NGA’s Sequoia program will provide data labeling to train AI computer vision models to find targets of interest in the reams of satellite and airborne imagery being gathered by DoD and the Intelligence Community. (Getty images)

WASHINGTON — The National Geospatial Intelligence Agency (NGA) today issued a call to industry — worth up to $708 million over a maximum of seven years — for help training AI-driven computer vision systems to, among other tasks, process satellite imagery and identify targets of interest.

Under the Sequoia program indefinite delivery/indefinite quantity (ID/IQ) contract, chosen vendors will provide data labeling, which allows artificial intelligence and machine learning systems to discriminate among objects. It is a foundational capability in particular for NGA’s sprawling Maven program, according to NGA officials.

NGA took over Maven from the Defense Department in 2022. NGA gathers imagery from satellites and aircraft, analyzes it, and then disseminates the resultant geospatial intelligence (GEOINT) products (such as 3D maps) to users across the US government, including to DoD leaders and military commanders.

“For example, the ID/IQ contract will support the NGA Maven Program, which applies AI capabilities to intelligence, surveillance and reconnaissance sensors and platforms, primarily through computer vision,” the NGA announcement said. “The NGA Maven CV [computer vision] algorithms, which rely heavily on robust data labeling, can perform a number of automated tasks, including but not limited to object detection, object tracking, object classification and pattern detection.”

The Sequoia contract also will support “natural language processing, analytic models and AI/ML models that support business process automation for the GEOINT mission,” the announcement added.

Vice Adm. Frank Whitworth, NGA director, told reporters on Aug. 30 that the call is “the largest data labeling request for proposal in the US government,” and “represents a significant investment in computer vision, machine learning and AI.”

The increasing amount of GEOINT data pouring in from myriad new satellites and other sensor platforms is posing a challenge for the Intelligence Community. While AI systems will help speed analysis, AI visual models first must be taught to accurately recognize military targets and ferret out abnormal activities.