AI systems often fail after deployment. A new test shows they can rapidly adapt to stay effective in the field.

AUSTIN, Texas, April 28, 2026 /PRNewswire/ — As the United States pushes to scale autonomous military systems, a central challenge has been keeping AI operational as conditions change in the field. Striveworks has been quietly working to address these failures across the Department of War, including the U.S. Navy. The Austin-based company has demonstrated that AI can operate continuously across multiple vessels simultaneously, maintaining accuracy even as conditions change at sea.

The Navy demonstration comes as the Pentagon speeds efforts to scale autonomous systems, which can extend U.S. coverage across the sea and other domains, often without putting our military at added risk. This shift is driven partly by growing national competition, as China and others invest billions annually in advanced AI and autonomous military capabilities. Autonomous vessels in particular are so central to future U.S. maritime operations that Congress recently committed more than $2 billion to accelerate unmanned service vehicle (USV) adoption.

Government reports show that, in practice, many AI systems are trained once and updated infrequently, leaving model performance to degrade over time. In defense environments—where weather, visibility, and adversaries are constantly impacting theaters of operation—their continuous high performance is essential to operators. When that performance degrades, the military must revert to manual analysis, limiting its ability to compete in theaters of operation.

“The critical challenge facing our military today is keeping AI models working once they’re deployed, especially at scale,” said Jim Rebesco, Striveworks’ cofounder and CEO. “Now, we’ve proven that continuity can happen as part of daily operations, instead of the delayed cycles that can represent risk to our men and women in uniform.”

In the Navy demonstration, Striveworks approached the problem differently. Its Chariot platform incorporates new operational data continuously, applies updates regularly, and delivers retrained models at the speed of need, measured in hours. Striveworks demonstrated rapid model transfer between different vessels and sensors across various sea states. Chariot provided rapid high quality target identification, tracking, and monocular passive ranging complete with full data lineage and no model or data IP restrictions. This bolsters the AI-assisted Commander’s confidence, assuring the advantage to stay aligned with changing conditions rather than fall victim to them.

Chariot integrates easily with the Navy’s existing infrastructure. By delivering processed insights instead of raw data, Striveworks’ software reduces bandwidth demands while giving operators faster, clearer information.

The Navy has spent years advancing autonomous vessels as part of a broader push toward distributed maritime operations. Striveworks’ work with the Navy builds on its deployments across the Army and Combatant Commands, reflecting a broader shift in defense from experimental AI pilots to systems expected to perform reliably in live missions.

ABOUT STRIVEWORKS
Striveworks helps organizations harness the power of artificial intelligence to solve real-world national security challenges, serving as the operational command center that connects data, models, and mission outcomes. The company’s AIOps platform, Chariot Core, allows organizations to rapidly build, launch, and maintain AI models in hours, not months. Users can deploy them with minimal friction and maintain performance even in contested settings. Striveworks delivers trustworthy AI-powered analysis by creating models that “learn” and stay ahead of their environment at machine speed. The company recently closed a Series B, led by Washington Harbour Partners.

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SOURCE Striveworks