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Scottish Climate Tech Calterra Secures £96k Funding

Graham Turner

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The platform has also been selected for University of Edinburgh’s AI Accelerator.

AI-powered climate-tech platform Calterra has been awarded £96,000 in SMART Grant funding from Scottish Enterprise to develop its technology for monitoring the long-term health of restored peatlands and woodlands.

The 14-month R&D project kicked off in September 2026 and will focus on improving Calterra’s digital monitoring, reporting and verification capabilities, with the aim of making it easier and more cost-effective to track how habitats recover over time.

A joint venture between AI consultancy New Gradient and Caledonian Climate, Calterra uses AI and Earth observation data to support habitat restoration projects.

Much of Calterra’s work to date has focused on the early stages of restoration; it will use the SMART Grant funding to improve its ability to monitor the long-term health of habitats following restoration, working across both peatlands and woodlands.


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Ewan McMillan, Founder and Managing Director of New Gradient, explains: “Most of our work with Calterra so far has been at the start of a restoration project: mapping the land and helping to plan what interventions are needed. This project is about what happens next.

“We want to be able to track the health of peatlands and woodland habitats over the long term, and do that more frequently, more accurately and at a lower cost – giving people greater confidence that restoration is actually delivering what it set out to do.”

The funding comes as Scotland’s new Climate Change Plan has set a target to restore more than 400,000 hectares of peatland by 2040. It also sets out plans for a new Peatland Standard intended to improve consistency and efficiency across restoration, including monitoring and verification.

Calterra is also one of 12 companies selected for Cohort 10 of the University of Edinburgh’s AI Accelerator programme, delivered in partnership with Edinburgh Innovations.

Graham Turner

Sub Editor

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