Agritech

Computomics Raises 6.3 Million Euros for AI-Powered Plant Breeding

Which plants will be able to cope with the climate of the future? Computomics aims to answer this question using genomic data and machine learning, and has raised 6.3 million euros to do so.
News by Marc Nemitz Marc Nemitz · Tübingen, 19. August 2026

The Tübingen-based AgTech company Computomics has closed a Series B funding round totaling 6.3 million euros. The round is led by the Convent Capital Agri Food Fund, which is investing five million euros on its own. Existing investors High Tech Gründerfonds, MBG Baden-Württemberg, and Amathaon Capital are also participating again.

Computomics plans to use the fresh capital to scale its platform for climate-resilient plant breeding and establish it more firmly in commercial breeding programs.

When Plant Breeding Lags Behind Climate Change

The timing of this funding could hardly be more timely. Heat and drought are increasingly taking their toll on European agriculture. At the same time, there is a fundamental problem with the development of new plant varieties: plant breeding takes time.

Some of the varieties coming to market today were selected and tested under climatic conditions that are only limitedly comparable to those of the years in which they will be grown.

This is exactly where Computomics comes in.

Founded in 2012, the company combines machine learning, genomic data, environmental data, and results from field trials to predict how certain genotypes will perform under different conditions.

Factors such as temperature, precipitation, and soil conditions are incorporated into the models.

AI Aims to Make Better Use of Years of Field Trials

For plant breeders, this raises crucial questions: Which candidates cope better with heat and drought? Which varieties deliver consistent results under varying environmental conditions? And for which regions is a particular variety especially well-suited?

Breeders have never lacked ambition when it comes to climate resilience. What they lacked was a way to identify these traits before the field reveals them—a process that takes years, which they no longer have.

Sebastian J. Schultheiss, CEO and Co-Founder

The ×SeedScore® platform is designed to enable such predictions on the scale of commercial breeding programs. Computomics is already collaborating with commercial breeders in sectors such as field crops, vegetables, forage crops, and specialty crops.

With this new funding, the technology will now be deployed on a significantly broader scale.

Convent Capital Invests Five Million Euros

The Convent Capital Agri Food Fund is providing the largest share of the funding round with five million euros. Existing investors, such as High Tech Gründerfonds, MBG Baden-Württemberg, and Amathaon Capital, as well as the company’s founders and scientific advisors, are also participating.

For lead investor Convent Capital, Computomics combines economic growth with a potentially increasing environmental impact. More accurate predictions could make breeding programs more efficient and help adapt plant varieties more quickly to changing climatic conditions.

The High Tech Gründerfonds has also been supporting Computomics since the seed phase. HTGF Principal Frank Hensel points out that AI-based breeding of stress-resistant crops is now also part of the German federal government’s High-Tech Agenda.

AI Meets Agriculture

Computomics thus belongs to a sector of the AI economy that receives significantly less public attention than generative AI, but which could simultaneously have a considerable impact on real-world value chains.

This is because climate change is not only altering average temperatures. For agriculture, factors such as heat waves, drought, changing precipitation patterns, and regional variations are critical.

This could give breeders a significant time advantage. And it is precisely this factor that is likely to become increasingly crucial: While the development of new varieties takes years, their future growing conditions are already changing today.


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