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Project Maven
AI military intelligence program From Wikipedia, the free encyclopedia
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Project Maven (officially Algorithmic Warfare Cross Functional Team) is a Department of Defense initiative launched in April 2017 to accelerate the adoption of machine learning and data integration across U.S. military intelligence workflows. Currently, the program operates under the National Geospatial-Intelligence Agency and encompasses multiple applications across the Department of Defense spanning military operation targeting support, data integration and visualization for analysts, and training machine learning models on labeled datasets of military assets and infrastructure.
The program originated under Deputy Secretary Robert O. Work after he raised concerns about China's advances in defense applications of artificial intelligence. The AWCFT integrates data from drones, satellites, and other sensors to flag potential targets, present findings to human analysts, and relay their decisions to operational systems. Project leaders, Col. Drew Cukor and Lt. Gen. Jack Shanahan, framed the program as human-in-the-loop decision support inside the Department of Defense rather than as an autonomous weapons platform.
Contractors supporting Maven have included Google, which withdrew in 2018 after internal protests, and follow-on integrators such as Palantir, Anduril, Amazon Web Services, and more.
The Pentagon credits Maven with providing 2024 targeting support for U.S. airstrikes in Iraq, Syria, and Yemen, along with locating hostile maritime assets in the Red Sea.
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Initially, the effort was led by Robert O. Work who was concerned about China's military use of the emerging technology.[1] Reportedly, Pentagon development stops short of acting as an AI weapons system capable of firing on self-designated targets.[2] The project was established in a memo by the U.S. Deputy Secretary of Defense on 26 April 2017.[3]
At the second Defense One Tech Summit in July 2017, Cukor also said that the investment in a "deliberate workflow process" was funded by the Department [of Defense] through its "rapid acquisition authorities" for about "the next 36 months".[4]
According to Lt. Gen. of the United States Air Force Jack Shanahan in November 2017, it is "designed to be that pilot project, that pathfinder, that spark that kindles the flame front of artificial intelligence across the rest of the [Defense] Department".[5] Its chief, U.S. Marine Corps Col. Drew Cukor, said: "People and computers will work symbiotically to increase the ability of weapon systems to detect objects."[6] Project Maven has been noted by allies, such as Australia's Ian Langford, for the ability to identify adversaries by harvesting data from sensors on UAVs and satellite.[7]
In 2022, the National Geospatial-Intelligence Agency took over Project Maven.[8]
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Project Maven uses machine learning algorithms to analyze and fuse vast amounts of surveillance data from multiple sources made possible through data integration using Palantir Technologies.[9][10]
The data sources include photographs, satellite imagery, geolocation data (IP address, geotag, metadata, etc) from communications intercepts, infrared sensors, synthetic-aperture radar, and more. Machine learning systems, including object recognition systems, process the data and identify potential targets, such as enemy tanks or location of new military facility. The training dataset included at least 4 million images of military objects such as warships, labelled by humans. The user interface is called Maven Smart System. It could display information such as aircraft movements, logistics, locations of key personnel, locations on the no-strike list, ships, etc. Yellow-outlined boxes show potential targets. Blue-outlined boxes show friendly forces or no-strike zones. It could also transmit, directly to weapons, a human decision to fire weapons.[10]
Contractors
Initially, The Pentagon collaborated with Google, but in 2018, Google employees, including Meredith Whittaker, staged walkouts protesting Google's involvement in Project Maven.[11][12] Subsequently, Google did not renew the contract with Pentagon and Palantir took over the contract.[13][9]
Companies that have contributed to the data integration include Palantir, Amazon Web Services, ECS Federal, L3Harris Technologies, Maxar Technologies, Microsoft and Sierra Nevada Corporation. ECS Federal has served as primary support contractor and led AI integration for Project Maven since 2017.[14][15][16] At least 21 private companies had been involved.[17]
Anduril Industries entered the program in 2018 to deploy its sensor fusion platform and edge hardware for data capture.[18] In December 2024 Anduril and Palantir announced a consortium that links Anduril's Lattice Mesh with Maven Smart System and Palantir's AI Platform to move tactical sensor data into AI-supported analyst workflows.[19][20]
As of September 2025, the director of the National Geospatial-Intelligence Agency claimed that by June 2026, Maven will begin to transmit "100 percent machine-generated" intelligence to combatant commanders using LLM technology. Booz Allen was the defense contractor responsible for the LLM-integration phase.[21]
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Applications
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Scarlet Dragon exercises
The 18th Airborne Corps is the main tester of Project Maven. With collaborating arms organization in US and UK, it has used Maven and weapons systems connected to it to strike targets from bombers, fighter jets and drones.[10]
Beginning in 2020, Maven was used for live-fire exercises ("Scarlet Dragon exercises").[17] The first took place at Fort Bragg. An AI system identified a tank in satellite images, the human approved, and the AI system signaled an M142 HIMARS to strike the target (in this case, a decommissioned tank). It was the first AI-enabled artillery strike in the US army.[10]
There are 6 steps in the kill chain: identify, locate, filter down to the lawful valid targets, prioritize, assign them to firing units, and fire.[17] Of these 6 steps, Maven can perform 4. A senior targeting officer estimates that with Maven, he could decide on 80 targets per hour, vs 30 targets per hour without Maven.[10] The efficiency was comparable with the targeting cell used during Operation Iraqi Freedom, but whereas the OIF used a targeting cell with roughly 2000 staff, the 18th Airborne used a targeting cell with 20 people.[17]
Conflict use
In the 2021 Kabul airlift, Maven was used to display the situation on the ground. It could simultaneously display data feeds, such as aircraft movements, logistics, threats and locations of key personnel such as Chris Donahue.[10]
In the 2022 Russian invasion of Ukraine, the US has used satellite intelligence and Maven Smart System to supply the locations of Russian equipment to Ukrainian forces.[10]
In February 2024, Maven was used for narrowing targets for airstrikes in Iraq and Syria. It was also used for locating rocket launchers in Yemen and surface vessels in the Red Sea, some of which were destroyed in February 2024 according to CENTCOM.[10][22]
References
External links
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