Gecko Robotics Secures $71M Contract with U.S. Navy
▼ Summary
– The U.S. Navy faces a severe maintenance crisis, with roughly 40% of its fleet unavailable and a repair backlog costing an estimated $13 to $20 billion annually.
– Gecko Robotics secured a major Navy contract worth up to $71 million, with an initial $54 million award, to begin inspecting 18 Pacific Fleet ships using its robots and sensors.
– The company’s AI platform, Cantilever, creates detailed digital twins of vessels from inspection data, enabling much faster and more accurate identification of necessary repairs.
– This technology allows inspections to occur before a ship enters dry dock, enabling advanced planning for parts and personnel to significantly reduce repair timelines.
– The contract is structured so that any Department of Defense branch can access Gecko’s AI and robotics, not just the Navy, to improve overall military readiness.
A significant new contract aims to tackle a massive maintenance backlog plaguing the U.S. Navy, leveraging robotics and artificial intelligence to restore critical fleet readiness. Gecko Robotics has secured a pivotal five-year contract with the U.S. Navy and the General Services Administration, valued at up to $71 million. This represents the largest robotics agreement the Navy has ever signed. The initial award is set at $54 million and will focus immediately on 18 vessels within the Pacific Fleet, including destroyers and amphibious warships.
The core issue is stark: approximately 40% of the Navy’s fleet is unavailable at any given moment due to maintenance delays. This backlog, according to company estimates, costs the service between $13 billion and $20 billion each year. With ships languishing in dry dock for extended periods, the Navy has struggled to meet its repair timelines, achieving only 41% on-time completion in 2025 against a goal of 71%.
Gecko’s solution involves deploying its wall-climbing TOKA robots, drones, and sensor arrays to meticulously inspect ship hulls, decks, and welds. These systems gather vast amounts of structural data in a fraction of the time required by human inspection teams. This raw information is then processed by the company’s Cantilever AI platform, which constructs a detailed digital twin, a dynamic, updatable model of each vessel’s structural integrity.
This technological approach allows the Navy to identify necessary repairs up to 50 times faster and with greater accuracy than traditional methods. Perhaps more importantly, inspections can occur before a ship ever enters dry dock. This enables the Navy to pre-stage the correct parts and skilled personnel, transforming a reactive process into a predictive one and drastically reducing vessel downtime.
The contract’s structure through the GSA is strategically important, as it allows any branch of the Department of Defense to utilize Gecko’s robotics and AI services under the same agreement. This broad access could accelerate modernization efforts across the military. The deal arrives amid heightened focus on U.S. naval capacity and shipbuilding, areas where American industry has fallen behind global competitors.
Gecko Robotics is not a newcomer to defense applications. The Pittsburgh-based company has previously worked with the Navy, deploying its robots on aircraft carriers and destroyers, and has collaborated with major contractors like L3Harris on digital twins for military aircraft. Earlier this year, a partnership with a Naval Nuclear Propulsion Program contractor demonstrated the potential to slash inspection times on nuclear components by up to 90%.
Company CEO Jake Loosararian emphasized that “readiness isn’t just a metric. It’s all that matters,” framing the partnership as providing an “unfair advantage” through predictive technology. The company, last privately valued at $1.25 billion, argues that its experience inspecting critical infrastructure in power generation and heavy manufacturing directly translates to the challenging environment of naval vessels. Whether assessing a boiler or a warship, understanding structural health requires the same meticulous, data-driven approach.
(Source: The Next Web)
