Domino Data Lab

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When Department of the Navy CTO Justin Fanelli spoke with TechCrunch recently, he made it clear, applied AI is the Navy's top technology priority. In that same interview, he noted that Domino Data Lab is now running the Navy's machine learning pipeline. That mention is a great honor, but it also highlights a deeper challenge across defense agencies. It doesn’t matter how fast AI evolves if federal acquisition pathways can’t keep up. Traditional acquisition can take long enough that the technology, requirements, or mission needs change before a contract is awarded. The core issue is that government procurement often can’t keep pace with commercial AI development. That’s why the Navy's new National Security Prototype to Production Consortium is such an important step forward. By using Other Transaction Authority, the consortium allows program offices to move working prototypes into production without forcing them to launch a brand new competition at every stage. Equally important, members commit to strict composability standards so software plugs cleanly into existing systems instead of sitting in an isolated silo. I have seen firsthand why this works. On Project AMMO, the Navy brought in Domino as the software integration layer across multiple vendors. By separating software updates from hardware cycles, deployment times dropped from six months down to six days. The consortium scales that concept across the entire Department of the Navy. I am proud that Domino is an inaugural member. For Navy program offices looking to move applied AI into the field today, the framework to make it happen is officially in place. Project AMMO case study: https://lnkd.in/ewiTpCvf

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