Capability

Multi-Source Data Collection and Integration: In Situ, Proximal, and Remote Sensing

ML-powered field diagnostics that seamlessly integrate with existing data systems

Beyond human-level accuracy

Our advanced computer vision models identify crop diseases with high accuracy, reducing human error and improving consistency across large-scale surveillance efforts. Our AI models continuously learn from new field data, enhancing detection accuracy.
From field to prediction in real-time

Data from our mobile apps feeds directly into the Command Centre platform, enabling real-time monitoring and predictive modelling for proactive disease management.

Pushing the boundaries

Emerging sensing technologies include UAVs (drones) equipped with multispectral and thermal cameras capable of capturing high resolution data (5 cm pixel resolution). Moreover, in-field environmental sensors, such as airborne sequencing or microscopy-based tools detect pathogens, such as fungal spores, providing a step change in airborne pathogen surveillance.
Interactions across technologies

Our high-quality, labeled datasets from UAVs and other sensing technologies improve the performance of large-scale, satellite-based disease monitoring models.

Building a data ecosystem

We combine our satellite-based surveillance, drone imagery, and field data with third-party sources to create a comprehensive disease monitoring ecosystem.
From fields to landscapes

Advanced data processing pipelines integrate diverse datasets, enabling robust, scalable analytics for predictive modeling and decision support.