Port automation, autonomous vessel perception, and subsea robotics — civil-first
Maritime AI must operate in RF-degraded, high-humidity, and mechanically harsh environments where cloud connectivity is intermittent at best. We help port operators, shipping lines, offshore asset managers, and autonomous-vessel makers deploy AI that works at the edge — from port AMR and crane automation to subsea robotics and remote predictive maintenance. Our distributed-agent and RF-spectrum primitives from Auralink provide transferable architectural foundations for port and vessel operations.
We design maritime AI architectures for disconnected, harsh, and safety-critical environments — from port AMR fleet orchestration and computer-vision berth planning to on-vessel edge inference and subsea autonomous inspection. We work within IMO MASS, DNV, and Lloyd's Register frameworks. Our distributed-agent architecture, proven in RF-spectrum-constrained EV charging coordination, transfers directly to port and vessel orchestration.
Based on common industry needs
Twelve weeks to a production-grade multi-agent system that serves as the software and control-plane complement to your cyber-physical stack — fleet intelligence, SCADA-adjacent orchestration, or autonomous operations — with the eval harness, the observability stack, and the SRE handoff your team needs to operate it
Four weeks to a strategy document, a business case, an ROI model, and a 12-month execution plan — scoped for industrial operators where OEE, safety-regime timelines, and physical-system procurement cycles are the real constraints, not just board optics
Twelve weeks to harden an edge or embedded AI pilot stuck before production — on constrained hardware, inside safety envelopes, under latency and reliability requirements the pilot was never designed to meet
The Full-Stack Physical AI layers most relevant to this sector.
A 30-minute call is enough to diagnose whether your AI initiative is stuck for industry-specific reasons — and what to do about it.