Building AI You Can Trust
LucenAI was established to enable organisations to apply advanced AI capabilities to their own data without compromising security, control, or trust.
Origins
The core technology behind LucenAI originated from research conducted at the University of Derby, where Dr Harry Yu led work in deep learning and applied artificial intelligence. This research highlighted a fundamental limitation in many existing AI tools in that their reliance on moving data into external or public environments, which is often unacceptable for organisations handling sensitive or regulated information.
Validation
These ideas were subsequently proven through a collaborative AI digital transformation initiative between the University of Derby and Bloc Digital. The partnership combined academic research with practical industrial delivery, demonstrating how AI systems could operate securely within organisational boundaries while remaining connected to live data and operational systems. The work also contributed to wider regional objectives around innovation, skills development and applied digital capability.
Foundation
Building on the success of this collaboration, Brian Scanlon, Dr Harry Yu and Trung Bui founded LucenAI to enable other organisations to realise the benefits of AI in a secure, governed and practical way. LucenAI was formed as a university spin-out, with the University of Derby retaining an equity stake and an ongoing role in the company's development.
Partnership
LucenAI continues to work closely with the University of Derby and its academic community, drawing on expertise in computer science, data science and mathematics to develop and validate its AI architecture and models. This ongoing relationship ensures the platform and its modules remains grounded in rigorous research while being shaped by real-world operational requirements.
Today
Today, LucenAI supports organisations seeking to deploy AI within their own environments, on their own data and under clear governance. The platform reflects its origins in applied research and industry collaboration, with a focus on building AI systems that are secure, explainable and fit for use in complex, real-world settings.