AimHi Earth funding news – Climate and Sustainability Training Provider AimHi Earth secures £1Million in Funding

It provides sustainability teams with the information they need to engage their workforce for the long term and upskills employees at all levels to include sustainability into decision-making. Through the use of data analytics, they enable customers to track staff members' participation in the programmes and provide ways to improve them.

This campaign marks one of the first instances where 7th Generation Shares have been included. A certain proportion of shares are inherited six times before being sold, to ensure investors consider long-term.

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The Climate Planet Foundation, Sam Wisnia, and Nicco Perra, three IT and finance entrepreneurs, are supporting this round. AimHi Earth intends to use this financing to teach workers in many areas to address the climate issue.

The UN Environment Programme, the Eden Project, Nature4Climate, Cambridge Zero at the University of Cambridge, and others provided the firm with its initial funding.

Matthew Shribman, Co-founder and Chief Scientist at AimHi Earth said: “We all want a future with clean air, healthy soil, stable weather and unpolluted water. This is why we're all on the same team when it comes to preventing the climate and nature emergency – everyone wins when we accelerate the evolution of our economy and society to one that's sustainable and regenerative. At AimHi Earth, we know that knowledge is the foundation of progress. That's why we're on a mission to train and upskill hundreds of millions of professionals, to champion and enable circularity, sustainability and operating within planetary boundaries."

About AimHi Earth

AimHi Earth are committed to ensuring that everyone is aware of the entire scope of the climate and natural disaster situation and is inspired to contribute to its resolution. In order to do this, they offer easily accessible and captivating live online climate training and education that is customised for individuals and organisations, supported by data, and executed at scale.