Rail Vision Ltd. (NASDAQ: RVSN, FSE: C80) announced that its AI-powered ShuntingYard system has been integrated into Railserve’s newly introduced YardGUARD industrial railyard safety system. The integration positions the ShuntingYard system as a core technology within the WatchGUARD situational awareness and obstacle detection solution, according to a press release.
This development follows the companies’ recently announced memorandum of understanding and combines Rail Vision’s perception technology with communications and cloud-based monitoring capabilities. The integrated system provides real-time visibility, obstacle detection, synchronized alerts, and automatic braking support. The ShuntingYard system is being showcased this week at Railway Interchange 2026 in Omaha, Nebraska, as part of Railserve’s broader yard safety platform.
Rail Vision is an early commercialization stage technology company that is transforming railway safety through advanced AI-integrated sensing systems. The company develops and commercializes proprietary, multi-spectral electro-optic platforms that provide extended-range situational awareness and real-time hazard detection. Using machine learning algorithms to identify and classify obstacles, Rail Vision’s technology enhances safety, improves operational efficiency, and supports continuity across deployments.
The company’s cloud-based platform complements its products by transforming railway operational data into actionable insights that help optimize performance, reduce downtime, and improve safety. As the company expands its global footprint, it delivers AI-driven perception that supports safer operations, reduces operational risk, and enables the transition to fully autonomous operations.
Rail Vision holds a 51% stake in Quantum Transportation, which has an exclusive sub-license for rail technologies under an innovative pending patent in quantum error correction owned by Ramot, the technology transfer company of Tel Aviv University.
For more information, visit the company’s newsroom at http://ibn.fm/RVSN.
