud detection, where organizations can share insights from their combined datasets without revealing sensitive customer information. The platform is delivered as a licensed product for on-premise or cloud deployment and is designed for easy integration into existing systems.

Keywords: secure computing, confidential computing, data security, homomorphic encryption, AI security, encrypted data analysis, data-in-use protection, privacy enhancing technology, machine learning security, DataArmor, Hiroki Imabayashi, Yusuke Maruyama, data collaboration, zero trust security, database encryption, secure query, AI model encryption, financial data security, manufacturing data analytics, infrastructure data management