CapyMOA
We are New Zealand data and environmental scientists using artificial intelligence to solve some of the biggest environmental issues facing New Zealand.
Datasets and Notebooks
Click on the links to find or share notebooks and datasets.
Find a notebook
Share a notebook
What's coming up?
Stay up to date with our upcoming events.
Latest News
AIRA and PRICAI
Our team are at the AIRA and PRICAI conferences, currently underway in Wellington at the University of Wellington.
We have a big few days lined up with a number of the team giving talks and running workshops and tutorials over the next two days.
Check out our LinkedIn page for regular updates.
October newsletter
In this newsletter, you’ll find:
Delphitech wins global award
Hackathon highlights
Introducing TAIAO Talks
Project Team spotlight
What have we been up to
What’s coming up
Winners of the World Bank Climate Risk Challenge
A big congratulations to Léa Cassé and the DelphiQ team who were recently announced as the winners of the Global Industry Challenge – World Bank track at the Quantum World Congress 2025 for their innovative solution to improving insurance for communities exposed to flooding.
TAIAO Talks
Get the inside scoop on the projects shaping our work. In this new series, our team members share deeper insights into the ideas, challenges, and impact behind the scenes.
This week, dive into CAPYmoa with Heitor Murilo Gomes and discover how it's making waves.
An initiative supported by the Ministry of Business, Innovation and Employment (MBIE), TAIAO is committed to promoting and facilitating the adoption of artificial intelligence (AI) and data science in New Zealand's environmental sector.
Recognising that good data is essential to research, understand, and set policy for effective management of our natural environment, the team at TAIAO are working to develop new machine learning methods that are tailored to process environmental data gathered from our New Zealand context.
TAIAO uses AI models to analyse vast amounts of historical and real-time data, and identify patterns to predict future trends, such as extreme weather events. Through this mahi, we aim to break barriers by enhancing industry capability, and pioneer new machine learning methods to process vast amounts of data in real-time to meet today's pressing demands.
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The University of Waikato
University of Canterbury
The University of Auckland
Victoria University of Wellington
MetService
Beca
