Defining Earth Science AI

Combining established disciplines with innovative scientific methodology



Led by research

At Cervest, Earth Science AI refers to the combination of knowledge and modelling approaches from the proven Earth sciences – including atmospheric science, meteorology, hydrology and agronomy – with the tools of modern artificial intelligence, imaging, machine learning and Bayesian statistics.

This unique approach enables Cervest to simultaneously tie together the interconnected elements that contribute to our planet’s increasingly volatile climate – across multiple regions.




Driven by data

While large sets of data and scientific measurement exist in some parts of the world, they are too vast complex for humans alone to process. Meanwhile, in other regions data is scarce. The challenge we have taken on is to translate the complex data that does exist and generate proprietary data via machine learning, at a commercially viable cost. 

Through the development of our Earth Science AI, we will nurture our planet by helping the decision makers who depend on it to adapt and thrive. 


Our roadmap

Our goal is to accelerate the advent of ‘holistic adaptation decisions for all’, so we can create and maintain a sustainable future for life to thrive. If we don’t create a system that enables interconnected climate and land risk analysis to drive better decisions, we will run out of time to reverse and restore the negative impacts of climate change on our planet.


Here’s how we’re going to get there using Earth Science AI: 



We are creating a dynamic map of the earth, using the best data to understand its relationship with climate, nature and productivity. We are mapping every hectare of land to generate insights that drive more sustainable in-season decisions around climatic and extreme events.



We will incorporate data on the other elements that make up our ecosystem: water, soil, atmosphere, biodiversity and people. We will create a holistic view of the interconnected risks to offer a new level of clarity on decisions related to land-based process and assets. 


The future

There is no ‘Planet B’, so humanity must adapt to survive. Cervest’s adaptation engine, powered by Earth Science AI, will provide the answers to key questions related to the new climate reality. It will empower everyone to make and augment decisions that ensure the resilience of our planet.

Ernesta Baniulyte

Ernesta Baniulyte 
Product Designer

Ernesta has been a full-stack product designer for more than five years. She has valuable experience in the B2B, B2C and B2B2C worlds, and while working at both agencies and product/service companies, she has learned to develop UX research infrastructures to support strategy.

At Cervest, Ernesta contributes to all stages of the product development process – from initial ideation to the exacting detail of UI design – finding new ways to visualise data, and ensure our product is intuitive and user friendly.

Ernesta’s decision to join Cervest was inspired by her desire to make the world a safer, better and more aware place.

Ramani Lachyan 
Junior Research Scientist

Ramani joined Cervest after obtaining her Master’s in Physics from ETH, Zurich. She brings with her valuable experience gained through working on model building and data simulation pertaining to neutrino physics.

Ramani has joined Cervest as a Junior Research Scientist and will be working on creating algorithms that allow for the extraction of physical observables from data from a range of sources.


Lukas Scholtes 
Statistical Scientist

Lukas completed his maths BSc at ETH Zurich, followed by an MSc in statistics at Imperial College. He wrote his MSc thesis in collaboration with Cervest, on the modelling of North American wheat yields via Bayesian parametric and non-parametric methods.

Following an internship in the NGO sector in Bangladesh and a stint in the world of fintech, Lukas comes to Cervest, excited to apply himself to the challenges that are arising as a consequence of unsustainable land-use policies and climate change.

Aidan Coyne
Junior Researcher

Aidan is currently pursuing a Bachelor of Arts and Sciences in Science and Engineering at University College London with a focus on computer science and data informatics.

At Cervest, Aidan is working on researching and assimilating a database of articles categorising the reasons for extreme decreases in crop yields across Europe. The information will be used to help predict the impact of weather events on crop yield and contribute to  Cervest’s ability to bring clarity to decision making around climatic and extreme events.

While studying, she also volunteers with environmental conservation groups and youth engagement programmes.

Jasmine Thompson
Engineering Resident

Jasmine’s background is primarily in Python programming with a focus on data analysis and visualisation.

Since graduating, she has worked on data insights for a London-based dating app startup, helping the company understand the user base and guide new growth. She is now excited to use her skills to help Cervest deliver playback data and useful data analysis and is passionate about the potential of data science, machine learning and visualisation tools.

While studying at Westcliff High School for Girls she was involved in a variety of projects including GUI design for BAE Systems and data collection for a surveillance vehicle project sponsored by Leonardo S.p.A. She was also the Data Analyst for a long-running Southend Youth Council project that advocated for students having better mental health services in school.