In a major step forward for maritime safety, Sea.AI has launched the MS-ParadiseAI project in collaboration with Silicon Austria Labs.
Supported by Upper Austria’s “AI-Region Upper Austria 2024” initiative, this project intent to demonstrate the power of Edge-AI to elevate safety standards, accelerate response times, and strengthen data security in maritime navigation systems.
The MS-ParadiseAI project leverages Edge-AI, which allows data processing to happen directly on devices at the edge of the network rather than through a centralized server or cloud.
This architecture drastically reduces response times—a critical advantage in the fast-moving maritime world—while enhancing both resilience and data security.
In environments as data-limited as the open sea, Edge-AI proves to be an optimal solution for achieving robust, efficient, and reliable safety systems.
Silicon Austria Labs (SAL), renowned for its pioneering research in microelectronics and AI, is a natural partner for Sea.AI in this endeavor.
SAL brings expertise in edge computing and industrial AI applications, which are key to the success of MS-ParadiseAI.
Together, the teams aim to redefine maritime safety with a system that not only adapts to the unique challenges of the marine environment but also demonstrates trustworthy, ethical AI usage.
“MS-ParadiseAI project will enhance our collision avoidance systems with multi-modal, multi-task learning capabilities. We’re building smarter, more adaptable systems that can respond quickly to dynamic ocean conditions. Our partnership with Silicon Austria Labs empowers us to push the boundaries of what AI can achieve for maritime safety.”
"Collaborating with SEA.AI allows us to apply our Edge-AI expertise in a real-world, safety-critical application. MS-ParadiseAI is all about building resilient, high-performance AI that adapts to real challenges at sea. Together, we’re creating solutions that redefine the possibilities for navigation and safety."
MS-ParadiseAI integrates efficient training data selection mechanisms and employs multi-modal, multi-task learning to create a system that’s uniquely responsive and adaptable.
This project is not just about advancing the technology of today; it’s about building the foundation for tomorrow’s safe and secure maritime operations.
This vision aligns seamlessly with Upper Austria’s #upperVISION2030 strategy, which seeks to position the region as a global leader in trusted, transformative AI technology.
MS-ParadiseAI is a testament to the strength of Upper Austria’s support for AI-driven innovation in the industrial sector, further establishing the region as a hub for forward-thinking technology that has real, positive impacts on safety and efficiency.
Silicon Austria Labs GmbH (SAL) is Austria’s leading research center for electronics and software-based systems (ESBS) – they are the technological backbone of digitalization.
More than 300 employees are currently working on pioneering solutions for environmental protection, health, energy, mobility and safety at the Graz, Villach and Linz sites.
SAL brings together key players from industry and science and thus valuable expertise and know-how and conducts cooperative, application-oriented research along the ESBS value chain. Cooperative projects (in accordance with European state aid law) are co-financed by SAL and enable a fast and unbureaucratic project start.
In this way, SAL is shaping Austria and Europe as a high-tech location and developing the future.
Radar sees a contact. AIS shows a name, provided the vessel chooses to broadcast one. When a threat USV does neither, optical AI is the only sensor layer that still sees it. That is the gap SEA.AI was built to close.
SEA.AI is growing in North America, new team, better support, wider availability. We’re strengthening our presence across North America with new talent, expanded support, and broader access to our safety systems.
Detection tells you what is on the water. Multi-Object Tracking tells you what each contact is, where it came from, and where it is going — for every object in the scene, simultaneously. That is the difference between a snapshot and operational intelligence.
