Gamaya’s robust technology platform integrates remote sensing and advanced crop modeling with world-leading AI analytics. While we aren’t the only agtech player with these capabilities, we do stand out from the rest because:

Gamaya’s robust technology platform integrates remote sensing and advanced crop modeling with world-leading AI analytics. While we aren’t the only agtech player with these capabilities, we do stand out from the rest because:

Our strong focus on sugarcane means we understand this crop in-depth and can provide tools and features that address the specific needs of the sugarcane value chain – from sugar growers, to sugar mills, to food and fuel companies.

Our proprietary AI analytics platform is industry-leading, based on IP from EPFL, Switzerland’s leading university for science and technology.

Our agronomic models are crop-specific, not generic. They have been ground truthed in various sugarcane agronomic environments over several years.

Innovative, Robust, Reliable

Remote Sensing

We collect and analyze all sorts of imagery – from simple RGB to advanced hyperspectral imaging – in order to provide assessments and recommendations related to things like crop health, nutrient levels, and presence of weeds and invasive species. This information becomes the basis for our predictive analytics models. 

Crop Modeling

Our crop-specific models are based on the multiple years of sugarcane research and experience by the Gamaya team and our partners. Tested in the various environments and situations, our crop models enhance data-science based approaches in order to reach the highest levels of precision and accuracy.

Artificial Intelligence

Our AI model stands out for its unique approach to crop prediction and management. Unlike other models that rely solely on satellite imagery, our model takes into account a diverse range of agronomic data such as soil type, crop varieties, and agronomic cycles.

Designed to address sustainable future.

Deep crop analytics focused on the outcomes:

With this unique combination of data sources, models and analytics capabilities, we can accurately predict the sugarcane’s crop development up to 12 months in advance – even before it is planted. Furthermore, we constantly revise our predictions on a weekly basis, taking into account any changes that occur throughout the growing season.

With this, we are able to model and predict crop conditions throughout the full vegetation cycle, capturing all changes and factors that can impact the crop’s growth and health. This comprehensive approach enables us to address multiple use cases and provide valuable insights for smart decisions regarding crop management throughout the entire cultivation season.

Ultimately, all of this helps the sugarcane value chain to increase yields, adopt more sustainable agronomic practices, and unleash new opportunities in the carbon markets.

Get to know more about our solutions to impulsionate yours

The Sweet Success of Deep Learning in Agriculture: How We Improved Sugarcane Yield with AI.
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Breaking Free from the Illusion: Why satellite imagery alone will not do the job of soil organic carbon measurement.
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