Descartes Labs has been nominated for the 2026 World AI Awards, recognising its work at the intersection of artificial intelligence, machine learning, satellite imagery and geospatial intelligence.
Built around a deceptively difficult problem — turning enormous volumes of Earth observation data into information people can actually use — Descartes Labs developed technology capable of combining satellite imagery with weather, environmental and other datasets before applying machine learning at large geographic scales.
The World AI Awards recognises organisations, individuals, products and technologies contributing to the development and practical application of artificial intelligence across industries.
Descartes Labs emerged from technology developed at Los Alamos National Laboratory and built its reputation around a cloud-based geospatial platform. Rather than simply supplying satellite images, the system was designed to handle much of the difficult work that comes before analysis: ingesting imagery, cleaning and normalising datasets, combining information from different sensors and making it available for large-scale computation.
Turning satellite pixels into usable intelligence
Satellite imagery is plentiful. Making different images comparable is another matter.
Clouds, atmospheric effects, different resolutions and differences between sensors can complicate analysis. Descartes Labs built what it called a geospatial “data refinery” to process those inputs before they reached machine-learning models.
Its platform incorporated imagery from sources including NASA’s Landsat programme and the European Space Agency’s Sentinel missions, alongside commercial imagery and complementary information such as weather data. Intel documented how users could access imagery and vector data through APIs and run analysis across thousands of cloud processor cores.
That infrastructure opened the door to something more useful than another satellite-image library: organisations could build models around specific business questions.
Agriculture became an early example. Descartes Labs worked on crop-yield prediction, while early customer and investor Cargill explored the technology across multiple business areas. The company also worked with DARPA on forecasting food-security issues in the Middle East and North Africa.
AI looks for patterns across an entire planet
The scale of the underlying data became a defining feature of the Descartes Labs approach.
By 2022, AWS said the company maintained a 20-petabyte data library and was migrating its geoprocessing and analytics infrastructure to Amazon Web Services. The platform combined high-performance computing with AI and machine learning to analyse geospatial information for sectors including agriculture, mining, defence, intelligence and consumer goods.
The practical applications were unusually varied.
Descartes Labs technology has been used to investigate crop conditions, mineral exploration, deforestation and environmental change. Earlier projects also examined methane concentrations and wildfire activity. That range matters because the underlying problem is largely the same: find meaningful changes or patterns inside geographic datasets far too large to examine manually.
Instead of asking an analyst to inspect thousands of individual satellite scenes, machine-learning models can process large areas repeatedly and surface the locations or changes that deserve attention.
Computer vision moves into defence and intelligence
The same geospatial infrastructure also found applications in government.
In 2020, Descartes Labs announced a $2.2 million contract with the U.S. Air Force Research Laboratory’s Space Technology Advanced Research programme.
The project used the company’s geospatial analytics platform alongside artificial intelligence and computer vision to support analysis of ground and airborne targets. Descartes Labs said the work was intended to improve moving-target indication and help generate actionable information from large-scale geospatial datasets.
That project illustrates why geospatial AI sits in a different category from conventional image recognition. The challenge is not simply identifying an object in one photograph. Systems may need to search enormous geographic areas, reconcile information collected at different times and by different sensors, and detect changes that become meaningful only when viewed as part of a wider pattern.
Descartes Labs technology enters a new chapter
The Descartes Labs story has since changed.
Following its acquisition by EarthDaily Analytics in 2024, technology originating with the Descartes Labs Platform has been incorporated into the EarthOne Platform. Current EarthOne documentation describes access to petabytes of normalised, interoperable geospatial data through a common interface and Python-based tools.
That makes the Descartes Labs nomination particularly interesting. The name represents a company that helped tackle one of AI’s less glamorous but critical problems: preparing huge, messy real-world datasets so machine learning can extract useful information from them.
The satellite image may be the visible part. The harder work happens underneath.
Graham Cooke, President of the World AI Awards, said:
“Descartes Labs’ nomination highlights an important side of artificial intelligence that often happens far from the public eye. Satellite and Earth observation systems generate extraordinary volumes of information, but that data only becomes valuable when organisations can turn it into something they can understand and act upon.
“Descartes Labs has explored how machine learning, computer vision and large-scale computing can help extract intelligence from our changing planet, with applications spanning agriculture, natural resources, environmental monitoring and government. We congratulate the team on its 2026 World AI Awards nomination and recognise the contribution this work has made to the development of geospatial AI.”
Descartes Labs joins organisations, researchers, entrepreneurs and technology developers being recognised through the 2026 World AI Awards.
The programme recognises organisations, individuals and technologies contributing to the development and application of artificial intelligence across industries. Geospatial intelligence offers a particularly tangible example: AI is being used not simply to generate digital content, but to interpret physical changes taking place across the Earth.
Descartes Labs helped push that idea toward planetary scale. Its work connected satellite imagery, cloud computing and machine learning in a platform designed to turn enormous datasets into information that businesses, scientists and public-sector organisations could use.
Learn more about Descartes Labs at descarteslabs.com.
Discover the World AI Awards 2026, explore the nominees and learn more about the awards at worldawards.ai.
