Empirisys is an organisation with extensive backgrounds in driving tangible advancements in process safety performance. Our founders bring to the forefront a wealth of knowledge in both process safety and data science that has been pivotal in shaping our mission.

At Empirisys, we work with high-hazard organisation across diverse sectors employing innovative data science solutions to unlock the power hidden within your organisation’s data. Our vision revolves around the core belief that transforming organisational culture is at the heart of fostering the conditions necessary for creating safer, more productive, and environmentally responsible businesses that, in turn, lead to greater sustainability. All of this is made possible through a data-driven approach.

Empirisys employs a comprehensive three-step process to uncover and analyse concealed data within your operational and organisational systems. First, our approach involves discovering and analysing hidden operational and structured data from your systems, shedding light on vital insights. This data analysis is then transformed into actionable knowledge through data science and machine learning leading to valuable insights. The culmination of this process yields data products, powered by AI-driven applications and tools, which enhance and improve various facets of your operations. From elevated process safety and asset reliability to the cultivation of an enhanced safety culture and leadership, our process paves the way for meaningful enhancements in performance.

Our clients are the cornerstone of our achievements, and we take immense pride in attracting those who recognise the true value of insights, intuition, and expert-led data analysis. They rely on Empirisys to provide guidance in making pivotal decisions, valuing our unique combination of analytical skills, process design, data science, and engineering Knowledge. Our clients not only choose to work with us but continue to do so because of the demonstrable impact we consistently make on their businesses.