Liquid runs entirely on the platform. Threat detection, autonomous navigation, and real-time ISR happen on the device in front of the operator, inside the size, weight, and power budget it already has. Because inference stays local, it stays fast, and it keeps working in the conditions forward units actually operate in.
Defense contractors struggle to deploy AI in edge/battlefield environments because:
Forward and contested operations have their own rules. Connectivity, bandwidth, and GPS can never be assumed.
For defense contractors, any system that sends data to an external network is a potential security risk and ITAR violation.
A lag that's barely noticeable to commercial users could compromise a mission and endanger a team.
Defense uses often have tight size, weight, and power (SWaP) envelopes. A model that doesn't work within them, doesn't work.
Liquid's multimodal models give dismounted teams hands-free decision support and give uncrewed systems the onboard perception to operate independently, all computed on the platform.
Liquid Foundation Models are built to run in real time on the processors you already field, so the answer arrives when the operator needs it.
Handheld, headset, ground vehicle, or small UAS: Liquid is tuned to the NPU and CPU on board, the memory available, and the power envelope. The best on-device model for each platform it runs on.
AI for the world's most demanding operational environments.
Defense hardware is built to be fast, secure, and survivable. Liquid delivers the only AI capabilities aligned to that mission.
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