BlackSky Technology won a more than $24 million, four-year, National Geospatial-Intelligence Agency (NGA) Luno A Facility Operational Monitoring (FOMO) delivery order for global monitoring of military and economic facilities. As part of the order, BlackSky has received an initial base and surge option award of $2 million.
“Securing this Luno A task order continues BlackSky’s long record of success delivering our industry-leading commercial real-time, AI-enabled dynamic monitoring capabilities at machine speed and scale in service to U.S. national security,” said Brian O’Toole, BlackSky CEO. Under the delivery order, BlackSky will perform AI-enabled object and pattern-of-life change detection to monitor trends and anomalies in vehicle, aircraft, vessel, railcar, and ground equipment activity at military and economic facilities worldwide, including ports, airfields, military installations, and railways.
“With unmatched speed and economics, BlackSky continues to improve upon our first-of-its-kind space-based intelligence system with the coming addition of our very high-resolution Gen-3 satellites to our high frequency, low latency constellation that will provide even more rapid, detailed, and precise insights to support the critical needs of our customers,” said O’Toole. BlackSky monitors over more than 30 million square kilometers of the Earth’s surface for the NGA. In October, NGA selected BlackSky for the five-year, up to $290 million Luno A multi-award, indefinite-delivery, indefinite-quantity contract to monitor global economic and environmental activity and military capability using high-cadence, rapid revisit satellite imagery and AI-driven change-detection analytics.
The Luno A contract also contributes to the creation of new products, data, and services that employ innovative uses for artificial intelligence to manage high volumes of data, produce deeper insights, and boost predictive analytical capabilities. BlackSky’s scalable and cost-effective AI tools allow for more frequent data-intensive, broad area search and discovery queries than traditional solutions.
