Machine learning for Planet Earth

Planet Earth is a complex ‘system’. Understanding risks and forecasting trends involves the fusion of multiple sciences and the modelling of dynamic natural systems. Our scientists have combined cutting-edge machine learning methods and algorithmic design to do just that.

Multi-Crop Machine Learning (MCML)


We have developed our own state-of-the-art Bayesian statistical methodology that allows us to make sense of large volumes of space-time data from a wide variety of sources, from satellites to farms.

Whether you’re a crop science company, a grower, CPG company, or a policymaker, our MCML platform provides deeply personalised crop prescriptions, generated to simultaneously safeguard your business and our planet. MCML powers our three pioneering products – DecisionVest, FarmVest, and CODEX – all purpose-built for your needs.

Core elements

Our software combines predictive and self-learning capabilities to enable you to better manage risk by making science-powered decisions about how to adapt for the future – days, weeks, months or years in advance.

Any crop. Any time. Anywhere

We simulate, in silico, land performance, from soil to sky, across space and time, with unprecedented precision irrespective of location – without the need for in-situ devices.

Exponential learning

Our platform simultaneously learns across millions of hectares, multiple crops, and ecosystems around the world – and with each new data point and simulation, its capability grows exponentially.

Automated & real-time analysis

We automate personalised risk analysis from bioclimatic, biophysical and image data, supporting sourcing and land-based decisions today and simulating the future for science-based adaptation.

Optimising for data scarcity

We draw data from the planet’s most trusted sources, so where your data might be limited or uncertain, our pioneering algorithms are able to optimise for data scarcity.

Best-fit adaption choices

Our machine learning technique can tell you what is happening and what will happen but also, crucially, what to do about it – helping you to secure future supplies and protect Earth’s natural capital.

André DuBuisson 
Chief Product Officer

Andre is a product specialist with 16 years’ experience delivering and growing global B2C / B2B products and Marketplaces across multiple sectors.

He’s successfully serviced diverse clients in product management, business analysis, UX and consulting. Recent engagements have included the innovative use of data science & technology in dynamic marketplaces and developing a large-scale customer engagement platform.

He has previously held product leadership positions at Victor Limited and Collinson Group, developing customer loyalty solutions for well-known international brands.

Ruiao Hu
Research Resident

A computer scientist by trade and a mathematician at heart, Ruiao graduated from Imperial College London with an MEng degree in Joint Mathematics and Computer Science.

With industry experience in data engineering gained with world-leading finance firms, Ruiao has joined Cervest for the summer to construct data pipelines for a number of our upcoming projects.

Just as he joined Cervest, Ruiao achieved a first class MEng degree with the Governor’s Prize and Corporate Partnership Programme award for his final year project. After his time at Cervest he will pursue a PhD in stochastic geometric mechanics under the supervision of Prof Darryl Holm at Imperial College London.

James Walsh
Research Resident

James is a Statistical Scientist with a bachelor’s degree in the subject awarded from the Statistics department at the University of Warwick.

James joins Cervest as part of his work with the Warwick Manufacturing Group and The Alan Turing Institute where he is a Research Assistant developing Physically Informed Hybrid models.

He will be spending his time at Cervest applying this expertise to simulating individual crop growth and constructing bulk processing technologies for modelling organic carbon content for soil quality monitoring. He has also worked in the risk team of financial consultants at Albourne Partners building simulations.

Mike Zotov
Research Resident

Mike has recently graduated with a first class honours degree in Mathematics from the University of Warwick.

Having studied Machine Learning as part of his degree, he has joined Cervest for the summer to work on deep generative models for de-noising remote-sensing data.

After his time at Cervest he will continue to pursue his passion for Machine Learning with a Master’s degree at Imperial College London.

Anna Moses
Business Process Lead

Anna has broad experience helping organisations to define and operationalise their processes in order to achieve ambitious business objectives.

Anna has worked across the public, private, and charity sectors with a focus on organisational transformation through business analysis and behavioural science-focused change management, at organisations including the UK House of Commons, the Parliamentary Digital Service and leading US healthcare consultancy The Advisory Board Company.

Inspired by Cervest’s commitment to using technology for good, through both the delivery of game-changing products and an inclusive working environment, Anna is passionate about being part of the solution to the climate crisis.

She has a BA in Political Science and History from Wellesley College, Massachusetts, and also attended the Massachusetts Institute of Technology.

Michael Griffiths
Senior Engineer

Michael has been building software for over a decade as both a developer and analyst. He has worked and consulted in a broad spectrum of domains – including insurance, payments and e-commerce – for both early-stage startups and established companies. He is also a passionate open-source developer, being a co-maintainer of a number of developer tools for the Clojure programming language. Further, he has been a teacher for the ClojureBridge organisation, which provides free programming workshops for underrepresented groups in tech.

A dedicated environmentalist, having worked for the National Laboratory Service arm of the UK Environment Agency before entering the software industry, he joined Cervest in 2019 with a commitment to use his expertise to build flexible and scalable distributed software systems to help our world adapt to the growing climate crisis, while promoting sustainability and science-driven decision making.

Michael holds a B.Sc. in Theoretical Physics from University College London.