Model how work is accomplished
Functional System Modelling reveals the activities, dependencies and conditions through which real systems produce both successful and unwanted outcomes.
Cambrensis develops practical methods and AI-supported applications for understanding how safety-critical systems work, vary and adapt.
Cambrensis brings together systems thinking, quantitative analysis and operational evidence. We develop methods, working models and research partnerships that help people examine complex sociotechnical systems with greater clarity.
Functional System Modelling reveals the activities, dependencies and conditions through which real systems produce both successful and unwanted outcomes.
We develop transparent analyses that connect functions, operational data, assumptions and simulation to test how system behaviour changes across conditions.
Structured investigation combines evidence, functional modelling and disciplined inquiry to explain what happened, how it emerged and why existing controls did not resolve it.
We design governed AI-supported tools that help analysts assemble evidence, build models, explore scenarios and retain an auditable line from source to conclusion.
Our work concentrates on settings in which performance emerges from interactions between people, technology, organisation, information and changing operational conditions.
Patient flow, bed occupancy, clinical work, incident investigation and the resilience of services under pressure.
Functional interpretation of flight data, actual-versus-expected performance and evidence-led examination of operational events.
Functional HAZOP, barrier performance, plant operations and quantitative exploration of how deviations propagate through complex systems.
FRAIXL connects data from different sources to a functional model of how the system works. It helps users see why changes matter, how effects propagate and where recovery or intervention may be possible.
FRAIXL is being developed as a governed agentic AI workbench. Its agents help analysts organise evidence, build and refine functional models, map operational data and examine results from controlled analyses. Analysts review proposed models, assumptions and findings, while supporting evidence and analysis history are retained.
We are developing the same core approach for healthcare, flight-data analysis and process industries.
Selected supervised trials will test how well people outside the development team can use the workbench.
Discuss a supervised research trial FRAIXL is a trade mark applied for by Cambrensis Ltd. UK application UK00004446658.Cambrensis convenes the combination of operational, academic, technical and domain expertise that complex safety questions require.
We are exploring research consortia in three areas: healthcare systems, flight-data analysis and process industries. Each would bring operational evidence together with a functional model to examine how the system performs. We welcome interest from researchers, practitioners and organisations with relevant questions, expertise or suitable data.
Express your interest ↗We organise focused events that bring researchers, practitioners, regulators and technology partners together to examine methods, cases and emerging applications.
Our papers, working notes and essays explore the foundations, limitations and practical development of safety science.
From systems thinking, SEIPS and FRAM towards executable functional models.
Open paper → AI & risk · Jul 2026Can governed AI and explicit evidence restore confidence in quantitative risk assessment?
Open paper → Perspective · Jul 2026A personal view of the field from someone who was there at the beginning.
Open essay →We welcome conversations with research partners, safety practitioners, universities, healthcare organisations, aviation specialists and process-industry teams.
info@cambrensis.org