Climate smart decisions supercharged by AI

Powered by our revolutionary platform, our team has built intuitive and easy-to-use applications rooted in field-to-biome machine learning. Designed to ensure business continuity and sustainable growth in the face of climate uncertainty, our platform empowers you to make smarter choices today and adapt positively to climate change for the future.

DecisionVest

Enterprise-grade, real-time crop performance monitoring for buyers.

The pressures on decision making for procurement, sustainability, and risk teams have never been greater. Access to actionable insight, early, and accurate in-season yield predictions, and future risk forecasts is crucial for maintaining your competitive edge.

So, we built DecisionVest for decision makers at CPG businesses, grain companies, cooperatives, and food processors, so you can make early and confident decisions across single or multiple product categories around the world.

Feature highlights

Performance monitoring

Easy-to-use interactive tools, visualisations, maps, and real-time insights, make it easy to see what’s happening right now.

Performance tracking

Easy-to-use interactive tools, visualisations, maps, and real-time insights, make it easy to see what’s happening right now.

Real-time and personalised

Personalised yield predictions at an order level, right down to individual farms or even fields dynamically monitor your global supply.

Real-time and personalised

Personalised yield predictions at an order level, right down to individual farms or even fields dynamically monitor your global supply.

Advanced warnings

Early alerts for risks such as weather events, changes in expected yield and more. Take early supply decisions and keep other stakeholders informed.

Advanced warnings

Early alerts for risks such as weather events, changes in expected yield and more. Take early supply decisions and keep other stakeholders informed.

‘What if’ planning

Simulation and scenario planning tools highlight natural capital fluctuations – from water and land-use to climatic variations – that impact yield.

‘What if’ planning

Simulation and scenario planning tools highlight natural capital fluctuations – from water and land-use to climatic variations – that impact yield.

Less data wrangling, more insights

Weekly and daily intelligence powered by multiple ‘context relevant’ data libraries enables you to watch the season unfold in real time and optimise decisions.

Less data wrangling, more insights

Weekly and daily intelligence powered by multiple ‘context relevant’ data libraries enables you to watch the season unfold in real time and optimise decisions.

FarmVest

Field-level and personalised forecasts for growers.

FarmVest is a yield management and prediction tool designed specifically for growers. It delivers personalised analysis of each field, tracks yield drivers throughout the season, and provides daily yield predictions.

FarmVest also provides field-level ‘long-range’ planning analysis, helping growers decide what and when to plant, and which varieties to select based on their unique geo-variables and practices.

Feature highlights

Improve productivity

Track crops from planting to harvest with automated daily yield predictions. Early warnings, expected output and quality indicators help you manage the season.

Improve productivity

Track crops from planting to harvest with automated daily yield predictions. Early warnings, expected output and quality indicators help you manage the season.

Monitor weather impacts

High-quality, location specific weather forecasting with short, medium and long-range outlooks.

Monitor weather impacts

High-quality, location specific weather forecasting with short, medium and long-range outlooks.

Troubleshoot

Field-level crop health monitoring using advanced imagery, enables you to identify potential crop issues from your mobile, then investigate on the ground.

Troubleshoot

Field-level crop health monitoring using advanced imagery, enables you to identify potential crop issues from your mobile, then investigate on the ground.

Profile your fields

Maintain an ongoing digital farm profile for multiple fields and crops. Track activity related to preparation, planting and harvesting – all in once place.

Profile your fields

Maintain an ongoing digital farm profile for multiple fields and crops. Track activity related to preparation, planting and harvesting – all in once place.

Plan for the future

Best-fit adaptation choices modelled on long-term natural capital and climate trends – uniquely scaled to your farm.

Plan for the future

Best-fit adaptation choices modelled on long-term natural capital and climate trends – uniquely scaled to your farm.

CODEX

Aggregated insights and shared intelligence for policy and business.

The Cervest Open Data Xchange (CODEX) provides bespoke crop-related intelligence and alternative data to those making decisions that affect the world’s natural capital – e.g. public policy, insurance and credit. Our revolutionary multi-crop machine learning technology can generate critical data to help you solve challenges such as:

  • Ensuring early warnings on food security for agencies
  • Customised pricing for climate insurance
  • Quantifing climate-related risk for disclosures and climate finance
  • Providing scientific evidence for adaptation policy by crop or region

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.

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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.