AI for climate risk intelligence

ClimateNode is a proud member of the Cambridge Institute for Sustainability Leadership's Canopy community of impact-led startups, entrepreneurs and small businesses.

Aims and Principles

AI for climate risk intelligence. ClimateNode is building AI-based tools to systematically scan scientific papers, news articles and reports for granular insights on climate-related hazards (floods, heatwaves, etc.) and their potential or actual impacts on human and natural systems. These include supply chains, companies, assets, infrastructure, production systems, health systems, natural capital, public services and water resource management. ClimateNode is using up-to-the-minute Natural Language Processing tools and techniques (including Large Language Models) in conjunction with a Knowledge Graph to achieve this.

Public benefit outlook. ClimateNode is a not-for-profit and seeks both commercial and non-commercial clients and partners. CN takes as self-evident that risks to human welfare encompass risks to natural capital, health, security and other social and public goods, as well as risks to commercial activities.

Respect for science. There is a need for good quality information which neither exaggerates nor downplays the risks of climate change. ClimateNode aims to treat any scientific research relevant to its work accurately and objectively. However, please note that ClimateNode does not credit itself with or offer scientific expertise.

Multicausal approach. Understanding climate risk often means understanding how climate and non-climate drivers interact. Flooding can be exacerbated by subsidence, deforestation and urbanisation. Drought can be exacerbated by poor water management. Risks can also be dampened by adaptation efforts. ClimateNode seeks to understand the interplay of complex and compounding factors which determine risk by putting physical hazards within the context of human systems.

Get in touch


Helen Jackson is Director of ClimateNode. Helen is an environment and natural resource economist with many years’ experience in climate change, energy and environmental policy and economics, working on projects for multilateral organisations, energy companies and governments. She was one of the first people to work for leading climate and energy consultancy Vivid Economics (now part of McKinsey). She has also worked for green finance pioneers the Climate Bonds Initiative on assessing asset-level climate resilience, as well as for the Economist Intelligence Unit. Originally trained as a physicist, Helen started out expecting to be a climate scientist, picking up her coding skills during space and atmospheric physics research projects as a student. She has an Advanced Diploma in data modelling, incorporating database design, from Oxford University. Her research has been cited by The Rough Guide to Economics and the leaders of both the UK Conservative and Labour parties. linkedin

Dr Elliot Christou is a data scientist with a background in theoretical physics at University College London. He is interested in using artificial intelligence to solve complex real world problems. He provided the initial foundations of ClimateNode's natural language processing capacity as part of the Faculty AI Fellowship programme in autumn 2020. He is now a data scientist at the Connected Places Catapult. linkedin