Research
Frame the question, test assumptions and understand the evidence.
Who we are
A specialist technology team connecting careful enquiry, strong engineering and the realities of implementation.
Our mission
RSynergy exists to shorten the distance between a worthwhile idea and technology that people can use, evaluate and improve.
That means asking better questions, being candid about uncertainty and keeping research, product thinking and engineering connected.
Our story
RSynergy was founded by Dr Razak Olu-Ajayi, an applied AI researcher and software engineer whose career has moved between academic research, product engineering and complex digital delivery. He holds a PhD in Applied Artificial Intelligence and an MSc in Software Engineering from the University of Hertfordshire.
Dr Razak has published peer-reviewed research in leading Q1 journals and IEEE venues, including IEEE Transactions on Engineering Management, Expert Systems with Applications, Automation in Construction and the Journal of Building Engineering. His work spans applied machine learning, building-energy performance, model reliability and predictive systems, with a consistent focus on turning rigorous research into practical value.
That bridge between research and delivery continues to shape RSynergy. Dr Razak’s experience includes cloud-based machine-learning systems, research-to-product engineering and digital programme delivery in healthcare and other operational settings: work that demands both technical depth and a clear understanding of users, organisations and real-world constraints. His significant contributions to digital technology earned him the “Exceptional Promise (Global Talent)” endorsement from Tech Nation UK, recognising his potential and impact as an emerging technology leader.
Our ambition is to work alongside companies to develop and evolve multiple products across different domains and industries. We bring together the capabilities needed across the product lifecycle—from discovery, research and technical strategy through design, software engineering, testing and release.
Today, our multidisciplinary team is equipped not only to build new digital products and AI-enabled systems, but also to support, maintain and improve them over time. We work collaboratively, stay candid about uncertainty and create technology that clients and their teams can understand, own and continue to develop.
Frame the question, test assumptions and understand the evidence.
Turn credible ideas into robust digital products and systems.
Design around users, governance and long-term ownership.
How we work
A focused team, direct collaboration and decisions grounded in evidence.
Start with the decision, workflow or user need—not a pre-selected tool.
Use evidence and focused technical work to expose important assumptions early.
Account for the people, governance and engineering conditions needed beyond launch.
Research profile
Peer-reviewed work spanning applied machine learning, building performance and AI across the built environment.
Start a conversation
Bring the question, the constraint or the opportunity. The team will help identify a credible next step.