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 Rail Vision’s technology as a core component within the WatchGUARD situational awareness and obstacle detection solution, following a recently signed memorandum of understanding between the two companies.
The combined system leverages Rail Vision’s perception technology alongside Railserve’s communications and cloud-based monitoring capabilities. It provides real-time visibility, obstacle detection, synchronized alerts, and automatic braking support, aiming to enhance safety in industrial railyard operations. 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 focused on transforming railway safety through advanced AI-integrated sensing systems. The company develops multi-spectral electro-optic platforms that provide extended-range situational awareness and real-time hazard detection. Machine learning algorithms identify and classify obstacles, improving safety, operational efficiency, and continuity across deployments.
In addition to its onboard systems, Rail Vision’s cloud-based platform converts railway operational data into actionable insights to optimize performance, reduce downtime, and improve safety. The company aims to support the transition to fully autonomous operations by delivering AI-driven perception that reduces operational risk.
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 on Rail Vision, visit the company’s newsroom at http://ibn.fm/RVSN. The full press release is available at https://ibn.fm/7wqO8.
