US Navy awards $100 million AI contract to detect mines in days instead of months

US Navy Accelerates Mine Detection with AI Partnership

The US Navy has awarded a $99.7 million contract to San Francisco-based Domino Data Lab, marking a significant shift in how naval forces approach underwater mine detection in contested waters1

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. The deal expands Domino's role as the AI backbone of Project AMMO—Accelerated Machine Learning for Maritime Operations—a program designed to make underwater mine detection faster, more accurate, and less dependent on naval personnel3

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. This technology addresses an urgent operational need in the Strait of Hormuz, where detecting Iranian mines has become critical to maintaining global trade security and protecting oil shipments during a tenuous ceasefire between the US and Iran4

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From Six Months to Days: The Speed Advantage

The core value proposition of this $100 million contract lies in dramatically accelerated training cycles for AI detection models. Before Domino Data Lab's involvement, updating detection algorithms that power unmanned underwater vehicles (UUVs) to recognize new or previously unseen mines could take up to six months2

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. The company claims it has reduced that timeline to mere days3

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. Thomas Robinson, Domino's chief operating officer, explained the strategic implications: "If there were UUVs in the Baltic Sea trained on Russian mines, and then they needed to be deployed to the Strait of Hormuz to detect Iranian mines, with Domino's technology, the Navy could be ready in a week rather than a year"5

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. This rapid adaptation capability transforms mine-hunting capabilities from a slow, ship-based operation into an agile, AI-driven process that can respond to emerging threats in real time.

How the Technology Works in Maritime Operations

The software integrates data from multiple sensor types, including side-scan sonar and visual imaging systems, creating a comprehensive detection framework for underwater drones1

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. This multi-sensor approach allows operators to monitor how various AI detection models perform in the field, identify failures, and push corrections to improve performance without retrieving the vehicles2

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. Rather than sending information back to a lab and waiting for AI developers to train new models, the system enables real-time updates as unmanned underwater vehicles operate in shipping lanes1

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. Robinson characterized the transformation succinctly: "Mine-hunting used to be a job for ships. It's becoming a job for AI"4

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Strategic Context and Pentagon AI Adoption

This contract reflects broader Pentagon efforts to integrate AI across military operations. The Department of Defense has announced deals with seven major AI tech companies—SpaceX, OpenAI, Google, Nvidia, Reflection, Microsoft, and Amazon Web Services—to deploy large language models across classified networks1

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. These tools sift through massive data volumes and identify patterns impossible for humans to process quickly, accelerating analysis and decision-making. DARPA has also called for proposals to develop next-generation deep-sea underwater drone platforms that can be built rapidly1

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. The focus on detecting Iranian mines in the Strait of Hormuz carries immediate operational urgency, as President Donald Trump has stated the US Navy is actively clearing Iranian mines from this vital sea route for oil shipments. Sweeping for underwater explosives could take months despite the ongoing ceasefire, making AI-enabled speed essential for reducing risk to sailors and maintaining global economic stability.