Climate crisis. Mass Extinction. Apocalypse. Catastrophe. Breakdown. The language we now use around climate change has escalated significantly in 2019, reflecting the seriousness of the challenge humanity now faces.  


Human activity is causing the Sixth Mass Extinction and the headlines are shocking. A biological annihilation of wildlife is threatening to wipe out one million species within decades. Meanwhile, soils are degrading, reducing the productivity of 23% of the Earth’s land surface – and already affecting the food supplies we rely on. More than 12m hectares of forest were destroyed just last year. The amount of carbon in the atmosphere is higher than it has been at any other time during the last 3m years. And global heating could cause the oceans to rise a staggering 6.5 feet by 2100 – swamping territory the size of Western Europe and potentially making 187m people homeless.


While we cannot claim to have evaluated the science in detail here, the trend is very clear – and it’s almost overwhelming. However, business leaders, governments and farmers (as well as consumers) have a responsibility to take the lead on tackling climate change by engaging with every possible opportunity to fix it. And while it might be two minutes to midnight on the Doomsday clock, the good news is we do still have time – and the capability.


Humans and AI: working together 

Humans and intelligent machines have the potential to co-solve what has arguably become the world’s greatest challenge. Indeed, we’ve reached a point where the scale of the problem requires scalable AI.


AI has the power to augment human decisions at the systemic scale needed to protect the future of our planet in the face of climate volatility. It can support everything from biodiversity and carbon capture to business growth and sustainability, feeding into decisions on crops, land development, insurance and credit – and help the 80% of enterprises expecting climate change to result in major changes to their business.


As an AI-first ClimateTech business, we are building a next-generation platform to support critical decisions. Our scientific framework, rooted in data and computational statistics will make it possible to pool data from all corners of the earth and then use that data to monitor, model and forecast land productivity. Analysing multiple crops, geographies, soil and water, at a personalised level and on a scale that is beyond human capabilities, it will also enable us to feed signals directly into climate smart decisions.


The power of billions of good decisions

Humans have unwittingly made billions of bad climate decisions in the past. But thanks to science we are now able to make billions of good ones – enabled by a scientific approach at scale: in business, in government and on the ground. 


As Neil deGrasse Tyson has said: “The Universe is under no obligation to make sense to you.”


Cervest’s role is to help you make sense of it, through personalised climate signals.


Photography is by Kazuend on Unsplash.


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.

Stoyan Binev
Junior Software Engineer

Stoyan is a BSc student at King’s College London with two years’ experience in software engineering.

With experience working for Amazon and Google as a software engineer, as well as for a fintech start-up, Stoyan was inspired to join Cervest’s by its planet-wide scale and the opportunity to make a positive impact in the world.

He is currently finishing his degree and dissertation while also specialising in data processing at Cervest.

Agnes Schim van der Loeff
Policy Researcher

Agnes joined Cervest after completing her BA in Arabic and Development Studies from SOAS University of London. She is interested in the intersection of the social, economic and political dimensions of climate change and passionate about climate justice. During her studies she was also engaged in environmental activism, including as environment officer in the SOAS students’ union.

Agnes started at Cervest as a research resident exploring the ethical implications of AI in relation to climate change, which resulted in a paper selected for an oral presentation at the NeurIPS 2019 workshop on AI for social good. Building on this, she is developing an ethical framework for Cervest. As policy researcher she now does research on the regulatory context of Cervest’s work and on emerging policies relating to climate change. 

Kate Chkhaidze
Machine Learning Scientist

Kate joined Cervest after completing her PhD study at the Institute of Cancer Research, University of London. Her Project was on statistical and computational modelling of cancer evolution. Her educational background is in pure mathematics (BSc – Tbilisi State University) and statistics (MSc – Imperial College London). Before deciding to study for a PhD, she worked as a junior analyst/developer at the Bank of Georgia and in parallel was giving lectures in Statistics to undergraduate students in Tbilisi for almost two years.

At Cervest, she will be working as a Machine Learning Scientist on crop classification problems. She loves the mission and goal of the company and is very excited to be a part of the process of achieving it.