Long-endurance autonomous surface vessels for maritime defense and commercial ops
Seasats manufactures small, unmanned autonomous surface vessels (ASVs) for defense, commercial, and scientific applications. The tech stack—C++, ROS, Cesium, MQTT, PostgreSQL—reflects a systems-engineering-heavy org building real-time maritime autonomy with geospatial visualization and distributed messaging. Active hiring (14 roles, 9 engineering) and the project backlog (fleet maintenance, testing/deployment infrastructure, remote monitoring, production systems) signal rapid scaling from R&D into manufacturing and ops, while pain points cluster around payload integration, production throughput, and operational readiness—typical friction points when moving from prototype to deployed fleet.
Notable leadership hires: Head of Software
Seasats designs and manufactures long-endurance autonomous surface vessels for U.S. defense, commercial maritime, and scientific research missions. Founded in 2020 and headquartered in San Diego, the company combines commercial manufacturing agility with defense-grade system reliability to deliver cost-effective unmanned vessels that extend maritime operational range, improve situational awareness, and reduce personnel risk. The product is deployed to Navy bases and managed remotely via fleet monitoring systems. Operations span engineering, manufacturing, and ops; current scaling priorities include production floor efficiency, payload integration workflows, and ensuring fleet operational readiness across multiple deployment contexts.
Seasats builds on C++, ROS, Python, and MQTT for core autonomy and control, with geospatial visualization via Cesium, PostgreSQL and MySQL for fleet data, Docker for deployment, and Jetson hardware for onboard compute.
Seasats is headquartered in San Diego, California and currently hiring exclusively in the United States across engineering, operations, and manufacturing roles.
Seasats's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.