Rail Vision (NASDAQ: RVSN) announced that its majority-owned subsidiary, Quantum Transportation Ltd., successfully implemented its transformer-based neural decoder on the AWS cloud, marking a milestone toward real-world quantum applications in the transportation sector. The deployment follows the recent unveiling of Quantum Transportation’s transformer neural decoder, which outperformed classical quantum error correction algorithms in simulations, and the delivery of its first universal error correction prototype, providing scalable infrastructure to process complex quantum data. The company indicated that the cloud-based implementation enables collaboration with quantum hardware partners and supports direct testing of its code-agnostic decoder on physical quantum systems, with potential long-term applications in railway anomaly detection, predictive maintenance and autonomous operations. Rail Vision completed its acquisition of a 51% stake in Quantum Transportation on Jan. 14, 2026, through a share exchange transaction.
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About Rail Vision Ltd.
Rail Vision is a development stage technology company that is seeking to revolutionize railway safety and the data-related market. The company has developed cutting edge, artificial intelligence based, industry-leading technology specifically designed for railways. The company has developed its railway detection and systems to save lives, increase efficiency, and dramatically reduce expenses for the railway operators. Rail Vision believes that its technology will significantly increase railway safety around the world, while creating significant benefits and adding value to everyone who relies on the train ecosystem: from passengers using trains for transportation to companies that use railways to deliver goods and services. In addition, the company believes that its technology has the potential to advance the revolutionary concept of autonomous trains into a practical reality.
NOTE TO INVESTORS: The latest news and updates relating to RVSN are available in the company’s newsroom at http://ibn.fm/RVSN
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