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AI use case
Gecko Robotics won a $71M U.S. Navy contract in March 2026 to deploy wall-climbing AI inspection robots across Pacific Fleet warships, identifying repairs 50 times faster than h…
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Title
U.S. Navy Wall-Climbing AI Inspection Robots ($71M Contract)
Content
The U.S. Navy and General Services Administration awarded Gecko Robotics a $71 million contract in March 2026 to deploy wall-climbing AI inspection robots and artificial intelligence systems across Pacific Fleet warships, including destroyers, amphibious warships, and littoral combat ships. Gecko wall-climbing robots can identify repairs up to 50 times faster and more accurately than human inspectors, and can perform inspections before ships reach their dock, enabling the right people and parts to be in place for faster repairs. The robots combine visual inspection with predictive maintenance AI to predict what things are going to fail and how to fix them fast, minimizing ship downtime. Gecko Robotics, launched in 2013, builds robots that conduct in-depth inspections of infrastructure and large equipment by climbing walls to scour ships hulls for structural or material weaknesses that human eyes might miss. The company also makes drones that analyze joints, connections, holes, and other flaws. Navy Chief Technology Officer Justin Fanelli stated that pure-play defense and dual-use companies like Gecko Robotics are moving the needle on outcome metrics by orders of magnitude. The contract means any Department of Defense branch can use Gecko AI and robotics, and the technology is part of the Navy effort to reach 80 percent fleet readiness and address its shortage of ships. Gecko is already working with the Navy to speed maintenance of aircraft carriers and submarines, deploying autonomy and robotics prior to ships entering dry dock facilities to assess material health and enable targeted, efficient repairs.
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Pittsburgh
Company/Organization
Gecko Robotics
Continent
North America
Country
United States
Category
Industrial Machinery & Supplies & Components
Type
Deployment
Id
40fe5dd8-66e7-4ce3-aba5-3f7abd050ff7
Created At
2026-04-03T17:25:06.239795+00:00