NEWS21 February 2024

Funding for Climate Policy Radar to expand data platform

AI News Sustainability Technology UK

UK – London-based Climate Policy Radar, a startup that uses data science and machine learning to analyse climate policies, has raised over $6.8m in funding.

laptop with CO2, car and leaf graphics floating above typing hands

The funding, secured in the last months of 2023, will bolster the organisation’s aims to organise and analyse data on global climate law and policy.

Founded in 2021, Climate Policy Radar’s AI-based platform allows users to search through a database of around 6,000 documents, including national climate laws, policies and United Nations Framework Convention on Climate Change submissions from national governments. The platform has around 350,000 users from 100 countries, according to the company.

Data within the platform is sourced in collaboration with the Grantham Research Institute on Climate Change and the Environment at LSE.

The recent financial backing came from the Environmental Defence Fund,, Open Society Foundations, The Patrick J. McGovern Foundation, Sequoia Climate Foundation, Schmidt Futures and Quadrature Climate Foundation.

Climate Policy Radar will use the funding to expand its scope of available data by adding more documents, including sub-national policies, climate-related litigation cases and corporate disclosures.

It also plans to continue its work on turning its body of textual data into structured data, and develop tools to synthesise it, including using generative AI to help answer questions.

The company also said it would expand its partnerships, including convening a network of climate natural language processing researchers and practitioners.

Climate Policy Radar said in a statement: “Running through all these pillars is our deep commitment to equality and justice – ensuring the needs and voices of the people who contribute the least but are most impacted by the climate crisis are well-represented in our methodology, tools, data sets, and stakeholder engagement.

“Apart from making our tools and datasets free and open, this also includes correcting and preempting biases in data and our machine learning models. We take seriously our responsibility in providing climate data, our eyes wide open not only to the opportunities but also to the risks of applying AI to these sensitive data and use cases.”