Ra’anana, Israel, Sept. 09, 2026 (GLOBE NEWSWIRE) -- Rail Vision Ltd. (Nasdaq: RVSN, FSE:C80) (“Rail Vision” or the “Company”), an early commercialization stage technology company transforming railway safety through advanced AI-integrated sensing systems, today announced new branding for its existing MainLine and ShuntingYard products, which will now be marketed as TrackScout and YardFlow Flex, respectively. With the updated TrackScout and YardFlow Flex branding, Rail Vision offers AI-powered perception solutions tailored to two distinct operating environments: mainline freight and passenger rail networks and complex industrial and freight yard operations.
TrackScout – Advanced AI Perception for Mainline Rail
TrackScout (formerly MainLine) is Rail Vision’s long-range AI perception system for mainline freight and passenger rail networks. Powered by multi-spectral electro-optical sensors and proprietary deep learning algorithms, the system detects and classifies hazards in real time at an extended visual range of up to 2,000 meters (1.2 miles), giving drivers critical reaction time to prevent incidents, maximize uptime, and maintain continuous operations, even under challenging weather and visibility.
The system features anomaly detection for unclassified hazards and industry-first switch-state detection, delivering clear real-time visual and acoustic alerts. Designed with a modular structure, TrackScout enables quick, simple retrofit across diverse locomotive fleets.
YardFlow Flex – AI-Powered Perception for Challenging Yard Environments
YardFlow Flex (formerly ShuntingYard) is Rail Vision’s AI-powered perception system for freight and industrial yards across locomotives and railcar movers operating in challenging yard environments. The system detects on-track and near-track hazards at distances of up to 200 meters (650 feet), including poor weather and low visibility. Key capabilities include switch-state detection, anomaly detection and sideswipe detection for rolling stock past the foul line. The system is built with a robust, modular design for seamless installation across diverse switching fleets.
TrackScout and YardFlow Flex are complemented by Rail Vision’s operational intelligence platform which uses big data analytics, real-time tracking, and continuous event recording to deliver actionable insights that maximize safety and efficiency across the entire fleet.
About Rail Vision Ltd.
Rail Vision (Nasdaq: RVSN, FSE: C80) is an early commercialization stage technology company 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, please visit https://www.railvision.io/
Forward-Looking Statements
This press release contains “forward-looking statements” within the meaning of the Private Securities Litigation Reform Act and other securities laws. Words such as “expects,” “anticipates,” “intends,” “plans,” “believes,” “seeks,” “estimates” and similar expressions or variations of such words are intended to identify forward-looking statements. For example, the Company is using forward-looking statements when it discusses the expected capabilities, performance and benefits of TrackScout, YardFlow Flex and its operational intelligence platform, the potential of these solutions to support railway safety and operational efficiency, and the Company's plans for the commercialization, deployment and marketing of its product portfolio. Such expectations, beliefs and projections are expressed in good faith. However, there can be no assurance that management’s expectations, beliefs and projections will be achieved, and actual results may differ materially from what is expressed in or indicated by the forward-looking statements. Forward-looking statements are subject to risks and uncertainties that could cause actual performance or results to differ materially from those expressed in the forward-looking statements. For a more detailed description of the risks and uncertainties affecting the Company, reference is made to the Company’s reports filed from time to time with the Securities and Exchange Commission (“SEC”), including, but not limited to, the risks detailed in the Company’s annual report on Form 20-F for the fiscal year ended December 31, 2025, filed with the SEC on March 31, 2026. Forward-looking statements speak only as of the date the statements are made. The Company assumes no obligation to update forward-looking statements to reflect actual results, subsequent events or circumstances, changes in assumptions or changes in other factors affecting forward-looking information except to the extent required by applicable securities laws. If the Company does update one or more forward-looking statements, no inference should be drawn that the Company will make additional updates with respect thereto or with respect to other forward-looking statements. References and links to websites have been provided as a convenience, and the information contained on such websites is not incorporated by reference into this press release. Rail Vision is not responsible for the contents of third-party websites.
Investor Relations:
Michal Efraty
[email protected]